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Data X:
'Baiomys_taylori' 7.43 63.9 21.99 2.52 10 68.35 20.38 'Dicrostonyx_groenlandicus' 58.44 117.32 20.84 3.78 2 38.61 17.42 'Eliomys_quercinus' 114.61 138.74 22.97 4.99 1 566.36 34.8 'Lagostomus_maximus' 4660.94 523.73 155.73 1.93 1.25 287.76 55.68 'Lagurus_lagurus' 20.6 92.52 20.24 4 5.25 41.82 20.84 'Beamys_hindei' 75.8 149.23 22.79 3.49 5 181.13 38.49 1 2 3 'Chinchilla_chinchilla' 499.99 305 111 2.5 2.5 247.48 48.99 'Castor_canadensis' 18124.41 754.74 111.59 3.6 1 663.02 46.5 'Cricetomys_gambianus' 1267.52 362.64 31.45 3.11 2 177.08 34.54 'Cuniculus_paca' 8172.55 647.06 116.24 1.01 1.75 335.48 82.75 'Cynomys_gunnisoni' 797.93 279.12 29.64 4.48 1 395.29 36.65 'Cynomys_leucurus' 963.76 307.49 30.39 5.4 1 413.84 31.76 'Cynomys_ludovicianus' 797.05 294.04 33.46 4.43 1 696.9 45.57 'Dipodomys_deserti' 107.63 138.11 30.5 3.36 2.5 50.88 24.17 'Dipodomys_heermanni' 63.08 111.25 30.99 3.11 2 53.13 25.9 'Dipodomys_merriami' 37.91 98.54 30.77 2.39 1.75 67.11 20.42 'Dipodomys_microps' 56.26 112.47 30.99 2.37 1 147.92 21 'Dipodomys_spectabilis' 124.61 141.14 23.5 2.67 2 310.33 23.47 'Dolichotis_patagonum' 8000 663.84 97.97 1.75 3.5 216.03 76.28
Names of X columns:
RodentiaBinomial AdultBodyMass_g AdultHeadBodyLength_mm GestationLength_d LitterSize LittersPerYear SexualMaturityAge_d WeaningAge_d
Number of Factors
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R Code
par1 <- '2' library(psych) par1 <- as.numeric(par1) x <- t(x) nrows <- length(x[,1]) ncols <- length(x[1,]) y <- array(as.double(x[1:nrows,2:ncols]),dim=c(nrows,ncols-1)) colnames(y) <- colnames(x)[2:ncols] rownames(y) <- x[,1] y fit <- principal(y, nfactors=par1, rotate='varimax') fit fs <- factor.scores(y,fit) fs bitmap(file='test2.png') plot(fs$scores,pch=20) text(fs$scores,labels=rownames(y),pos=3) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Rotated Factor Loadings',par1+1,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variables',1,TRUE) for (i in 1:par1) { a<-table.element(a,paste('Factor',i,sep=''),1,TRUE) } a<-table.row.end(a) for (j in 1:length(fit$loadings[,1])) { a<-table.row.start(a) a<-table.element(a,rownames(fit$loadings)[j],header=TRUE) for (i in 1:par1) { a<-table.element(a,round(fit$loadings[j,i],3)) } a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab')
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