##The command ##source("http://parker.ad.siu.edu/Olive/linmoddata.txt") ##is an easy way to get these data sets into R. # For references, see Olive (2018), Prediction and Statistical Learning. # data sets are listed alphabetically as # Abraham and Ledolter (2006, pp. 360-364), death data # Agresti (2002, p. 127), crab data # Beaton, Martin, Mullis, Gonzales, Smith and Kelly (1996), timss data: # Box and Cox (1964), wool textile data 3^3 design # Buxton (1920) data # Collett (1999, pp. 216-219), rotifer data # Cook and Weisberg (1999a), mussels data # Cook and Weisberg (1999a), species data # Gladstone (1905), brain data and glado data # Hebbler, B. (1847), marry data``Statistics of Prussia," # Johnson (1996) bodyfat data # Minor (2012) State data # Myers, Montgomery and Vining (2002): ceriod Poisson regression data # Myers, Montgomery and Vining (2002): popcorn data # SAS Institute (1985, p. 146) Fitness Club Data # Schaaffhausen (1878), museum data # Wisseman, Hopke and Schindler-Kaudelka (1987) pottery data ##Abraham and Ledolter (2006, pp. 360-364), death data dmv <- c(62,182,17,22,13,11,12,6,9,7,17,4) aggrav<- c(1,1,2,2,3,3,4,4,5,5,6,6) race<- c(1,0,1,0,1,0,1,0,1,0,1,0) dy<-c(2,1,2,1,6,2,9,2,9,4,17,4) dx <- cbind(aggrav,race) rm(aggrav,race) ##Agresti (2002, p. 127), crab data #Y = number of satellites (number of male crabs near the female crab) #color (2: light medium, 3: medium, 4: dark medium, 5: dark) #spine (1: both good, 2: one worn or broken, 3 both worn or broken) #width (carapace width in cm) #weight (of female crab in grams) craby <- c(8, 0, 9, 0, 4, 0, 0, 0, 0, 0, 0, 0, 11, 0, 14, 8, 1, 1, 0, 5, 4, 3, 1, 2, 3, 0, 3, 5, 0, 0, 4, 0, 0, 8, 5, 0, 0, 6, 0, 6, 3, 5, 6, 5, 9, 4, 6, 4, 3, 3, 5, 5, 6, 4, 5, 15,3, 3, 0, 0, 0, 5, 3, 5, 1, 8, 10,0, 0, 3, 7, 1, 0, 6, 0, 0, 3, 4, 0, 5, 0, 0, 0, 4, 0, 3, 0, 0, 0, 0, 5, 0, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 4, 1, 1, 1, 1, 2, 4, 3, 6, 0, 2, 2, 0, 12,0, 5, 6, 6, 2, 0, 2, 3, 0, 3, 4, 2, 6, 6, 0, 4, 10,7, 0, 5, 5, 6, 6, 7, 3, 3, 0, 0, 8, 4, 4, 10, 9, 4, 0, 0, 0, 0, 4, 0, 2, 0, 4, 4, 3, 8, 0, 7, 0, 0, 2, 3, 4, 0, 0, 0) color <- c(3, 4, 2, 4, 4, 3, 2, 4, 3, 4, 4, 3, 3, 5, 3, 2, 3, 3, 5, 3, 3, 2, 3, 4, 5, 5, 3, 3, 5, 3, 2, 2, 3, 3, 3, 5, 3, 3, 5, 3, 4, 2, 2, 3, 4, 4, 3, 3, 3, 3, 5, 3, 2, 3, 3, 3, 3, 4, 3, 5, 4, 4, 4, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 4, 3, 4, 3, 4, 3, 4, 5, 4, 4, 3, 5, 3, 5, 5, 3, 3, 3, 5, 3, 4, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 4, 3, 3, 3, 3, 3, 3, 4, 3, 3, 5, 5, 4, 3, 4, 4, 2, 4, 3, 3, 3, 4, 5, 3, 3, 2, 3, 3, 5, 3, 3, 3, 4, 3, 3, 3, 3, 4, 3, 3, 5, 3, 3, 4, 3, 3, 3, 3, 3, 5, 3, 3, 3, 4, 4, 3, 3, 3, 5, 3, 3, 4, 4, 4, 4, 2, 5, 3) spine <- c(3, 3, 1, 3, 3, 3, 1, 2, 1, 3, 3, 3, 3, 2, 1, 1, 3, 3, 3, 3, 2, 2, 1, 3, 3, 3, 3, 1, 3, 3, 1, 3, 2, 1, 1, 3, 3, 3, 3, 3, 3, 1, 1, 1, 1, 3, 3, 3, 3, 1, 3, 3, 1, 3, 1, 3, 3, 3, 1, 3, 3, 3, 1, 3, 3, 3, 3, 3, 1, 3, 3, 3, 3, 3, 3, 2, 2, 3, 3, 3, 2, 3, 3, 1, 3, 3, 3, 1, 3, 2, 1, 1, 3, 1, 3, 1, 3, 3, 3, 3, 3, 3, 3, 2, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 3, 3, 3, 2, 3, 3, 3, 1, 2, 3, 1, 3, 3, 3, 1, 3, 2, 3, 1, 3, 3, 1, 3, 3, 1, 3, 3, 3, 3, 3, 1, 1, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 3, 2) weight <- c(3050, 1550, 2300, 2100, 2600, 2100, 2350, 1900, 1950, 2150, 2150, 2650, 3050, 1850, 2300, 2950, 2000, 3000, 2200, 2700, 1950, 2300, 1600, 2600, 2000, 1300, 3150, 2700, 2600, 2100, 3200, 2600, 2000, 2000, 2700, 1850, 2650, 3150, 1900, 2800, 3100, 2800, 2500, 3300, 3250, 2800, 2600, 2100, 3000, 3600, 2100, 2900, 2700, 1600, 2000, 3000, 2700, 2300, 2750, 2250, 2550, 2050, 2450, 2150, 2800, 3050, 3200, 2400, 1300, 2400, 2800, 1650, 1800, 2250, 1900, 1600, 2200, 2250, 1200, 2100, 2250, 2900, 1650, 2550, 2300, 2250, 3050, 2750, 1900, 1700, 3850, 2550, 2450, 3200, 1550, 2800, 2250, 1967, 2200, 3000, 2867, 1600, 2550, 2550, 2000, 2900, 2400, 3100, 1900, 2300, 3250, 2500, 2100, 2100, 3325, 1800, 3225, 1400, 2400, 2500, 1800, 3275, 2225, 1650, 2900, 2300, 3200, 1475, 2025, 2300, 1950, 1800, 2900, 2250, 3050, 2200, 3100, 2400, 2250, 2625, 5200, 3325, 2925, 2000, 2400, 2100, 3725, 3025, 1900, 3000, 2850, 2300, 2000, 1600, 1900, 1950, 3200, 1850, 1800, 3500, 2350, 2275, 3050, 2150, 2750, 2200, 1800, 2175, 2750, 3275, 2625, 2625, 2000) width <- c(28.3,22.5, 26.0, 24.8, 26.0, 23.8, 26.5, 24.7, 23.7, 25.6, 24.3, 25.8, 28.2, 21.0, 26.0, 27.1, 25.2, 29.0, 24.7, 27.4, 23.2, 25.0, 22.5, 26.7, 25.8, 26.2, 28.7, 26.8, 27.5, 24.9, 29.3, 25.8, 25.7, 25.7, 26.7, 23.7, 26.8, 27.5, 23.4, 27.9, 27.5, 26.1, 27.7, 30.0, 28.5, 28.9, 28.2, 25.0, 28.5, 30.3, 24.7, 27.7, 27.4, 22.9, 25.7, 28.3, 27.2, 26.2, 27.8, 25.5, 27.1, 24.5, 27.0, 26.0, 28.0, 30.0, 29.0, 26.2, 26.5, 26.2, 25.6, 23.0, 23.0, 25.4, 24.2, 22.9, 26.0, 25.4, 25.7, 25.1, 24.5, 27.5, 23.1, 25.9, 25.8, 27.0, 28.5, 25.5, 23.5, 24.0, 29.7, 26.8, 26.7, 28.7, 23.1, 29.0, 25.5, 26.5, 24.5, 28.5, 28.2, 24.5, 27.5, 24.7, 25.2, 27.3, 26.3, 29.0, 25.3, 26.5, 27.8, 27.0, 25.7, 25.0, 31.9, 23.7, 29.3, 22.0, 25.0, 27.0, 23.8, 30.2, 26.2, 24.2, 27.4, 25.4, 28.4, 22.5, 26.2, 24.9, 24.5, 25.1, 28.0, 25.8, 27.9, 24.9, 28.4, 27.2, 25.0, 27.5, 33.5, 30.5, 29.0, 24.3, 25.8, 25.0, 31.7, 29.5, 24.0, 30.0, 27.6, 26.2, 23.1, 22.9, 24.5, 24.7, 28.3, 23.9, 23.8, 29.8, 26.5, 26.0, 28.2, 25.7, 26.5, 25.8, 24.1, 26.2, 26.1, 29.0, 28.0, 27.0, 24.5) crabx <- cbind(color,spine,weight,width) rm(color,spine,weight,width) ##Beaton, Martin, Mullis, Gonzales, Smith and Kelly (1996), timss data: ytimss <- c(0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0) #1 if there was a statistically significant gender difference in the nation's 8th grade TIMSS science test m8s <- c(550, 566, 558, 479, 537, 418, 461, 586, 494, 506, 542, 505, 535, 563, 501, 477, 544, 576, 492, 484, 570, 538, 534, 490, 492, 544, 527, 612, 552, 573, 526, 543, 529, 524, 539) #male 8th grade score g8s <- c(540, 549, 543, 463, 525, 405, 465, 562, 463, 490, 524, 489, 507, 545, 486, 461, 532, 551, 478, 470, 550, 512, 520, 468, 480, 533, 507, 603, 537, 548, 508, 528, 514, 526, 530) #female 8th grade score m7s <- c(507, 522, 536, 453, 505, 396, 420, 543, 452, 461, 505, 452, 503, 525, 468, 443, 504, 545, 440, 405, 523, 489, 489, 436, 456, 493, 477, 548, 520, 539, 487, 493, 492, 495, 514) #male 7th grade score g7s <- c(502, 516, 521, 432, 493, 378, 420, 523, 427, 443, 495, 446, 485, 510, 456, 428, 487, 521, 430, 401, 512, 472, 477, 420, 448, 475, 459, 541, 499, 521, 467, 484, 475, 492, 502) #female 7th grade score edaids <- c(66, 56, 64, 58, 57, 10, 37, 33, 66, 49, 66, 28, 33, 32, 72, 1, 67, 38, 13, 35, 83, 56, 63, 35, 8, 30, 74, 47, 27, 43, 40, 58, 63, 4, 56) #percent of students with with educational aids (dictionary, study table, and computer) colgrad <- c(28, 10, 20, 27, 37, 15, 15, 21, 13, 13, 11, 18, 7, 24, 25, 3, 17, 22, 27, 37, 12, 25, 25, 9, 10, 34, 14, 8, 20, 19, 15, 22, 11, 9, 33) #percent of 8th graders who say a parent is a college grad fun<- c(94, 90, 94, 95, 96, 93, 91, 90, 98, 91, 88, 89, 74, 96, 95, 79, 94, 58, 90, 86, 96, 95, 97, 87, 83, 92, 94, 79, 95, 88, 96, 97, 83, 84, 93) #percent of 8th graders whose moms think having fun is important dowell<-c(64, 45, 70, 78, 68, 93, 71, 61, 82, 53, 35, 82, 74, 66, 65, 95, 59, 79, 53, 55, 82, 66, 72, 88, 80, 81, 70, 96, 60, 56, 89, 61, 40, 94, 69) #percent of 8th graders whose friends think it is important to do well in science study <-c(2.0, 2.4, 3.4, 3.0, 2.2, 4.6, 3.6, 1.8, 1.4, 2.7, 2.0, 4.4, 2.5, 3.1, 2.4, 6.4, 2.7, 2.5, 2.7, 2.7, 2.2, 2.1, 2.3, 3.0, 5.0, 2.9, 1.8, 4.6, 2.4, 2.9, 3.6, 2.3, 2.7, 3.5, 2.3) #8th graders ave hours studying outside of school fteach<- c(39, 52, 55, 56, 37, 39, 52, 76, 23, 51, 39, 43, 32, 74, 44, 40, 54, 48, 75, 78, 20, 40, 31, 78, 74, 86, 37, 69, 63, 77, 44, 37, 14, 64, 54) #percent of 8th graders taught by female teachers comp <- c(73, 59, 67, 60, 61, 11, 39, 36, 76, 50, 71, 29, 39, 37, 77, 4, 78, 39, 13, 42, 85, 60, 64, 39, 19, 35, 90, 49, 31, 47, 42, 60, 66, 4, 59) #percent of 8th graders with computer at home rate<-c(75, 43, 61, 57, 90, 91, 100, 96, 88, 87, 70, 87, 83, 99, 97, 100, 82, 100, 83, 96, 23, 90, 84, 94, 94, 97, 79, 100, 91, 81, 96, 96, 90, 99, 77) #participation rate of eligible schools #countries: Australia, Austria, Belgiumfl, Belgiumfr, Canada, Columbia, #Cyprus, Czech, Denmark, France, Germany, Greece, Hong Kong, #Hungary, Iceland, Iran, Ireland, Korea, Latvia, Lithuania, Netherlands, #New Zealand, Norway, Portugal, Romania, Russia, Scotland, Singapore, Slovak, #Slovenia, Spain, Sweden, Switzerland, Thailand, USA xtimss <- cbind(m8s, g8s,m7s,g7s,edaids,colgrad,fun,dowell,study,fteach,comp,rate) rm(m8s,g8s,m7s,g7s,edaids,colgrad,fun,dowell,study,fteach,comp,rate) ## Box and Cox (1964), wool textile data 3^3 design cycles <- c(674, 370, 292, 338, 266, 210, 170, 118, 90, 1414, 1198, 634, 1022, 620, 438, 443, 332, 220, 3636, 3184, 2000, 1568, 1070, 566, 1140, 884, 360) amp <- rep(c(8,8,8,9,9,9,10,10,10),3) length <- rep(c(250,300,350),c(9,9,9)) load <- rep(c(40,45,50),9) wooly <- cycles woolx <- cbind(amp,length,load) amp <- factor(amp) length <- factor(length) load <- factor(load) wool <- data.frame(amp,length,load,cycles) rm(amp,length,load,cycles) ##Buxton (1920) data buxy <- c(1720,1698,1727,1739,1622,1684,1583,1697,1711,1672,1617,1772,1792,1696,1656,1770, 1617,1679,1631,1814,1668,1796,1620,1587,1735,1670,1672,1660,1610,1773,1571,1763,1635,1613, 1690,1770,1771,1640,1770,1740,1683,1696,1730,1722,1637,1716,1790,1694,1742,1712,1637,1645, 1715,1610,1700,1664,1723,1755,1697,1670,18,18,19,19,19,1786,1685,1750,1587,1686,1663,1693, 1750,1598,1710,1590,1790,1758,1835,1720,1684,1631,1758,1661,1790,1704,1590) len <- c(168,176,179,176,177,175,170,177,179,178,171,189,183,190,180,173,180,178,179,178, 188,173, 182,162,187,189,170,176,173,169,172,178,173, 185, 175, 176, 184, 184, 182, 178, 175, 189, 174, 173, 178, 186, 173,168, 172, 185,175,196,181, 177,173,171, 184, 178, 174, 181, 1755, 1537, 1650, 1675, 1610, 175,183, 180, 187, 181, 176, 185, 191, 179, 184, 172,175, 179, 177,167, 179,170, 170, 182, 173, 185, 189) nasal<- c(51, 55, 55, 46, 48, 54, 48, 54, 51, 50, 51, 61, 57, 51, 54, 55, 50, 50, 53, 57, 45, 60, 45, 45, 63, 49, 49, 50, 50, 47, 43, 58, 55, 51, 52, 52, 54, 47, 56, 50, 51, 52, 50, 46, 49, 49, 57, 56, 52, 47, 53, 55, 54, 51, 54, 47, 46, 59, 54, 55, 53, 44, 55, 47, 48, 44, 53, 49, 50, 59, 51,58, 49, 45, 49, 56, 58, 53, 48, 52, 57, 55, 56, 46, 57, 55, 50) bigonal<-c( 104, 106, 104, 114, 101, 102, 116, 110, 97, 107, 108, 114, 115, 108, 103, 108, 109, 110, 97, 108, 105, 102, 105, 92, 108, 110, 118, 112, 103, 112, 105, 109, 114, 106, 108, 110, 104, 106, 108, 108, 112, 110, 109, 103, 99, 110, 92, 117, 107, 106, 103, 108, 111, 108, 93, 100, 103, 100, 110, 106, 102, 124, 90, 107, 104, 111, 112, 97, 115, 112, 102, 101, 105, 103, 113, 105, 105, 103, 105, 107, 114, 103, 105, 108, 92, 107, 110) cephalic <- c( 89.29, 83.52, 83.80, 88.64, 80.79, 88.57, 90.00, 85.88, 83.24, 83.59, 85.96, 83.07, 80.87, 82.63, 87.22, 83.82, 81.67, 83.15, 84.92, 83.71, 77.66, 90.75, 81.32, 86.42, 79.68, 79.37, 86.47, 85.23, 86.71, 91.72, 91.28, 85.39, 89.60, 86.49, 90.86, 86.36, 80.98, 78.80, 82.97, 86.52, 85.71, 76.72, 85.63, 93.06, 85.39, 78.49, 80.35, 90.48, 87.79, 82.70, 79.43, 73.68, 79.01, 80.79, 84.39, 88.89, 83.70, 79.78, 83.33, 75.69, 86.63, 79.01, 76.09, 88.20, 83.63, 86.29, 79.23, 81.11, 79.68, 85.64, 86.36, 79.46, 80.10, 78.21, 84.78, 87.79, 85.14, 87.15, 85.31, 95.21, 85.47, 88.82, 87.06, 84.32, 80.35, 85.41, 74.60) buxx <- cbind(len,nasal,bigonal,cephalic) rm(len,nasal,bigonal,cephalic) ##Collett (1999, pp. 216-299) rotifer data rotmv <- c(58,86,76,83,56,73,29,44,31,56,27,59,22,14,17,22,66,86,492,89, 161,248,234,283,129,161,167,286,117,162,42,48,49,160,74,45,101,68,190, 154) density<- c(1.019,1.020,1.021,1.03,1.03,1.03,1.031,1.04,1.04,1.041, 1.048,1.049,1.05,1.05,1.06,1.061,1.063,1.07,1.07,1.07,1.019,1.020, 1.021,1.03,1.03,1.03,1.031,1.04,1.04,1.041,1.048,1.049,1.05,1.05, 1.06,1.061,1.063,1.07,1.07,1.07) species <- 0*1:40 species[1:20] <- species[1:20]+1 roty<-c(11,7,10,19,9,21,13,34,10,36,20,54,20,9,14,10,64,68,488,88, 13,14,30,10,14,35,26,32,22,23,7,22,9,34,71,25,94,63,178,154) rotx <- cbind(density,species) rm(density,species) ##Cook and Weisberg (1999a, pp. 351, 433, 447), mussels data #L Shell length in mm #W Shell width in mm #H Shell height in mm #S Shell mass in g #M Muscle mass in g L<-c(318, 312, 265, 222, 274, 216, 217, 202, 272, 273, 260, 276, 270, 280, 262, 312, 220, 212, 196, 226, 284, 320, 331, 276, 186, 213, 291, 298, 287, 230, 293, 298, 290, 282, 221, 287, 228, 210, 308, 265, 270, 208, 277, 241, 219, 170, 150, 132, 175, 150, 162, 252, 275, 224, 211, 254, 234, 221, 167, 220, 227, 177, 230, 288, 275, 273, 246, 250, 290, 226, 269, 267, 263, 217, 188, 152, 227, 216, 242, 260, 196, 220) W<-c(68, 56, 46, 38, 51, 35, 34, 32, 44, 49, 48, 47, 50, 52, 50, 61, 34, 32, 28, 38, 61, 60, 60, 46, 30, 35, 47, 54, 55, 40, 57, 48, 47, 52, 37, 54, 46, 33, 58, 48, 44, 33, 45, 39, 38, 27, 21, 20, 30, 22, 25, 47, 48, 36, 33, 46, 37, 37, 27, 36, 35, 25, 47, 46, 54, 42, 37, 43, 48, 35, 45, 48, 48, 36, 33, 25, 38, 25, 45, 44, 35, 36) H<-c(158, 148, 124, 104, 143, 99, 109, 96, 119, 123, 135, 133, 126, 130, 134, 120, 94, 102, 85, 104, 134, 137, 140, 126, 92, 98, 130, 137, 140, 106, 135, 135, 134, 135, 104, 135, 129, 107, 131, 124, 124, 99, 123, 110, 105, 87, 75, 65, 86, 69, 79, 124, 131, 107, 100, 126, 114, 108, 80, 106, 118, 83, 112, 132, 127, 120, 110, 115, 131, 111, 121, 121, 123, 104, 93, 76, 112, 110, 112, 123, 101, 105) S<-c(345, 290, 167, 67, 238, 68, 75, 54, 128, 150, 117, 190, 160, 212, 208, 235, 52, 74, 42, 69, 268, 323, 359, 167, 33, 51, 170, 224, 238, 68, 208, 167, 187, 191, 58, 180, 188, 65, 299, 159, 145, 54, 129, 104, 66, 24, 19, 10, 36, 18, 20, 133, 179, 69, 59, 120, 72, 74, 27, 52, 76, 25, 125, 138, 191, 148, 90, 120, 203, 64, 124, 153, 151, 68, 51, 19, 88, 53, 61, 133, 68, 64) M<-c(47, 52, 27, 13, 31, 14, 15, 4, 23, 32, 30, 26, 24, 31, 31, 42, 9, 13, 7, 13, 50, 39, 47, 40, 5, 12, 26, 32, 40, 16, 33, 28, 28, 42, 15, 27, 33, 14, 29, 26, 25, 9, 18, 23, 13, 6, 6, 1, 8, 5, 6, 22, 24, 13, 11, 18, 17, 15, 7, 14, 14, 8, 18, 24, 29, 21, 17, 17, 34, 16, 22, 24, 19, 13, 10, 5, 15, 12, 12, 24, 15, 16) mussels <- cbind(L,W,H,S,M) rm(L,W,H,S,M) #Cook and Weisberg (1999a, pp. 285-286) species data #Y = number of species, endem = number of endemic species #area = area of island, elev = elevation of island #distnear = distance of nearest island, distsc = distance to Santa Cruz #areanear = area of nearest island Y <- c(58, 31, 3, 25, 2, 18, 10, 8, 2, 97, 93, 58, 5, 40, 347, 51, 2, 104, 108, 12, 70, 280, 237, 444, 62, 285, 44, 16, 21) endem <- c(23, 21, 3, 9, 1, 11, 7, 4, 2, 26, 35, 17, 4, 19, 89, 23, 2, 37, 33, 9, 30, 65, 81, 95, 28, 73, 16, 8, 12) area <- c(25.09, 1.24, 0.21, 0.10, 0.05, 0.34, 2.33, 0.03, 0.18, 58.27, 634.49, 0.57, 0.78, 17.35, 4669.32, 129.49, 0.01, 59.56, 17.95, 0.23, 4.89, 551.62, 572.33, 903.82, 24.08, 170.92, 1.84, 1.24, 2.85) elev <- c(NA, 109, 114, 46, NA, NA, 168, NA, 112, 198, 1494, 49, 227, 76, 1707, 343, 25, 777, 458, NA, 367, 716, 906, 864, 259, 640, NA, 186, 253) distnear <- c(0.6, 0.6, 2.8, 1.9, 1.9, 8.0, 34.1, 0.4, 2.6, 1.1, 4.3, 1.1, 4.6, 47.4, 0.7, 29.1, 3.3, 29.1, 10.7, 0.5, 4.4, 45.2, 0.2, 0.6, 16.5, 2.6, 0.6, 6.8, 34.1) distsc <- c(0.6, 26.3, 58.7, 47.4, 1.9, 8.0, 290.2, 0.4, 50.2, 88.3, 95.3, 93.1, 62.2, 92.2, 28.1, 85.9, 45.9, 119.6, 10.7, 0.6, 24.4, 66.5, 19.8, 0.0, 16.5, 49.2, 9.6, 50.9, 254.7) areanear <- c(1.84, 572.33, 0.78, 0.18, 903.82, 1.84, 2.85, 17.95, 0.10, 0.57, 4669.32, 58.27, 0.21, 129.49, 634.49, 59.56, 0.10, 129.49, 0.03, 25.09, 572.33, 0.57, 4.89, 0.52, 0.52, 0.10, 25.09, 17.95, 2.33) species <- cbind(Y,endem,area,elev,distnear,distsc, areanear) rm(Y,endem,area,elev,distnear,distsc, areanear) ##Gladstone (1905) brain data cbrainy<-c( 1297, 1335, 1282, 1590, 1300, 1400, 1255, 1355, 1375, 1340, 1380, 1355, 1522, 1208, 1405, 1358,1292, 1340, 1400, 1357, 1287, 1275, 1270, 1505, 1490, 1485, 1310, 1420, 1318, 1432, 1364, 1405, 1432, 1207, 1375, 1350, 1236, 1250, 1350, 1320, 1525, 1570, 1340, 1422, 1506, 1215, 1311, 1300, 1224, 1350, 1335, 1390, 1400, 1225, 1310, 1560, 1330, 1222, 1415, 1175, 1330, 1485, 1470, 1135, 1310, 1154, 1510, 1415, 1468, 1390, 1380, 1432, 1240, 1225, 1188, 1252, 1315, 1245, 1430, 1279, 1245, 1309, 1412, 1120, 1220, 1440, 1370, 1192, 1230, 1346, 1290, 1165, 1240, 1132, 1242, 1270, 1218, 1430, 1586, 1320, 1290, 1260, 1425, 1226, 1360, 1620, 1310, 1250, 1295, 1290, 1290, 1275, 1250, 1270, 1362, 1300, 1173, 1256, 1440, 1180, 1306, 1350, 1125, 1165, 1312, 1300, 1270, 1335, 1450, 1310, 1235, 1260, 1165, 1080, 1127, 1252, 1200, 1290, 1334, 1380, 1140, 1243, 1340, 1168, 1322, 1249, 1321, 1192, 1373, 1170, 1265, 1235, 1302, 1241, 1078, 1520, 1460, 1075, 1280, 1180, 1250, 1190, 1374, 1306, 1202, 1240, 1316, 1280, 1350, 1180, 1210, 1127, 1324, 1210, 1290, 1100, 1280, 1175, 1160, 1205, 1163, 1243, 1350, 1237, 1204, 1090, 1355, 1250, 1076, 1120, 1220, 1240, 1220, 1095, 1235, 1105, 1405, 1150, 1305, 1220, 1296, 1175, 955, 1070, 1320, 1060, 1130, 1250, 1225, 1180, 1178, 1142, 1130, 1185, 1012, 1280, 1103, 1408, 1300, 1246, 1350, 1060, 1350, 1220, 1110, 1215, 1104, 1170, 1120, 450, 1052, 1015, 1120, 1240, 1310, 1095, 1080, 1202, 1200, 1375, 1450, 1417, 1412, 1379, 1322, 1454, 1618, 1095, 1230, 1460, 1278, 1412, 1450, 385, 490, 512, 503, 960, 995, 1100, 1120, 1205, 1205, 1180, 1147, 1419, 1245) age <-c(39.00, 35.00, 35.00, 37.00, 34.00, 38.00, 45.00, 45.00, 40.00, 21.00, 42.00, 25.00, 23.00, 45.00, 41.00, 28.00, 45.00, 20.00, 43.00, 43.00, 25.00, 29.00, 40.00, 40.00, 29.00, 35.00, 27.00, 20.00, 38.00,24.00, 41.00, 45.00, 41.00, 37.00, 29.00, 36.00, 21.00, 38.00, 42.00, 43.00, 37.00, 31.00, 34.00, 44.00, 24.00, 28.00, 44.00, 43.00, 44.00, 38.00, 35.00, 39.00, 36.00, 43.00, 42.00, 50.00, 47.00, 47.00, 49.00, 50.00,48.00, 47.00, 50.00, 48.00, 47.00, 50.00, 48.00, 49.00, 48.00, 49.00, 48.00, 50.00, 69.00, 58.00, 57.00, 67.00, 61.00, 53.00, 60.00, 58.00, 55.00, 57.00, 75.00, 63.00, 69.00, 52.00, 66.00, 67.00, 67.00, 53.00, 55.00, 56.00, 54.00, 59.00, 65.00, 59.00, 60.00, 60.00, 60.00, 62.00, 70.00, 59.00, 51.00, 57.00, 51.00, 65.00, 56.00, 75.00, 47.00, 57.00, 62.00, 84.00, 48.00, 58.00, 63.00, 52.00, 57.00, 52.00, 58.00, 63.00, 57.00, 46.00, 61.00, 58.00, 55.00, 50.00, 52.00, 51.00, 63.00, 72.00, 20.00, 35.00, 40.00, 30.00, 33.00, 42.00, 35.00, 31.00, 35.00, 23.00, 38.00, 23.00, 32.00, 34.00, 37.00, 39.00, 34.00, 41.00, 43.00, 33.00, 28.00, 33.00, 34.00, 38.00, 45.00, 25.00, 39.00, 36.00, 36.00, 40.00, 22.00, 40.00, 40.00, 40.00, 30.00, 42.00, 34.00, 42.00, 39.00, 39.00, 24.00, 44.00, 24.00, 30.00, 37.00, 33.00, 38.00, 26.00, 25.00, 35.00, 21.00, 50.00, 46.00, 50.00, 46.00, 49.00, 49.00, 48.00, 47.00, 53.00, 56.00, 64.00, 69.00, 60.00, 55.00, 55.00, 53.00, 60.00, 54.00, 60.00, 62.00, 53.00, 68.00, 63.00, 51.00, 78.00, 57.00, 68.00, 58.00, 59.00, 49.00, 56.00, 58.00, 62.00, 67.00, 47.00, 64.00, 47.00, 74.00, 67.00, 63.00, 74.00, 49.00, 46.00, 46.00, 50.00, 63.00, 56.00, 63.00, 0.21, 1.70, 2.50, 2.50, 2.70, 3.00, 3.50, 3.80, 4.00, 5.00, 7.00, 8.00, 10.00, 11.00, 12.00, 12.00, 12.50, 15.00, 17.00, 18.00, 19.00, 19.00, 19.00, 19.00, 0.06, 0.21, 0.42, 0.50, 0.67, 2.50, 3.50, 7.00, 7.00, 15.00, 17.00, 18.00, 18.00, 19.00) ageclass<-c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0) breadth <-c( 149.5, 152.5, 145.5, 153.0, 146.0, 143.0, 140.0, 147.0, 150.5, 141.0, 148.5, 142.0, 154.0, 152.0, 148.0, 147.0, 144.5, 138.0, 160.0, 149.0, 158.0, 146.0, 151.0, 168.0, 151.0, 151.0, 139.0, 147.0, 153.0, 148.0, 159.0, 159.0, 153.0, 149.0, 142.0, 153.0, 142.0, 141.0, 152.0, 143.0, 155.0, 154.0, 153.0, 156.0, 158.0, 141.0, 143.0, 144.0, 154.5, 148.5, 161.0, 162.0, 154.0, 152.0, 152.0, 155.0, 149.0, 144.0, 153.0, 145.0, 159.0, 155.0, 148.0, 146.5, 141.0, 147.0, 154.0, 160.0, 151.5, 152.0, 160.0, 158.0, 148.0, 148.0, 140.0, 153.0, 150.0, 150.0, 146.0, 141.0, 146.0, 152.0, 150.0, 141.0, 141.0, 151.0, 151.0, 144.0, 145.0, 149.0, 143.0, 148.0, 144.0, 141.0, 156.0, 143.0, 148.0, 153.0, 148.0, 150.0, 148.0, 151.0, 143.5, 143.0, 152.0, 157.0, 150.0, 145.5, 150.0, 149.0, 149.5, 145.0, 147.0, 154.0, 152.0, 155.0, 147.0, 164.0, 158.0, 149.0, 157.0, 144.0, 144.0, 145.0, 154.0, 151.0, 145.0, 146.0, 156.0, 151.0, 139.5, 153.0, 144.0, 138.0, 143.0, 143.0, 140.0, 145.0, 158.0, 156.0, 142.5, 141.0, 141.0, 137.0, 139.0, 141.0, 144.0, 147.0, 151.5, 137.0, 142.0, 151.0, 152.0, 141.0, 138.0, 153.5, 145.0, 140.0, 147.0, 143.0, 144.0, 146.0, 151.0, 150.0, 141.0, 145.0, 145.0, 151.0, 151.0, 143.0, 147.0, 147.0, 154.0, 141.0, 144.0, 147.0, 154.0, 142.0, 145.0, 148.0, 148.0, 137.5, 144.0, 141.0, 141.0, 141.0, 151.0, 149.0, 130.0, 140.0, 136.5, 145.0, 142.0, 142.0, 139.0, 146.0, 154.0, 136.0, 157.5, 144.0, 153.0, 144.0, 131.0, 135.0, 146.0, 138.0, 135.0, 149.0, 143.0, 142.0, 139.0, 144.0, 140.0, 143.0, 132.0, 152.0, 147.0, 145.0, 152.0, 142.0, 152.0, 143.0, 145.0, 140.0, 146.0, 150.0, 143.0, 144.0, 148.0, 95.0, 125.0, 131.0, 135.5, 139.0, 137.0, 129.5, 135.0, 134.0, 132.0, 140.0, 140.0, 149.5, 145.0, 141.0, 142.0, 143.0, 151.0, 150.5, 142.0, 146.0, 157.0, 147.5, 149.0, 88.5, 99.0, 95.0, 104.5, 126.0, 132.0, 126.0, 131.0, 133.0, 139.0, 143.5, 135.0, 151.0, 141.0) cause <- c(1, 3, 3, 1, 2, 3, 3, 2, 2, 3, 2, 2, 1, 2, 1, 1, 3, 1, 3, 3, 2, 3, 3, 1, 2, 2, 2, 1, 3, 2, 2, 3, 3, 2, 2, 1, 3, 3, 3, 3, 3, 1, 3, 3, 3, 3, 3, 1, 3, 1, 3, 1, 1, 3, 3, 2, 3, 2, 3, 1, 3, 2, 1, 1, 2, 2, 3, 2, 3, 2, 2, 1, 3, 1, 2, 3, 1, 2, 1, 3, 3, 1, 2, 2, 2, 3, 3, 3, 2, 1, 3, 1, 3, 3, 1, 3, 3, 1, 3, 3, 1, 1, 1, 3, 3, 1, 3, 3, 3, 3, 3, 3, 3, 3, 1, 3, 1, 1, 2, 3, 1, 1, 3, 2, 2, 3, 3, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 1, 1, 2, 2, 3, 3, 2, 2, 2, 3, 3, 3, 3, 1, 3, 3, 1, 2, 3, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 1, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 3, 2, 3, 3, 2, 3, 3, 3, 3, 3, 3, 3, 2, 3, 3, 1, 3, 3, 1, 3, 3, 3, 3, 3, 3, 3, 3, 2, 2, 2, 2, 1, 3, 3, 2, 2, 3, 2, 2, 3, 1, 3, 2, 3, 3, 3, 3, 1, 1, 2, 2, 3, 3, 3, 3, 3, 1, 2, 3, 3, 3, 3, 3, 2) cephalic<-c(81.9, 75.9, 75.4, 78.5, 78.5, 74.2, 74.1, 79.2, 76.7, 76.2, 75.4, 75.3, 77.8, 79.6, 76.3, 80.3, 78.3, 77.5, 83.3, 78.4, 80.2, 77.0, 83.0, 86.2, 76.3, 78.2, 75.5, 73.5, 84.1, 77.9, 85.0, 83.2, 78.3, 78.0, 77.2, 81.8, 78.0, 73.4, 78.1, 75.3, 77.1, 81.1, 79.7, 80.8, 82.3, 77.9, 75.3, 75.4, 80.1, 76.7, 82.6, 85.3, 79.8, 83.5, 79.6, 80.7, 78.4, 74.6, 80.5, 80.6, 79.1, 77.1, 75.9, 80.3, 76.8, 78.2, 75.5, 81.2, 79.3, 80.9, 85.1, 80.6, 77.9, 80.7, 76.1, 81.6, 79.8, 81.1, 76.8, 78.3, 78.1, 77.6, 77.7, 75.4, 75.0, 77.0, 77.8, 80.0, 79.2, 78.0, 73.0, 77.1, 77.6, 77.5, 85.2, 75.3, 80.2, 79.7, 76.3, 80.2, 77.5, 79.0, 71.7, 77.3, 78.8, 77.3, 79.2, 75.3, 78.1, 79.7, 81.2, 76.3, 77.4, 81.5, 76.4, 81.2, 80.3, 85.4, 74.5, 79.3, 80.9, 73.5, 78.3, 84.4, 82.8, 79.9, 74.0, 77.2, 78.8, 82.1, 75.6, 81.8, 79.1, 77.3, 79.0, 76.5, 77.8, 80.1, 81.9, 88.6, 77.0, 77.9, 76.6, 76.5, 74.7, 77.5, 75.8, 80.1, 81.0, 76.1, 79.3, 81.2, 79.6, 79.7, 77.5, 84.8, 78.8, 78.0, 80.3, 81.9, 80.4, 79.3, 78.2, 81.1, 79.7, 77.1, 77.1, 79.9, 79.5, 81.7, 79.0, 78.0, 81.1, 75.4, 77.0, 82.1, 78.2, 81.1, 78.0, 77.9, 77.5, 73.5, 77.8, 77.9, 77.0, 81.5, 81.6, 80.5, 73.4, 83.3, 73.0, 79.7, 76.8, 78.0, 77.2, 83.9, 81.9, 76.0, 87.0, 80.4, 79.7, 80.0, 75.7, 78.5, 79.8, 78.4, 75.0, 79.3, 80.3, 78.9, 76.8, 77.4, 76.9, 77.7, 75.4, 82.2, 81.7, 75.5, 79.6, 76.8, 80.4, 76.9, 78.2, 71.4, 83.9, 82.9, 80.3, 78.3, 82.7, 76.0, 74.4, 81.9, 78.8, 85.8, 75.7, 76.2, 77.6, 77.5, 77.7, 80.0, 72.9, 79.9, 80.1, 77.1, 77.6, 77.7, 79.2, 79.6, 82.6, 78.1, 82.2, 78.2, 78.8, 77.6, 76.4, 73.6, 78.8, 87.5, 76.7, 76.8, 77.5, 76.4, 75.1, 80.6, 75.4, 81.2, 78.8) circum <- c( 550.0, 569.0, 542.0, 576.0, 547.0, 549.0, 535.0, 555.0, 565.0, 537.0, 570.0, 558.0, 576.0, 561.0, 569.0, 551.0, 541.0, 517.0, 580.0, 568.0, 582.0, 554.0, 541.0, 577.0, 564.0, 570.0, 537.0, 574.0, 567.0, 564.0, 574.0, 584.0, 574.0, 548.0, 530.0, 560.0, 528.0, 540.0, 558.0, 539.0, 587.0, 550.0, 563.0, 578.0, 569.0, 510.0, 545.0, 555.0, 570.0, 560.0, 558.0, 557.0, 569.0, 538.0, 549.0, 560.0, 544.0, 556.0, 553.0, 530.0, 585.0, 585.0, 568.0, 541.0, 548.0, 550.0, 583.0, 589.0, 564.0, 563.0, 576.0, 575.0, 560.0, 540.0, 544.0, 569.0, 552.0, 545.0, 564.0, 532.0, 572.0, 569.0, 553.0, 534.0, 540.0, 552.0, 570.0, 531.0, 524.0, 568.0, 551.0, 558.0, 530.0, 528.0, 544.0, 536.0, 525.0, 579.0, 555.0, 548.0, 565.0, 558.0, 565.0, 542.0, 556.0, 585.0, 549.0, 555.0, 561.0, 555.0, 536.0, 545.0, 549.0, 557.0, 588.0, 558.0, 544.0, 563.0, 585.0, 551.0, 573.0, 556.0, 531.0, 534.0, 558.0, 547.0, 556.0, 553.0, 583.0, 554.0, 523.0, 558.0, 532.0, 498.5, 531.0, 552.0, 521.0, 539.0, 554.0, 555.0, 542.0, 540.0, 532.0, 505.0, 532.0, 521.0, 552.0, 533.0, 565.0, 530.0, 528.0, 560.0, 546.0, 523.0, 514.0, 550.0, 535.0, 519.0, 535.0, 513.0, 513.0, 528.0, 548.0, 535.0, 502.0, 539.0, 540.0, 543.0, 555.0, 515.0, 560.0, 541.0, 552.0, 540.0, 530.0, 490.0, 578.0, 545.0, 542.0, 547.0, 541.0, 528.0, 532.0, 522.0, 522.0, 514.0, 545.0, 530.0, 516.0, 515.0, 531.0, 540.0, 525.0, 515.0, 518.0, 506.0, 577.0, 518.0, 548.0, 523.0, 561.0, 523.0, 502.0, 520.0, 532.0, 509.0, 525.0, 540.0, 515.0, 524.0, 512.0, 541.0, 520.0, 528.0, 509.0, 547.0, 532.0, 565.0, 564.0, 528.0, 548.0, 542.0, 535.0, 521.0, 532.0, 542.0, 522.0, 533.0, 537.0, 361.0, 481.0, 474.0, 486.0, 483.0, 514.0, 476.0, 501.0, 501.0, 490.0, 504.0, 530.0, 539.0, 532.0, 540.0, 528.0, 530.0, 547.0, 536.0, 520.0, 556.0, 558.0, 540.0, 547.0, 324.0, 369.0, 368.0, 385.0, 437.0, 496.0, 475.0, 493.0, 485.0, 518.0, 524.0, 507.0, 554.0, 512.0) headht<-c(137.0, 139.0, 134.5, 140.0, 132.0, 137.5, 134.5, 132.5, 135.0, 132.0, 136.5, 136.0, 138.0, 132.0, 135.0, 130.0, 130.0, 126.0, 144.0, 137.0, 130.0, 137.5, 135.0, 135.0, 135.0, 138.0, 135.0, 142.0, 136.0, 135.0, 138.0, 137.0, 139.0, 134.0, 135.0, 131.0, 129.0, 129.0, 134.0, 129.0, 138.5, 130.0, 131.5, 134.0, 142.0, 124.0, 134.0, 132.5, 130.5, 132.0, 136.0, 132.0, 135.0, 125.0, 134.0, 140.0, 139.0, 132.0, 133.0, 130.0, 139.0, 136.5, 129.5, 124.5, 132.0, 122.0, 141.0, 139.0, 138.5, 135.0, 137.0, 131.0, 136.0, 131.0, 130.5, 137.0, 136.0, 138.0, 139.0, 128.0, 131.0, 132.0, 133.0, 125.5, 128.5, 132.0, 142.0, 128.0, 138.0, 137.0, 132.0, 133.0, 130.0, 136.0, 128.0, 128.0, 128.0, 130.5, 135.0, 130.5, 128.0, 126.5, 140.5, 128.5, 133.5, 139.0, 130.0, 125.5, 124.0, 129.0, 123.0, 127.0, 128.5, 134.0, 136.0, 133.0, 126.0, 132.0, 134.0, 129.0, 133.0, 134.0, 128.0, 126.0, 141.5, 125.5, 129.0, 128.0, 131.0, 132.0, 133.5, 132.5, 126.0, 126.0, 122.5, 132.0, 126.0, 131.0, 128.0, 142.0, 129.0, 128.0, 133.0, 126.0, 132.0, 129.5, 134.5, 127.5, 136.0, 128.0, 129.0, 132.0, 138.0, 131.0, 125.0, 136.0, 133.0, 131.0, 130.0, 123.5, 126.0, 125.0, 130.5, 128.5, 126.0, 128.5, 131.0, 130.5, 126.0, 128.0, 132.0, 128.5, 136.0, 134.0, 137.0, 120.0, 132.0, 128.0, 129.0, 129.5, 128.5, 132.0, 139.0, 124.0, 130.0, 123.0, 132.0, 129.0, 120.5, 130.0, 131.0, 132.0, 125.5, 130.0, 129.0, 129.0, 133.0, 126.0, 129.5, 132.0, 136.0, 128.0, 120.0, 126.5, 134.0, 121.0, 123.0, 128.0, 124.0, 127.0, 126.0, 122.0, 133.0, 128.5, 124.0, 133.0, 131.5, 131.0, 128.0, 125.0, 130.0, 121.0, 137.0, 135.0, 126.5, 125.0, 127.0, 126.5, 128.0, 89.5, 119.0, 111.0, 121.0, 116.0, 124.4, 121.0, 127.0, 127.0, 125.0, 127.0, 131.5, 137.5, 130.0, 136.0, 122.5, 134.0, 141.0, 129.0, 131.0, 143.0, 135.0, 133.0, 138.0, 92.5, 94.5, 88.5, 100.0, 118.0, 124.0, 114.0, 121.0, 118.0, 128.0, 125.5, 125.0, 139.0, 131.0) height<-c(68.00, 71.00, 70.00, 68.00, 65.00, 68.00, 69.50, 68.00, 64.00, 66.00, 63.00, 69.75, 66.50, 71.00, 60.50, 63.50, 65.00, 71.50, 68.00, 68.50, 68.50, 68.50, 68.50, 72.50, 69.25, 70.50, 69.50, 69.00, 68.50, 69.75, 70.50, 71.00, 67.00, 61.00, 65.00, 61.50, 61.00, 62.50, 61.50, 62.50, 66.00, 67.50, 69.00, 69.00, 69.50, 68.50, 67.00, 66.50, 68.50, 68.50, 70.00, 69.00, 69.00, 66.00, 60.50, 68.00, 69.00, 67.00, 64.50, 69.00, 69.50, 69.00, 72.25, 64.50, 67.00, 68.00, 68.00, 68.50, 69.50, 69.00, 66.00, 69.50, 69.50, 67.00, 69.00, 68.50, 66.00, 69.00, 68.50, 70.00, 67.50, 67.00, 67.50, 61.00, 67.25, 63.25, 71.50, 69.50, 67.00, 63.00, 63.00, 65.00, 65.00, 63.00, 65.50, 64.00, 65.50, 69.00, 68.00, 65.00, 67.00, 67.50, 68.00, 66.00, 68.50, 70.50, 66.00, 72.50, 69.50, 67.25, 69.75, 50.50, 61.50, 68.50, 67.50, 67.00, 66.00, 69.00, 72.00, 65.00, 67.50, 69.00, 64.00, 66.00, 65.00, 66.00, 66.00, 67.00, 69.00, 66.50, 63.00, 63.50, 60.00, 51.00, 58.00, 62.00, 66.00, 66.00, 64.00, 69.00, 65.50, 67.50, 70.00, 58.00, 60.00, 64.00, 63.00, 66.50, 66.50, 59.00, 64.00, 67.00, 66.00, 65.50, 68.00, 67.00, 62.00, 61.00, 62.50, 60.00, 58.50, 63.50, 61.50, 65.00, 63.00, 64.50, 63.50, 62.50, 63.50, 62.50, 64.00, 64.50, 64.50, 63.50, 63.75, 55.00, 67.00, 64.50, 61.50, 63.00, 66.50, 60.00, 66.00, 63.00, 67.50, 60.50, 65.50, 64.00, 66.50, 64.00, 60.00, 61.50, 62.50, 61.00, 61.50, 59.00, 61.00, 60.50, 60.50, 64.50, 62.50, 61.00, 61.00, 62.50, 66.00, 58.50, 61.00, 64.00, 60.50, 65.00, 57.00, 60.00, 59.00, 62.50, 63.00, 64.00, 59.00, 65.00, 63.00, 62.00, 63.00, 62.00, 65.50, 67.00, 62.50, 64.50, 58.50, 64.50, 62.00, 22.00, 37.50, 31.75, 33.00, 38.00, 37.00, 35.50, 34.00, 39.00, 37.50, 46.00, 43.00, 52.00, 55.00, 65.00, 48.50, 56.50, 62.50, 67.00, 71.00, 67.00, 67.50, 65.50, 69.50, 21.50, 22.00, 22.50, 24.50, 25.00, 33.50, 38.50, 47.00, 48.00, 61.50, 61.00, 53.50, 66.00, 65.00) len <-c( 182.5, 201.0, 193.0, 195.0, 186.0, 192.5, 189.0, 185.5, 196.0, 185.0, 197.0, 188.5, 198.0, 191.0, 194.0, 183.0, 184.5, 178.0, 192.0, 190.0, 197.0, 189.5, 182.0, 195.0, 198.0, 193.0, 184.0, 200.0, 182.0, 190.0, 187.0, 191.0, 195.5, 191.0, 184.0, 187.0, 182.0, 192.0, 194.5, 190.0, 201.0, 190.0, 192.0, 193.0, 192.0, 181.0, 190.0, 191.0, 193.0, 193.5, 195.0, 190.0, 193.0, 182.0, 191.0, 192.0, 190.0, 193.0, 190.0, 180.0, 201.0, 201.0, 195.0, 182.5, 183.5, 188.0, 204.0, 197.0, 191.0, 188.0, 188.0, 196.0, 190.0, 183.5, 184.0, 187.5, 188.0, 185.0, 190.0, 180.0, 187.0, 196.0, 193.0, 187.0, 188.0, 196.0, 194.0, 180.0, 183.0, 191.0, 196.0, 192.0, 185.5, 182.0, 183.0, 190.0, 184.5, 192.0, 194.0, 187.0, 191.0, 191.0, 200.0, 185.0, 193.0, 203.0, 189.5, 193.0, 192.0, 187.0, 184.0, 190.0, 190.0, 189.0, 199.0, 191.0, 183.0, 192.0, 212.0, 188.0, 194.0, 196.0, 184.0, 171.0, 186.0, 189.0, 196.0, 189.0, 198.0, 184.0, 184.5, 187.0, 182.0, 178.5, 181.0, 187.0, 180.0, 181.0, 193.0, 176.0, 185.0, 181.0, 184.0, 179.0, 186.0, 182.0, 190.0, 183.5, 187.0, 180.0, 179.0, 186.0, 191.0, 177.0, 178.0, 181.0, 184.0, 179.5, 183.0, 174.5, 179.0, 184.0, 193.0, 185.0, 177.0, 188.0, 188.0, 189.0, 190.0, 175.0, 186.0, 188.5, 190.0, 187.0, 187.0, 179.0, 197.0, 175.0, 186.0, 190.0, 191.0, 187.0, 185.0, 181.0, 183.0, 173.0, 185.0, 185.0, 177.0, 168.0, 187.0, 182.5, 185.0, 182.0, 180.0, 174.0, 188.0, 179.0, 181.0, 179.0, 192.0, 180.0, 173.0, 172.0, 183.0, 176.0, 180.0, 188.0, 178.0, 180.0, 181.0, 186.0, 182.0, 184.0, 175.0, 185.0, 180.0, 192.0, 191.0, 185.0, 189.0, 186.0, 185.5, 196.0, 174.0, 181.0, 178.0, 184.0, 179.0, 125.0, 168.0, 160.0, 172.0, 162.0, 181.0, 170.0, 174.0, 173.0, 170.0, 175.0, 192.0, 187.0, 181.0, 183.0, 183.0, 184.0, 190.5, 189.0, 172.0, 187.0, 191.0, 188.5, 189.0, 114.0, 129.5, 129.0, 132.5, 144.0, 172.0, 164.0, 169.0, 174.0, 185.0, 178.0, 179.0, 186.0, 179.0) sex<-c(1,1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0) size <- c(3738, 4261, 3777, 4177, 3585, 3785, 3559, 3613, 3982, 3443, 3993, 3640, 4208, 3832, 3876, 3497, 3466, 3095, 4424, 3878, 4046, 3804, 3710, 4423, 4036, 4022, 3454, 4175, 3787, 3796, 4103, 4161, 4158, 3814, 3527, 3748, 3334, 3492, 3962, 3505, 4315, 3804, 3863, 4034, 4308, 3165, 3641, 3644, 3891, 3793, 4270, 4063, 4012, 3458, 3890, 4166, 3935, 3669, 3866, 3393, 4442, 4253, 3737, 3329, 3415, 3372, 4430, 4381, 4008, 3858, 4121, 4057, 3824, 3558, 3362, 3930, 3835, 3830, 3856, 3249, 3577, 3933, 3850, 3309, 3406, 3907, 4160, 3318, 3662, 3899, 3700, 3779, 3473, 3490, 3654, 3478, 3495, 3834, 3876, 3661, 3618, 3648, 4032, 3399, 3916, 4430, 3695, 3524, 3571, 3594, 3383, 3499, 3589, 3900, 4114, 3937, 3399, 4200, 4488, 3614, 4051, 3782, 3391, 3124, 4053, 3582, 3666, 3532, 4046, 3667, 3436, 3791, 3302, 3104, 3171, 3530, 3175, 3438, 3903, 3899, 3401, 3267, 3451, 3090, 3413, 3323, 3680, 3439, 3853, 3156, 3279, 3707, 4006, 3269, 3071, 3779, 3548, 3292, 3497, 3082, 3248, 3358, 3803, 3566, 3145, 3503, 3571, 3724, 3615, 3203, 3609, 3561, 3979, 3533, 3689, 3158, 4005, 3181, 3479, 3642, 3632, 3394, 3703, 3165, 3354, 3000, 3687, 3556, 2773, 3058, 3344, 3493, 3297, 3360, 3228, 3277, 3851, 3067, 3692, 3402, 3995, 3318, 2720, 2937, 3580, 2939, 2989, 3586, 3156, 3246, 3170, 3268, 3389, 3381, 2864, 3740, 3479, 3647, 3716, 3284, 3735, 3218, 3685, 3704, 3214, 3394, 3233, 3352, 3391, 1063, 2499, 2327, 2820, 2612, 3087, 2664, 2983, 2944, 2805, 3112, 3535, 3844, 3412, 3509, 3183, 3526, 4056, 3669, 3200, 3904, 4048, 3698, 3886, 933, 1212, 1085, 1385, 2141, 2815, 2356, 2679, 2731, 3292, 3206, 3021, 3904,3306) cbrainx <- cbind(age,ageclass,breadth,cause,cephalic,circum,headht,height,len,sex,size) rm(age,ageclass,breadth,cause,cephalic,circum,headht,height,len,sex,size) #Glado data is Gladstone cbrain data where head length for case 119 in the paper was 109 #instead of 199 the case is 115 in the data set since 4 cases were deleted gladoy <- cbrainy gladox <- cbrainx gladox[115,9] <- 109 rm(age,ageclass,breadth,cause,cephalic,circum,headht,height,len,sex,size) ##Hebbler, B. (1847), marry data``Statistics of Prussia," # mmen = number of married men #mmilmen = number of married military men #milwmn = number of women married to military men #mwmn = number of married women pop <-c(821946, 619553, 387306, 577575, 857230, 432957, 353149, 782186, 799772, 517522, 413106, 175722, 1117204, 939624, 892056, 647326, 701037, 335543, 418765, 452877, 549801, 465363, 851456, 489900, 478338, 394451) mmen <- c(133217, 104159, 61670, 97363, 142600, 71710, 43455, 130111, 139617, 85671, 67357, 28389, 189939, 158427, 162699, 109785, 117142, 55557, 65510, 74236, 86664, 69870, 134882, 77345, 74970, 60449) mwmn <- c( 133217, 104245, 61688, 97456, 142538, 71374, 43639, 130663, 140088, 85892, 67681, 28623, 190063, 158456, 163279, 110621, 118078, 56305, 65989, 74698, 87629, 70040, 136012, 77755, 74970, 60534) mmilmen<- c(1129, 290, 651, 752, 931, 192, 1524, 1822, 1066, 1202, 649, 269, 1522, 1076, 1018, 941, 879, 610, 229, 410, 156, 464, 519, 781, 678, 159) milwmn <- c( 1061, 290, 612, 711, 925, 189, 1476, 1750, 955, 1089, 617, 253, 1455, 1046, 1019, 929, 792, 585, 226, 381, 156, 413, 493, 716, 591, 128) marry <- cbind(pop,mmen,mwmn,mmilmen,milwmn) rm(pop,mmen,mwmn,mmilmen,milwmn) ##Johnson (1996) x1=density, y=bfat=x2, x3=age, x4=weight, x5=height, x6=neck, x7=chest, #x8=abdomen, x9=hip, x10=thigh, x11 = knee, x12=ankle, x13=biceps, x14=forarm, x15=wrist # Density determined from underwater weighing #Percent body fat from Siri's (1956) equation #Age (years) #Weight (lbs) #Height (inches) #Neck circumference (cm) #Chest circumference (cm) #Abdomen circumference (cm) #Hip circumference (cm) #Thigh circumference (cm) #Knee circumference (cm) #Ankle circumference (cm) #Biceps (extended) circumference (cm) #Forearm circumference (cm) #Wrist circumference (cm) density<-c(1.0708, 1.0853, 1.0414, 1.0751, 1.0340, 1.0502, 1.0549, 1.0704, 1.0900, 1.0722, 1.0830, 1.0812, 1.0513, 1.0505, 1.0484, 1.0512, 1.0333, 1.0468, 1.0622, 1.0610, 1.0551, 1.0640, 1.0631, 1.0584, 1.0668, 1.0911, 1.0811, 1.0468, 1.0910, 1.0790, 1.0716, 1.0862, 1.0719, 1.0502, 1.0263, 1.0101, 1.0438, 1.0346, 1.0202, 1.0258, 1.0217, 1.0250, 1.0279, 1.0269, 1.0814, 1.0670, 1.0742, 1.0665, 1.0678, 1.0903, 1.0756, 1.0840, 1.0807, 1.0848, 1.0906, 1.0473, 1.0524, 1.0356, 1.0280, 1.0430, 1.0396, 1.0317, 1.0298, 1.0403, 1.0264, 1.0313, 1.0499, 1.0673, 1.0847, 1.0693, 1.0439, 1.0788, 1.0796, 1.0680, 1.0720, 1.0666, 1.0790, 1.0483, 1.0498, 1.0560, 1.0283, 1.0382, 1.0568, 1.0377, 1.0378, 1.0386, 1.0648, 1.0462, 1.0800, 1.0666, 1.0520, 1.0573, 1.0795, 1.0424, 1.0785, 1.0991, 1.0770, 1.0730, 1.0582, 1.0484, 1.0506, 1.0524, 1.0530, 1.0480, 1.0412, 1.0578, 1.0547, 1.0569, 1.0593, 1.0500, 1.0538, 1.0355, 1.0486, 1.0503, 1.0384, 1.0607, 1.0529, 1.0671, 1.0404, 1.0575, 1.0358, 1.0414, 1.0652, 1.0623, 1.0674, 1.0587, 1.0373, 1.0590, 1.0515, 1.0648, 1.0575, 1.0472, 1.0452, 1.0398, 1.0435, 1.0374, 1.0491, 1.0325, 1.0481, 1.0522, 1.0422, 1.0571, 1.0459, 1.0775, 1.0754, 1.0664, 1.0550, 1.0322, 1.0873, 1.0416, 1.0776, 1.0542, 1.0758, 1.0610, 1.0510, 1.0594, 1.0287, 1.0761, 1.0704, 1.0477, 1.0775, 1.0653, 1.0690, 1.0644, 1.0370, 1.0549, 1.0492, 1.0525, 1.0180, 1.0610, 1.0926, 1.0983, 1.0521, 1.0603, 1.0414, 1.0763, 1.0689, 1.0316, 1.0477, 1.0603, 1.0387, 1.1089, 1.0725, 1.0713, 1.0587, 1.0794, 1.0453, 1.0524, 1.0520, 1.0434, 1.0728, 1.0140, 1.0624, 1.0429, 1.0470, 1.0411, 1.0488, 1.0583, 1.0841, 1.0462, 1.0709, 1.0484, 1.0340, 1.0854, 1.0209, 1.0610, 1.0250, 1.0254, 1.0771, 1.0742, 1.0829, 1.0373, 1.0543, 1.0561, 1.0543, 0.9950, 1.0678, 1.0819, 1.0433, 1.0646, 1.0706, 1.0399, 1.0726, 1.0874, 1.0740, 1.0703, 1.0650, 1.0418, 1.0647, 1.0601, 1.0745, 1.0620, 1.0636, 1.0384, 1.0403, 1.0563, 1.0424, 1.0372, 1.0705, 1.0316, 1.0599, 1.0207, 1.0304, 1.0256, 1.0334, 1.0641, 1.0308, 1.0736, 1.0236, 1.0328, 1.0399, 1.0271) bfat<-c( 12.3, 6.1, 25.3, 10.4, 28.7, 20.9, 19.2, 12.4, 4.1, 11.7, 7.1, 7.8, 20.8, 21.2, 22.1, 20.9, 29.0, 22.9, 16.0, 16.5, 19.1, 15.2, 15.6, 17.7, 14.0, 3.7, 7.9, 22.9, 3.7, 8.8, 11.9, 5.7, 11.8, 21.3, 32.3, 40.1, 24.2, 28.4, 35.2, 32.6, 34.5, 32.9, 31.6, 32.0, 7.7, 13.9, 10.8, 5.6, 13.6, 4.0, 10.2, 6.6, 8.0, 6.3, 3.9, 22.6, 20.4, 28.0, 31.5, 24.6, 26.1, 29.8, 30.7, 25.8, 32.3, 30.0, 21.5, 13.8, 6.3, 12.9, 24.3, 8.8, 8.5, 13.5, 11.8, 18.5, 8.8, 22.2, 21.5, 18.8, 31.4, 26.8, 18.4, 27.0, 27.0, 26.6, 14.9, 23.1, 8.3, 14.1, 20.5, 18.2, 8.5, 24.9, 9.0, 17.4, 9.6, 11.3, 17.8, 22.2, 21.2, 20.4, 20.1, 22.3, 25.4, 18.0, 19.3, 18.3, 17.3, 21.4, 19.7, 28.0, 22.1, 21.3, 26.7, 16.7, 20.1, 13.9, 25.8, 18.1, 27.9, 25.3, 14.7, 16.0, 13.8, 17.5, 27.2, 17.4, 20.8, 14.9, 18.1, 22.7, 23.6, 26.1, 24.4, 27.1, 21.8, 29.4, 22.4, 20.4, 24.9, 18.3, 23.3, 9.4, 10.3, 14.2, 19.2, 29.6, 5.3, 25.2, 9.4, 19.6, 10.1, 16.5, 21.0, 17.3, 31.2, 10.0, 12.5, 22.5, 9.4, 14.6, 13.0, 15.1, 27.3, 19.2, 21.8, 20.3, 34.3, 16.5, 3.0, 0.7, 20.5, 16.9, 25.3, 9.9, 13.1, 29.9, 22.5, 16.9, 26.6, 2.0, 11.5, 12.1, 17.5, 8.6, 23.6, 20.4, 20.5, 24.4, 11.4, 38.1, 15.9, 24.7, 22.8, 25.5, 22.0, 17.7, 6.6, 23.6, 12.2, 22.1, 28.7, 6.0, 34.8, 16.6, 32.9, 32.8, 9.6, 10.8, 7.1, 27.2, 19.5, 18.7, 19.5, 47.5, 13.6, 7.5, 24.5, 15.0, 12.4, 26.0, 11.5, 5.2, 10.9, 12.5, 14.8, 25.2, 14.9, 17.0, 10.6, 16.1, 15.4, 26.7, 25.8, 18.6, 24.8, 27.3, 12.4, 29.9, 17.0, 35.0, 30.4, 32.6, 29.0, 15.2, 30.2, 11.0, 33.6, 29.3, 26.0, 31.9) age<-c(23,22,22,26,24,24,26,25,25,23,26,27,32,30,35,35,34,32,28,33,28,28,31, 32,28,27,34,31,27,29,32,29,27,41,41,49,40,50,46,50,45,44,48,41,39,43,40,39, 45,47,47,40,51,49,42,54,58,62,54,61,62,56,54,61,57,55,54,55,54,55,62,55,56, 55,61,61,57,69,81,66,67,64,64,70,72,67,72,64,46,48,46,44,47,46,47,53,38,50, 46,47,49,48,41,49,43,43,43,52,43,40,43,43,47,42,48,40,48,51,40,44,52,44,40, 47,50,46,42,43,40,42,49,40,47,50,41,44,39,43,40,49,40,40,52,23,23,24,24,25, 25,26,26,26,27,27,27,28,28,28,30,31,31,33,33,34,34,35,35,35,35,35,35,35,35, 36,36,37,37,37,38,39,39,40,40,40,40,40,41,41,41,41,41,42,42,42,42,42,42,42, 42,43,43,43,43,44,44,44,44,47,47,47,49,49,49,50,50,51,51,51,52,53,54,54,54, 55,55,55,55,55,56,56,57,57,58,58,60,62,62,63,64,65,65,65,66,67,67,68,69,70,72,72,72,74) weight<-c(154.25,173.25,154,184.75,184.25,210.25,181,176,191,198.25,186.25, 216,180.5,205.25,187.75,162.75,195.75,209.25,183.75,211.75,179,200.5,140.25, 148.75,151.25,159.25,131.5,148,133.25,160.75,182,160.25,168,218.5,247.25, 191.75,202.25,196.75,363.15,203,262.75,205,217,212,125.25,164.25,133.5, 148.5,135.75,127.5,158.25,139.25,137.25,152.75,136.25,198,181.5,201.25,202.5, 179.75,216,178.75,193.25,178,205.5,183.5,151.5,154.75,155.25,156.75,167.5,146.75, 160.75,125,143,148.25,162.5,177.75,161.25,171.25,163.75,150.25,190.25,170.75, 168,167,157.75,160,176.75,176,177,179.75,165.25,192.5,184.25,224.5,188.75,162.5,156.5,197, 198.5,173.75,172.75,196.75,177,165.5,200.25,203.25,194,168.5,170.75,183.25,178.25, 163,175.25,158,177.25,179,191,187.5,206.5,185.25,160.25,151.5,161,167, 177.5,152.25,192.25,165.25,171.75,171.25,197,157,168.25,186,166.75,187.75, 168.25,212.75,176.75,173.25,167,159.75,188.15,156,208.5,206.5,143.75,223,152.25, 241.75,146,156.75,200.25,171.5,205.75,182.5,136.5,177.25,151.25,196,184.25, 140,218.75,217,166.25,224.75,228.25,172.75,152.25,125.75,177.25,176.25,226.75, 145.25,151,241.25,187.25,234.75,219.25,118.5,145.75,159.25,170.5,167.5,232.75, 210.5,202.25,185,153,244.25,193.5,224.75,162.75,180,156.25,168,167.25,170.75, 178.25,150,200.5,184,223,208.75,166,195,160.5,159.75,140.5,216.25,168.25,194.75, 172.75,219,149.25,154.5,199.25,154.5,153.25,230,161.75,142.25,179.75,126.5, 169.5,198.5,174.5,167.75,147.75,182.25,175.5,161.75,157.75,168.75,191.5,219.15, 155.25,189.75,127.5,224.5,234.25,227.75,199.5,155.5,215.5,134.25,201,186.75, 190.75,207.5) height<-c(67.75, 72.25, 66.25, 72.25, 71.25, 74.75, 69.75, 72.50, 74.00, 73.50, 74.50, 76.00, 69.50, 71.25, 69.50, 66.00, 71.00, 71.00, 67.75, 73.50, 68.00, 69.75, 68.25, 70.00, 67.75, 71.50, 67.50, 67.50, 64.75, 69.00, 73.75, 71.25, 71.25, 71.00, 73.50, 65.00, 70.00, 68.25, 72.25, 67.00, 68.75, 29.50, 70.00, 71.50, 68.00, 73.25, 67.50, 71.25, 68.50, 66.75, 72.25, 69.00, 67.75, 73.50, 67.50, 72.00, 68.00, 69.50, 70.75, 65.75, 73.25, 68.50, 70.25, 67.00, 70.00, 67.50, 70.75, 71.50, 69.25, 71.50, 71.50, 68.75, 73.75, 64.00, 65.75, 67.50, 69.50, 68.50, 70.25, 69.25, 67.75, 67.25, 72.75, 70.00, 69.25, 67.50, 67.25, 65.75, 72.50, 73.00, 70.00, 69.50, 70.50, 71.75, 74.50, 77.75, 73.25, 66.50, 68.25, 72.00, 73.50, 72.00, 71.25, 73.75, 69.25, 68.50, 73.50, 74.25, 75.50, 69.25, 68.50, 70.00, 70.00, 70.25, 71.75, 69.25, 72.75, 72.00, 74.00, 72.25, 74.50, 71.50, 68.75, 66.75, 66.50, 67.00, 68.75, 67.75, 73.25, 69.75, 71.50, 70.50, 73.25, 66.75, 69.50, 69.75, 70.75, 74.00, 71.25, 75.00, 71.00, 69.50, 67.75, 72.25, 77.50, 70.75, 72.75, 69.75, 72.50, 70.25, 69.00, 74.50, 72.25, 67.25, 73.50, 75.25, 69.00, 72.25, 68.75, 71.50, 72.25, 73.00, 68.75, 70.50, 72.00, 73.75, 68.00, 72.25, 69.50, 69.50, 67.75, 65.50, 71.00, 71.50, 71.75, 69.25, 67.00, 71.50, 69.25, 74.50, 74.25, 68.00, 67.25, 69.75, 74.25, 71.50, 74.25, 72.00, 72.50, 68.25, 69.25, 76.00, 70.50, 74.75, 72.75, 68.25, 69.00, 71.50, 72.75, 67.50, 70.25, 69.25, 71.50, 74.00, 69.75, 73.00, 65.50, 72.50, 70.25, 70.75, 68.00, 74.50, 71.75, 70.75, 73.00, 64.00, 69.75, 70.00, 71.75, 69.25, 70.50, 72.25, 67.50, 67.25, 68.75, 66.75, 68.25, 74.25, 69.50, 68.50, 65.75, 71.75, 71.50, 67.25, 67.50, 67.50, 72.25, 69.50, 69.50, 65.75, 65.75, 68.25, 72.00, 72.75, 68.50, 69.25, 70.50, 67.00, 69.75, 66.00, 70.50, 70.00) neck<-c(36.2,38.5,34,37.4,34.4,39,36.4,37.8,38.1,42.1,38.5,39.4,38.4,39.4, 40.5,36.4,38.9,42.1,38,40,39.1,41.3,33.9,35.5,34.5,35.7,36.2,38.8,36.4,36.7,38.7, 37.3,38.1,39.8,42.1,38.4,38.5,42.1,51.2,40.2,43.2,36.6,37.3,41.5,31.5,35.7, 33.6,34.6,32.8,34,34.9,34.3,36.5,35.1,37.8,39.9,39.1,40.5,40.5,38.4,41.4,35.6,38, 37.4,40.1,40.9,35.6,36.9,37.5,36.3,35.5,38.7,36.4,33.2,36.5,36,38.7,38.7,37.8, 37.4,38.4,38.1,39.3,38.7,38.5,36.5,37.7,36.5,38,36.7,37.2,39.2,37.5,38,37.3, 41.1,37.5,38.7,35.9,40,40.1,37,36.3,40.7,39.6,31.1,38.6,42,38.5,34.2,37.2,37.1, 40.2,35.3,38,36.3,36.8,41,38.3,38,40.8,39.5,36.9,36.9,37.7,36.6,38.9,37.5, 39.8,38.3,35.5,36.3,37.8,37.8,36.5,37.8,37,37.7,34.3,40.8,37.4,36.5,37.5,35.5, 38,35.7,39.2,40.9,35.2,40.6,35.4,41.8,34.1,37.9,38.2,35.6,38.5,37,35.9,36.2, 35,38.5,40.7,36,39.5,40.5,38.5,43.9,40.4,37.6,37,34,38.4,38.7,41.5,36,35.3,42.1, 38,42.8,40,33.8,35.5,35.3,37.7,39.4,41.9,38.5,40.8,38,36.4,41.8,40.7,38.5, 35.4,38.5,35.5,36.5,37.6,37.4,37.8,35.2,37.9,37.9,40.9,41.9,39.1,40.2,36,34.5, 35.8,40.2,38.3,39,37.4,41.2,34.8,36.9,39.4,37.6,38.5,42.5,37.4,35.2,41.1,33.4, 37.2,38.3,38.1,37.4,35.2,39.4,38,35.1,40.4,38.3,40.6,40.2,37.9,40.8,34.7,38.8, 41.4,41.3,40.7,36.3,40.8,34.9,40.9,38.9,38.9,40.8) chest<-c(93.1,93.6,95.8,101.8,97.3,104.5,105.1,99.6,100.9,99.6,101.5,103.6,102,104.1, 101.3,99.1,101.9,107.6,106.8,106.2,103.3,111.4,86,86.7,90.2,89.6, 88.6,97.4,93.5,97.4,100.5,93.5,93,111.7,117,118.5,106.5,105.6,136.2,114.8,128.3,106, 113.3,106.6,85.1,96.6,88.2,89.8,92.3,83.4,90.2,89.2,89.7,93.3,87.6, 107.6,100,111.5,115.4,104.8,112.3,102.9,107.6,105.3,105.3,103,90,95.4,89.3,94.4, 97.6,88.5,93.6,87.7,93.4,91.6,91.6,102,96.4,102.7,97.7,97.1,103.1,101.8, 101.4,98.9,97.5,104.3,97.3,96.7,99.7,101.9,97.2,106.6,99.6,113.2,99.1,99.4, 95.1,107.5,106.5,99.1,96.7,103.5,104,93.1,105.2,110,110.1,97.8,96.3,108,99.7,93.5, 100.7,97,96,99.2,95.4,101.8,104.3,99.2,99.3,94,98.9,101,98.7,95.9,103.9,96.2, 97.8,94.6,103.6,100.4,98.4,104.6,92.9,97.8,98.3,104.7,98.6,99.5,102.7,92.1,96.6, 92.7,102,110.9,92.3,114.1,92.9,108.3,88.5,94,101.1,92.1,105.6,98.5,88.7,101.1, 94,103.8,98.9,89.2,111.4,107.5,99.1,108.2,114.9,99.1,92.2,90.8,100.5,98.2,115.3, 96.8,92.6,119.2,102.7,109.5,108.5,79.3,95.5,92.3,98.9,89.5,117.5,107.4,109.2,103.4, 91.4,115.2,104.9,106.7,92.2,101.6,97.8,92,94,103.7,102.7,91.1,107.2,100.8,121.6, 105.6,100.6,102.7,99.8,92.9,91.2,115.6,98.3,103.7,98.7,119.8,92.8,93.3,106.8,93.9, 99,119.9,94.2,92.7,106.9,88.8,101.7,105.3,104,98.6,99.6,103.4,100.2,94.9,97.2, 104.7,104,117.6,95.8,106.4,93,119.6,119.7,115.8,118.3,97.4,113.7,89.2,108.5, 111.1,108.3,112.4) abdomen<-c(85.2,83,87.9,86.4,100,94.4,90.7,88.5,82.5,88.6,83.6,90.9,91.6,101.8, 96.4,92.8,96.4,97.5,89.6,100.5,95.9,98.8,76.4,80,76.3,79.7,74.6,88.7,73.9,83.5, 88.7,84.5,79.1,100.5,115.6,113.1,100.9,98.8,148.1,108.1,126.2,104.3,111.2,104.3, 76,81.5,73.7,79.5,83.4,70.4,86.7,77.9,82,79.6,77.6,100,99.8,104.2,105.3, 98.3,104.8,94.7,102.4,99.7,105.5,100.3,83.9,86.6,78.4,84.6,91.5,82.8,82.9,76,83.3, 81.8,78.8,95,95.4,98.6,95.8,89,97.8,94.9,99.8,89.7,88.1,90.9,86,86.5, 95.6,93.2,83.1,97.5,88.8,99.2,91.6,86.7,88.2,94,95,92,89.2,95.5,98.6,87.3,102.8, 101.6,88.7,92.3,90.6,105,95,89.6,92.4,86.6,90,90,92.4,87.5,99.2,98.1,83.3, 86.1,84.1,89.9,92.1,78,93.5,87,90.1,90.3,99.8,89.4,87.2,101.1,86.1,98.6,88.5,106.6, 93.1,93,91,77.1,85.3,81.9,99.1,100.5,76.5,106.8,77.6,102.9,72.8,88.2, 100.1,83.5,105,90.8,76.6,92.4,81.2,95.6,92.1,83.4,106,95.1,90.4,100.4,115.9,90.8, 81.9,75,90.3,90.3,108.8,79.4,83.2,110.3,92.7,104.5,104.6,69.4,83.6,86.8, 90.4,83.7,109.3,98.9,98,101.2,80.6,113.7,94.1,105.7,85.6,96.6,86,89.7,78,89.7,89.2, 85.7,103.1,89.1,113.9,96.3,93.9,101.3,83.9,84.4,79.4,104,89.7,97.6,87.6, 122.1,81.1,81.5,100,88.7,91.8,110.4,87.6,82.8,95.3,78.2,91.1,96.7,89.4,93,86.4, 96.7,88.1,94.9,93.3,95.6,98.2,113.8,82.8,100.5,79.7,118,109,113.4,106.1, 84.3,107.6,83.6,105,111.5,101.3,108.5) hip<-c(94.5,98.7,99.2,101.2,101.9,107.8,100.3,97.1,99.9,104.1,98.2,107.7,103.9, 108.6,100.1,99.2,105.2,107,102.4,109,104.9,104.8,94.6,93.4,95.8,96.5,85.3,94.7, 88.5, 98.7, 99.8,100.6,94.5,108.3,116.1,113.8,106.2,104.8,147.7,102.5,125.6, 115.5,114.1,106,88.2,97.2,88.5,92.7,90.4,87.2,98.3,91,89.1,91.6,88.6,99.6, 102.5,105.8,97,99.6,103.1,100.8,99.4,99.7,108.3,104.2,93.9,91.8,96.1,94.3,98.5, 95.5,96.3,88.6,93,94.8,94.3,98.3,99.3,100.2,97.1,96.9,99.6,95,96.2,96.2, 96.9,93.8,99.3,98.3,102.2,100.6,95.4,100.6,101.4,107.5,102.4,96.2,92.8,103.7, 101.7,98.3,98.3,101.6,99.5,96.6,103.6,100.7,102.1,100.6,99.3,103,98.6,99.8, 97.5,92.6,99.7,96.4,104.3,101,104.1,101.4,97.5,95.2,94,100,98.5,93.2,99.5,97.8, 95.8,99.1,103.2,92.3,98.4,102.1,95.6,100.6,98.3,107.7,101.6,99.3,98.9, 93.9,102.5,95.3,110.1,106.2,92.1,113.9,93.5,114.4,91.1,95.2,105,98.3,106.4,102.5, 89.8,99.3,91.5,105.1,103.5,89.6,108.8,104.5,95.6,106.8,111.9,98.1, 92.8,89.2,98.7,99.9,114.4,89.2,96.4,113.9,101.9,109.9,109.8,85,91.6,96.1,95.5, 98.1,108.8,104.1,101.8,103.1,92.3,112.4,102.7,111.8,96.5,100.6,96.2,101,99, 94.2,99.2,96.9,105.5,102.6,107.1,102,100.1,101.7,91.8,94,89,109,99.1,104.2,96.1, 112.8,96.3,94.4,105,94.5,96.2,105.5,95.6,91.9,98.2,87.5,97.1,106.6,98.4, 97,90.1,100.7,97.8,100.2,94,93.7,101.1,111.8,94.5,100.5,87.6,114.3,109.1,109.8, 101.6,94.4,110,88.8,104.5,101.7,97.8,107.1) thigh<-c(59,58.7,59.6,60.1,63.2,66,58.4,60,62.9,63.1,59.7,66.2,63.4,66,69, 63.1,64.8,66.9,64.2,65.8,63.5,63.4,57.4,54.9,58.4,55,51.7,57.5,50.1,58.9,57.5,58.5, 57.3,67.1,71.2,61.9,63.5,66,87.3,61.3,72.5,70.6,67.7,65,50,58.4,53.3,52.7, 52,50.6,52.6,51.4,49.3,52.6,51.9,57.2,62.1,61.8,59.1,60.6,61.6,60.9,61,60.8, 65,64.8,55,54.3,56,51.2,56.6,58.9,52.9,50.9,55.5,54.5,56.7,55,53.5,56.5,54.8, 54.8,58.9,56,56.3,54.7,57.2,57.8,61,60.4,58.3,58.9,56.9,58.9,57.4,61.7,60.6,62.1,54.7, 62.7,59,59.3,60,59.1,59.5,54.7,61.2,55.8,57.5,57.5,61.9,63.7,62.3,61.5,59.3, 55.9,58.8,56.8,64.6,58.5,58.5,57.1,60.5,58.1,58.5,60.7,60.7,53.5,61.7,57.4, 57,60.3,61.2,56.1,56,58.9,58.8,63.6,58.1,66.5,59.1,60.4,57.1,56.1,59.1,56.4, 71.2,68.4,51.9,67.6,56.9,72.9,53.6,56.8,62.1,57.3,68.6,60.8,50.1,59.4,52.5,61.4, 64,52.4,63.8,64.8,55.5,63.3,74.4,60.1,54.7,50,57.8,59.2,69.2,50.3,60,69.8,64.7, 69.5,68.1,47.2,54.1,58,55.4,57.3,67.7,63.5,62.8,61.5,54.3,68.5,60.6,65.3, 60.2,61.1,57.7,62.3,57.5,58.5,60.2,55.5,68.8,60.6,63.5,63.3,58.9,60.7,53,56,51.1, 63.7,56.3,60,57.1,62.5,53.8,54.7,63.9,53.7,57.7,64.2,59.7,54.4,57.4,50.8,56.6,64, 58.4,55.4,53,59.3,57.1,56.8,54.3,54.4,59.3,63.4,61.2,59.2,50.7,61.3,63.7,65.6,58.2, 54.3,63.3,49.6,59.6,60.3,56,59.3) knee<-c(37.3,37.3,38.9,37.3,42.2,42,38.3,39.4,38.3,41.7,39.7,39.2,38.3,41.5, 39,38.7,40.8,40,38.7,40.6,38,40.6,35.3,36.2,35.5,36.7,34.7,36,34.5,35.3,38.7, 38.8,36.2,44.2,43.3,38.3,39.9,41.5,49.1,41.1,39.6,42.5,40.9,40.2,34.7,38.2,34.5, 37.5,35.8,34.4,37.2,34.9,33.7,37.6,34.9,38,39.6,39.8,38,37.7,40.9,38,39.4, 40.1,41.2,40.2,36.1,35.4,37.4,37.4,38.6,37.6,37.5,35.4,35.2,37,39.7,38.3,37.5, 39.3,38.2,38,39,36.5,36.6,37.8,37.7,39.5,38.4,39.9,38.2,39.7,38.3,40.5,39.6, 42.3,39.4,39.3,37.3,39,39.4,38.4,38.4,39.8,36.1,39,39.3,38.7,40,36.8,38,40,38.1, 37.8,38.1,36.3,38.4,38.8,41.1,39.2,39.3,40.5,38.7,36.5,36.6,36,36.8,35.8,39, 36.9,38.7,38.5,38.1,35.6,36.9,37.9,36.1,39.2,38.4,42.5,39.6,38.2,36.7,36.1,37.6, 36.5,43.5,40.8,35.7,42.7,35.9,43.5,36.8,37.4,40,37.8,40,38.5,34.8,39,36.6, 40.6,37.3,35.6,42,41.3,34.2,41.7,40.6,39.1,36.2,34.8,37.3,37.7,42.4,34.8,38.1, 42.6,39.5,43.1,42.8,33.5,36.2,39.4,38.9,39.7,41.3,39.8,41.3,40.4,36.3,45,38.6, 43.3,38.9,38.4,38.6,38,40,39,39.2,35.7,38.3,39,40.3,39.8,37.6,39.4,36.2,38.2,35, 40.3,38.8,40.9,38.1,36.9,36.5,39,39.2,36.2,38.1,42.7,40.2,35.2,37.1,33,38.5, 42.6,37.4,38.8,35,38.6,38.9,35.9,35.7,37.1,40.3,41.1,39.1,38.1,33.4,42.1,42.4,46, 38.8,37.5,44,34.8,40.8,37.3,41.6,42.2) ankle<-c(21.9,23.4,24,22.8,24,25.6,22.9,23.2,23.8,25,25.2,25.9,21.5,23.7,23.1,21.7, 23.1,24.4,22.9,24,22.1,24.6,22.2,22.1,22.9,22.5,21.4,21,21.3,22.6,33.9,21.5, 24.5,25.2,26.3,21.9,22.6,24.7,29.6,24.7,26.6,23.7,25,23,21,23.4,22.5,21.9,20.6,21.9, 22.4,21,21.4,22.6,22.5,22,22.5,22.7,22.5,22.9,23.1,22.1,23.6,22.7, 24.7,22.7,21.7,21.5,22.4,21.6,22.4,21.6,23.1,19.1,20.9,21.4,24.2,21.8,21.5,22.7,23.7, 22,23,24.1,22,33.7,21.8,23.3,23.8,24.4,22.5,23.1,22.1,24.5,24.6, 23.2,22.9,23.3,21.9,22.3,22.3,22.4,23.2,25.4,22,24.8,23.5,23.4,24.8,22.8,22.3,23.6, 23.9,21.9,21.8,22.1,22.8,23.3,24.8,24.5,24.6,23.2,22.6,22.1,23.5,21.9, 22.2,20.8,21.8,22.2,23.2,23,22.6,20.5,23,22.7,22.4,23.8,22.5,24.5,21.6,22,22.3,22.7, 23.2,22,25.2,24.6,22,24.7,20.4,25.1,23.8,22.8,24.9,21.7,25.2,25,21.8, 24.6,21,25,23.5,20.4,23.4,25.6,21.9,24.6,24,23.4,22.1,22,22.4,21.5,24,22.2,22,24.8, 24.7,25.8,24.1,20.2,21.8,22.7,22.4,22.6,24.7,23.5,24.8,22.9,21.8, 25.5,24.7,26,22.4,24.1,24,22.3,22.5,24.1,23.8,22,23.7,24,21.8,24.1,21.4,23.3,22.5, 22.6,21.7,23.2,23,25.5,21.8,23.6,21.5,22.6,22.9,22,23.9,27,23.4,22.5, 21.8,19.7,22.6,23.4,22.5,23.2,21.3,22.8,23.6,21,21,22.7,23,22.3,22.3,24,20.1,23.4, 24.6,25.4,24.1,22.6,22.6,21.5,23.2,21.5,22.7,24.6) biceps<-c(32,30.5,28.8,32.4,32.2,35.7,31.9,30.5,35.9,35.6,32.8,37.2,32.5,36.9,36.1, 31.1,36.2,38.2,37.2,37.1,32.5,33,27.9,29.8,31.1,29.9,28.7,29.2,30.5, 30.1,32.5,30.1,29,37.5,37.3,32,35.1,33.2,45,34.1,36.4,33.6,36.7,35.8,26.1,29.7,27.9, 28.8,28.8,26.8,26,26.7,29.6,38.5,27.7,35.9,33.1,37.7,31.6,34.5,36.2, 32.5,32.7,33.6,35.3,34.8,29.6,32.8,32.6,27.3,31.5, 30.3,29.7,29.3,29.4,29.3,30.2, 30.8,31.4,30.3,29.4,29.9,34.3,31.2,29.7,32.4,32.6,29.2,30.2,28.8,29.1,31.4, 30.1,33.3,30.3,32.9,31.6,30.6,31.6,35.3,32.2,27.9, 31,31,30.1,31,30.5,35.1,35.1, 32.1,33.3,33.5,35.3,30.7,31.8,29.8,29.9,33.4,33.6,32.1,33.9,33,34.4,30.6,34.4, 35.6,33.8,33.9,33.3,31.6,27.5,31.2,33.5,33.6,34,30.9,32.7,34.3,31.7,35.5,30.8,32, 31.6,30.5,31.8,33.5,36.1,33.3,25.8,36,31.6,38.5,27.8,30.6,33.7,32.2,35.2, 31.6,27,30.1,27,31.3,33.5,28.3,34,36.4,30.2,37.2,36.1,32.5,30.4,24.8,31,32.4,35.4, 31,31.5,34.4,34.8,39.1,35.6,27.7,31.4, 30,30.5,32.9,37.2,36.4,36.6,33.4,29.6, 37.1,34,33.7,31.7,32.9,31.2,30.8,30.6,33.8,31.7,29.4,32.1,32.9,34.8,37.3,33.1,36.7, 31.4, 29,30.9,36.8,29.5,32.7,28.6,34.7,31.3,27.5,35.7,28.5,31.4,38.4,27.9, 29.4,34.1,25.3,33.4,33.2,34.6,32.4,31.7,31.8,30.9,27.8,31.3,30.3,32.6,35.1, 29.8,35.9,28.5,34.9,35.6,35.3,32.1,29.2,37.5,25.6,35.2,31.3,30.5,33.7) forarm<-c(27.4,28.9,25.2,29.4,27.7,30.6,27.8,29,31.1,30,29.4,30.2,28.6,31.6, 30.5,26.4,30.8,31.6,30.5,30.1,30.3,32.8,25.9,26.7,28,28.2,27,26.6,27.9,26.7, 27.7,26.4,30,31.5,31.7,29.8,30.6,30.5,29,31,32.7,28.7,29.8,31.5,23.1,27.4,26.2, 26.8,25.5,25.8,25.8,26.1,26,27.4,27.5,30.2,28.3,30.9,28.8,29.6,31.8,29.8,29.9, 29,31.1,30.1,27.4,27.4,28.1,27.1,27.3,27.3,27.3,25.7,27,27,29.2,25.7,26.8,28.7, 27.2,25.2,29.6,27.3,26.3,27.7,28,28.4,29.3,29.6,27.7,28.4,28.2,29.6,27.9,30.8, 30.1,27.8,27.5,30.9,31,26.2,29.2,30.3,27.2,29.4,28.5,29.6,30.7,26,28.2,27.8,31.1, 27.6,27.3,26.3,28,29.8,29.5,28.6,31.2,29.6,28,27.5,29.2,30.2,30.3,28.2,29.6, 27.8,26.5,28.4,28.6,29.3,29.8,28.8,28.3,28.4,27.4,29.8,27.9,28.5,27.5,27.2,29.7, 28.3,30.3,29.7,25.2,30.4,29,33.8,26.3,28.3,29.2,27.7,30.7,28,34.9,28.2,26.3, 29.2,30.6,26.2,31.2,33.7,28.7,33.1,31.8,29.8,27.4,25.9,28.7,28.4,21,26.9,26.6,29.5, 30.3,32.5,29,24.6,28.3,26.4,28.9,29.3,31.8,30.4,32.4,29.2,27.3,31.2,30.1, 29.9,27.1,29.8,27.3,27.8,30,28.8,28.4,26.6,28.9,29.2,30.7,23.1,29.5,31.6,27.5,26.2, 28.8,31,27.9,30,26.7,29.1,26.3,25.9,30.4,25.7,29.9,32,27,26.8,31.1,22, 29.3,30,30.1,29.7,27.3,29.1,29.6,26.1,28.7,26.3,28.5,29.6,28.9,30.5,24.8,30.1,30.7, 29.8,29.3,27.3,32.6,25.7,28.6,27.2,29.4,30) wrist<-c(17.1,18.2,16.6,18.2,17.7,18.8,17.7,18.8,18.2,19.2,18.5,19,17.7,18.8,18.2, 16.9,17.3,19.3,18.5,18.2,18.4,19.9,16.7,17.1,17.6,17.7,16.5,17,17.2,17.6, 18.4,17.9,18.8,18.7,19.7,17,19,19.4,21.4,18.3,21.4,17.4,18.4,18.8,16.1,18.3,17.3, 17.9,16.3,16.8,17.3,17.2,16.9,18.5,18.5,18.9,18.5,19.2,18.2,18.5,20.2, 18.3,19.1,18.8,18.4,18.7,17.4,18.7,18.1,17.3,18.6,18.3,18.2,16.9,16.8,18.3,18.1,18.8, 18.3,19,19,17.7,19,19.2,18,18.2,18.8,18.1,18.8,18.7,17.7,18.8,18.4, 19.1,17.8,20.4,18.5,18.2,18.2,18.3,18.6,17,18.4,19.7,17.7,18.8,18.1,19.1,19.2,17.3, 18.1,17.4,19.8,17.4,17.5,17.3,18.1,19.5,18.5,18,19.5,18.4,17.6,17.6, 18,17.6,17.2,17.4,18.1,17.7,17.6,17.1,17.9,17.3,18.1,17.6,17.1,17.7,17.6,18.7,16.6, 17.8,17.9,18.2,18.3,17.3,18.7,18.4,16.9,18.4,17.8,19.6,17.4,17.9,19.4, 17.7,19.1,18.6,16.9,18.2,16.5,19.1,19.7,16.5,18.5,19.4,17.7,19.8,18.8,17.4,17.7,16.9, 17.7,17.8,20.1,16.9,16.7,18.4,18.1,19.9,19,16.5,17.2,17.4,17.7,18.2, 20,19.1,18.8,18.5,17.9,19.9,18.7,18.5,17.1,18.8,17.4,16.9,18.5,18.8,18.6,17.4,18.7, 18.4,17.4,19.4,17.3,18.4,17.7,17.6,17.4,18.9,18.6,19,18,18.4,17.8,18.6,19.2,17.1,18.9, 19.6,17.8,17,19.2,15.8,18.8,18.4,18.8,19,16.9,19,18,17.6,18.3,18.3,19,18.5,18.3,19.1, 16.5,19.4,19.5,19.5,18.5,18.5,18.8,18.5,20.1,18,19.8,20.9) bodfat<-cbind(density, bfat, age, weight, height, neck, chest, abdomen, hip, thigh, knee, ankle, biceps, forarm, wrist) rm(density, bfat, age, weight, height, neck, chest, abdomen, hip, thigh, knee, ankle, biceps, forarm, wrist) ##Minor (2012) State data #gdp = GDP per capita #povrt = poverty rate #unins = 3 year average uninsured rate 2007-9 #lifexp = life expectancy #wkfrnd = worker friendly (1 yes, 0 no) gdp<- c(32748,59638,35313,32191,47067,46150,58476,62080,36065,36677, 45980,32557,44260,37495,43644,40662,32848,41836,35214,45495,50566, 34157,45392,29634,36420,32915,43990,42564,41110,50227,34056,50205, 38847,45390,37237,38644,41949,39674,40996,31618,43773,35650,42526, 36691,37579,46960,46352,30248,39617,60527) povrt <- c(15.7,8.4,14.7,17.3,13.3,11.4,9.3,10,13.2,14.7,9.1,12.6, 12.2,13.1,11.5,11.3,17.3,17.3,12.3,8.1,10,14.4,9.6,21.2,13.4,14.8, 10.8,11.3,7.6,8.7,17.1,13.6,14.6,12,13.4,15.9,13.6,12.1,11.7,15.7, 12.5,15.5,15.8,9.6,10.6,10.2,11.3,17,10.4,9.4) unins <- c(13.6,18.6,19.1,17.7,18.9,15.9,10.5,11.8,20.9,18.6,7.8, 14.9,13.7,12.6,10,12.7,15.3,18.2,9.8,13.2,5.1,12.4,8.6,18.1,13.5, 15.7,12.2,18.9,10.4,15.2,22.6,14,16.6,10.8,12.5,16.6,16.9,10.3, 11.6,16.4,12,14.9,25.5,13.6,10.1,13.4,12.2,14.4,9.1,14.3) lifexp <- c(74.4,77.1,77.5,75.2,78.2,78.2,78.7,76.8,77.5,75.3,80, 77.9,76.4,76.1,78.3,77.3,75.2,74.2,77.6,76.3,78.4,76.3,78.8,73.6, 75.9,77.2,77.8,75.8,78.3,77.5,77,77.7,75.8,78.3,76.2,75.2,77.8, 76.7,78.3,74.8,77.7,75.1,76.7,78.7,78.2,76.8,78.2,75.1,77.9,76.7) wkfrnd <-c(0,1,0,0,1,1,1,1,0,0,1,0,1,1,0,0,1,0,1,1,1,1,1,0,1,1, 0,0,1,1,1,1,0,0,1,0,1,1,1,0,0,0,0,0,1,0,1,1,1,0) state <- cbind(gdp,povrt,unins,lifexp,wkfrnd) rm(gdp,povrt,unins,lifexp,wkfrnd) ##Myers, Montgomery and Vining (2002): ceriod Poisson regression data #conc: concentration of a jet fuel that impairs reproduction #strain: type of organism #y number of Ceriodaphnia organisms counted ceriody <- c(82,58, 106, 58, 63, 62, 99, 58, 101, 73, 45, 27, 34, 28, 26, 31, 44, 28, 42, 38, 31, 19, 22, 20, 16, 22, 30, 20, 29, 28, 22, 14, 14, 14, 10, 15, 21, 14, 20, 21, 15, 9, 8, 10, 6, 12, 14, 10, 13, 16, 10, 7, 8, 3, 11, 1, 10, 8, 10, 7, 8, 4, 8, 3, 3, 2, 8, 8, 1, 4) conc <- c(0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.00, 0.50, 0.50, 0.50, 0.50, 0.50, 0.50, 0.50, 0.50, 0.50, 0.50, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.25, 1.50, 1.50, 1.50, 1.50, 1.50, 1.50, 1.50, 1.50, 1.50, 1.50, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75, 1.75) strain <- c(1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0) ceriodx <- cbind(conc,strain) rm(conc,strain) ##Myers, Montgomery and Vining (2002): popcorn data ## y = number of kernels that did not pop popy <- c(24, 28, 40, 42, 11, 16, 126, 34, 32, 32, 34, 17, 30, 17, 50) oil <- c(4, 3, 3, 2, 4, 3, 3, 2, 4, 2, 2, 3, 3, 3, 4) temp <- c(7, 5, 7, 7, 6, 6, 5, 6, 5, 6, 5, 7, 6, 6, 6) time <- c(90, 105, 105, 90, 105, 90, 75, 105, 90, 75, 90, 75, 90, 90, 75) popx <- cbind(oil, temp, time) rm(temp,oil,time) ##SAS Institute (1985, p. 146) Fitness Club Data #Three physiological and three exercise variables measured on #20 middle aged men at a fitness club. #DD plot outliers cases 9,10,14 weight <- c(191,189,193,162,189,182,211,167, 176,154,169,166,154,247,193,202,176,157,156,138) waist <- c(36,37,38,35,35,36,38,34,31,33,34,33, 34,46,36,37,37,32,33,33) pulse <- c(50,52,58,62,46,56,56,60,74,56,50,52, 64,50,46,62,54,52,54,68) chinups <- c(5,2,12,12,13,4,8,6,15,17,17,13,14, 1,6,12,4,11,15,2) situps <- c(162,110,101,105,155,101,101,125,200,251,120, 210,215,50,70,210,60,230,225,110) jumps <- c(60,60,101,37,58,42,38,40,40,250,38,115,105, 50,31,120,25,80,73,43) fitness <- cbind(weight, waist, pulse, chinups, situps, jumps) rm(weight, waist, pulse, chinups, situps, jumps) ##Schaaffhausen (1878) museum data ape <- c(0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0, 0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,1,1,1,1,1,1,1) crancap <- c(1485, 1450, 1460, 1425, 1430, 1290, 1225, 1280, 1325, 1225, 1090, 1510, 1440, 1220, 1310, 1400, 1225, 1340, 1410, 1200, 1460, 1575, 1335, 1250, 1325, 1050, 1270, 1355, 1405, 1305, 1195, 1310, 1300, 1350, 1300, 1295, 1430, 1325, 1455, 1325, 1450, 1190, 1330, 1280, 1065, 1125, 1520, 315, 340, 315, 485, 440, 480, 310, 345, 350, 385, 330, 420, 90) hdlen<- c(175, 191, 186, 191, 178, 180, 168, 179, 186, 185, 173, 184, 175, 177, 177, 185, 184, 184, 181, 174, 176, 186, 184, 168, 181, 163, 163, 168, 182, 160, 160, 165, 158, 171, 161, 171, 169, 162, 170, 168, 179, 174, 164, 175, 159, 166, 178, 113, 119, 108, 158, 131, 136, 111, 110, 117, 127, 103, 133, 75) hdbrdth<- c(148, 150, 142, 135, 148, 146, 138, 139, 136, 133, 128, 158, 153, 138, 142, 135, 128, 138, 154, 141, 146, 153, 135, 139, 135, 119, 133, 145, 141, 146, 141, 140, 142, 146, 137, 138, 141, 143, 145, 145, 137, 130, 148, 138, 132, 147, 145, 87, 95, 89, 106, 97, 103, 96, 97, 98, 98, 91, 97, 61) hdht <-c(132, 117, 122, 125, 120, 117, 120, 123, 123, 115, 120, 121, 126, 126, 130, 129, 126, 116, 119, 112, 132, 129, 131, 122, 128, 118, 126, 129, 131, 123, 128, 131, 126, 137, 129, 124, 130, 130, 134, 131, 134, 132, 122, 121, 127, 123, 128, 85, 87, 72, 85, 76, 85, 77, 79, 73, 76, 69, 84, 51) lowjaw <-c(95, 96, 101, 101, 95, 100, 96, 99, 99, 98, 88, 103, 101, 87, 90, 94, 95, 95, 99, 90, 101, 103, 98, 97, 106, 81, 105, 98, 93, 103, 97, 97, 90, 100, 94, 96, 98, 104, 97, 97, 94, 87, 97, 93, 98, 99, 99, 74, 85, 55, 110, 112, 122, 75, 79, 94, 90, 55, 85, 42) facelen<-c(100, 121, 123, 113, 127, 120, 108, 120, 115, 118, 89, 115, 109, 118, 107, 121, 118, 108, 117, 117, 109, 106, 119, 110, 118, 79, 118, 107, 119, 117, 102, 107, 121, 124, 107, 113, 112, 127, 108, 125, 114, 124, 114, 110, 116, 120, 111, 110, 132, 71, 146, 185, 178, 111, 88, 126, 130, 72, 112, 50) upjaw <-c(74, 83, 82, 74, 87, 83, 72, 85, 78, 77, 61, 75, 73, 81, 71, 81, 78, 68, 79, 79, 75, 72, 76, 74, 76, 53, 76, 73, 76, 75, 69, 71, 86, 78, 79, 74, 75, 84, 73, 83, 72, 85, 70, 75, 78, 79, 77, 75, 98, 50, 115, 141, 127, 75, 61, 91, 94, 51, 84, 33) htjaw <- c(34, 38, 40, 39, 46, 42, 36, 40, 41, 41, 29, 40, 35, 43, 40, 40, 43, 38, 44, 38, 38, 38, 43, 41, 43, 29, 45, 37, 45, 43, 36, 41, 45, 42, 39, 36, 35, 47, 41, 47, 38, 47, 42, 37, 38, 40, 42, 46, 53, 28, 65, 67, 82, 46, 33, 64, 62, 29, 56, 21) eyewdth <- c(96, 106, 103, 115, 109, 112, 110, 113, 109, 110, 95, 117, 109, 101, 100, 112, 121, 109, 119, 108, 112, 115, 109, 107, 113, 93, 109, 118, 116, 117, 107, 105, 100, 108, 106, 106, 121, 106, 115, 112, 105, 103, 108, 102, 106, 109, 109, 70, 93, 50, 130, 116, 117, 72, 67, 80, 97, 52, 97, 43) diaglen <-c(234, 237, 237, 231, 236, 223, 211, 230, 231, 230, 204, 237, 223, 229, 226, 238, 239, 227, 230, 226, 228, 228, 238, 224, 238, 201, 232, 232, 234, 233, 217, 221, 220, 240, 227, 226, 229, 238, 234, 240, 232, 235, 230, 218, 228, 238, 226, 181, 209, 128, 290, 289, 283, 178, 170, 202, 224, 102, 203, 99) museum <- cbind(ape,crancap,hdlen,hdbrdth,hdht,lowjaw,facelen,upjaw,htjaw,eyewdth,diaglen) rm(ape,crancap,hdlen,hdbrdth,hdht,lowjaw,facelen,upjaw,htjaw,eyewdth,diaglen) ##Wisseman, Hopke and Schindler-Kaudelka (1987) pottery data #groups 1-Arretine, 2-not-Arretine, 3-North Italian, 4-Central Italian #5-questionable origin #cases 2,5,14,26-36 Arretine #cases 3 and 21 not Arretine #cases 17 and 23 North Italian #cases 1,8,11,13,18 were guessed to be Central Italian #cases 12, 19, 22, 25 were guessed to be Arretine #case 15 guessed to be North Italian group <- c(4,1,2,5,1,5,5,4,5,5,4,1,4,1,3,5,3,4,1,5, 2,1,3,5,1,1,1,1,1,1,1,1,1,1,1,1) Ga <- c(51.6,40.8,56,48.5,11,55.3,74.4,48.9,47.5,42.7, 50.5,61.4,43.8,40.9,27.3,44.1,41,60.2,42,38.5, 29.7,39.1,36.9,54.3,55.7,42,48,55.6,56.5,35.6, 48.9,42.3,65.5,51.7,62.9,46.7) As <- c(7.41,5,4.5,6.6,8.1,9.3,3.2,9.5,5.96,7.53, 4.6,6.8,10,7,10.1,6.5,18.2,8,1.3,14.4, 12.5,6.8,11.4,16.6,6.95,3.74,2.31,2.39,3.25,3.95, 2.34,2.95,4.81,4.98,2.35,5.93) Na <- c(.581,.484,.47,.552,.578,.442,.419,.504,.648,.64, .758,.504,.54,.395,.718,.503,.509,.604,.571,.6, .875,.57,.876,.594,.58,.654,.456,.376,.325,.443, .377,.469,.464,.453,.341,.467) K <- c(1.84,1.6,1.25,1.54,2.03,1.41,1.29,1.61,1.72,1.43, 1.85,1.32,1.55,1.63,1.82,2.13,2.68,1.94,2.65,2.38, 2.66,2,2.2,2,2.03,2.08,2.02,1.46,1.46,1.85, 1.68,1.88,1.5,1.69,1.39,1.81) Sc <- c(11.8,14.7,9.34,9.62,13.3,10.5,9.11,10.9,11.4,11.5, 12,10.8,10.9,14.7,12.3,12.7,13.24,11.3,14.6,13.7, 13.5,14.3,10.2,11.9,12.5,13,15.4,12.5,12.4,16.8, 13.7,15.1,11,12.8,11.3,16) Cr <- c(97,134,90.6,85.3,120,85.8,81.8,89.7,101,103, 121,103,97.5,130,104,110,118,100,140,120, 121,146,83.5,97.1,96.7,130,146,125,113,165, 129,147,106,118,109,150) Mn <- c(800,910,492,718,437,690,543,813,953,337, 576,422,526,994,769,667,770,736,1050,900, 980,914,792,880,792,875,1090,773,830,982, 980,1155,800,964,946,990) Fe <- c(3.51,4.06,2.61,2.85,2.83,3.15,2.58,3.23,3.44,2.59, 3.16,3.07,2.94,4.02,3.61,3.54,3.88,3.31,3.95,3.85, 3.94,3.83,3.11,3.57,3.47,3.65,4.02,3.41,3.29,4.7, 3.72,4.16,3.04,3.46,3.65,4.36) Co <- c(14.7,19.4,11.6,13.3,14.1,13,11.2,1.43,15.5,15.2, 14.5,12.6,12.4,19.4,15.8,1.57,14.41,14.1,26.6,16.4, 17.8,19.4,13.1,16,16.9,17.3,20.1,16.5,15.1,22.5, 18,20.2,15.6,17.1,15.5,22.5) Rb <- c(118,110,68,96,117,118,71,104,146,103, 100,94.1,104,115,105,100,130,105,96.9,120, 135,110,105,130,93.4,105,117,80.3,74.8,114, 98,108,72.5,76,82,109) Sb <- c(1.55,.92,.82,1.21,1.81,1.74,1.2,1.12,1,2.3, .29,.92,.32,2.1,1.38,1.75,1.21,1.03,.81,1.25, 1.4,.7,1.38,1.6,.82,.83,.7,.84,.8,1.1, 4.7,.55,.87,.62,.27,.78) Cs <- c(9.53,5.56,5.66,6.9,7.37,10.8,7.03,8.93,13.1,18.6, 6.03,5.69,5.82,6.25,10.3,7.91,13.3,8.47,6.05,7.76, 11.6,6.3,9,1.49,6.1,5.76,7.1,5.8,5.7,6.8, 5.6,6,5.2,6.1,4.61,7) Ba <- c(390,330,280,374,450,540,397,420,360,61, 210,186,107,380,420,90,540,520,440,520, 650,362,500,550,344,351,384,340,324,448, 340,520,335,327,308,440) La <- c(32.4,29.2,24.5,28.5,30.1,35.2,24.1,31.4,31,31.4, 26.9,30.4,37.8,39.2,44.6,36.8,42,37.1,36.4,38.6, 47.7,38,38,53.1,32.5,33.3,38.1,30,30.5,41.3, 33.6,37.5,28.2,32,29.2,39.3) Ce <- c(71.1,67.4,40.8,57,58.7,74.3,50.4,66.9,78.2,66.4, 54.2,49.2,50.3,66.7,79.2,62.2,75.4,64.8,64.5,66.6, 72.8,69.5,69.4,92.3,57.6,59.3,65.6,57.1,56.9,76.7, 62.6,67.3,57.9,56.7,53.6,73.3) Eu <- c(1.23,1.01,.71,.936,.983,.973,.779,.96,1.18,.996, .81,.886,.89,.9,1.09,.857,1.19,1.18,1.54,1.4, 1.71,1.28,1.34,1.52,1.18,1.22,1.26,.9,1.01,1.46, 1.66,1.27,1.02,1.09,.81,1.1) Yb <- c(2.03,2.6,1.7,2.4,2.09,2.5,2.2,2.6,2.7,2.4, 2.5,2.43,2.3,2.5,2.9,2.7,3.2,2.81,2.7,2.59, 3.02,3.2,2.98,2.94,2.4,2.74,2.9,2.39,2.3,3.45, 2.7,3.1,2.12,2.51,2.13,3.2) Hf <- c(2.93,2.85,2.48,3.5,3.01,3.36,2.86,3.12,4.11,3.26, 3.06,2.78,2.4,2.73,3.78,3.24,3.75,3.51,3.03,3.08, 4.4,3.2,3.81,4.1,2.55,2.77,2.78,2.86,2.4,3.3, 3,3.1,2.45,2.32,2.2,2.91) Ta <- c(1.18,.87,.68,.804,1.3,.15,.646,.895,.29,.97, .94,.777,.61,1.1,1.06,.63,.9,.9,1,1.06, 1.1,.9,.9,1.1,.7,1,.9,.7,.8,1.4, 1.15,1,.7,.81,.9,1.19) Th <- c(17.6,12.2,8.83,12.5,12,18.5,11.3,16.3,2.01,11.9, 10.5,9.4,9.41,11.1,18,13,17.3,14.6,15,14.1, 19.5,12.2,15,25.9,9.9,11,12.2,10.3,9.9,14, 11.1,12.3,12.5,10.3,8.6,12.9) Ga <- Ga/10; Na<-Na*10; Sc<-Sc/10; Cr<-Cr/10; Mn<-Mn/100; Co<-Co/10; Ba<-Ba/100; La<-La/10; Ce <- Ce/10; Th <- Th/10; pottery <- cbind(group,As,Ba,Ce,Co,Cr,Cs,Eu,Fe,Ga,Hf,K, La,Mn,Na,Rb,Sb,Sc,Ta,Th,Yb) rm(group,As,Ba,Ce,Co,Cr,Cs,Eu,Fe,Ga,Hf,K,La,Mn,Na,Rb,Sb,Sc,Ta,Th,Yb)