R version 2.9.0 (2009-04-17)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- array(list('A.rat'
+ ,0
+ ,0.81954393554187
+ ,6.3
+ ,0.30102999566398
+ ,0.65321251377534
+ ,1.6232492903979
+ ,3
+ ,1
+ ,3
+ ,'Elephant'
+ ,3.40602894496362
+ ,3.66304097489397
+ ,2.1
+ ,0.25527250510331
+ ,1.83884909073726
+ ,2.79518458968242
+ ,3
+ ,5
+ ,4
+ ,'Baboon'
+ ,1.02325245963371
+ ,2.25406445291434
+ ,9.1
+ ,-0.15490195998574
+ ,1.43136376415899
+ ,2.25527250510331
+ ,4
+ ,4
+ ,4
+ ,'B.bat'
+ ,-1.69897000433602
+ ,-0.52287874528034
+ ,15.8
+ ,0.5910646070265
+ ,1.27875360095283
+ ,1.54406804435028
+ ,1
+ ,1
+ ,1
+ ,'Tapir'
+ ,2.20411998265592
+ ,2.22788670461367
+ ,5.2
+ ,0
+ ,1.48287358360875
+ ,2.59328606702046
+ ,4
+ ,5
+ ,4
+ ,'Cat'
+ ,0.51851393987789
+ ,1.40823996531185
+ ,10.9
+ ,0.55630250076729
+ ,1.44715803134222
+ ,1.79934054945358
+ ,1
+ ,2
+ ,1
+ ,'Chimp'
+ ,1.71733758272386
+ ,2.64345267648619
+ ,8.3
+ ,0.14612803567824
+ ,1.69897000433602
+ ,2.36172783601759
+ ,1
+ ,1
+ ,1
+ ,'Chinchilla'
+ ,-0.36653154442041
+ ,0.80617997398389
+ ,11
+ ,0.17609125905568
+ ,0.84509804001426
+ ,2.04921802267018
+ ,5
+ ,4
+ ,4
+ ,'Cow'
+ ,2.66745295288995
+ ,2.62634036737504
+ ,3.2
+ ,-0.15490195998574
+ ,1.47712125471966
+ ,2.44870631990508
+ ,5
+ ,5
+ ,5
+ ,'Mole'
+ ,-1.09691001300806
+ ,0.079181246047625
+ ,6.3
+ ,0.32221929473392
+ ,0.54406804435028
+ ,1.6232492903979
+ ,1
+ ,1
+ ,1
+ ,'Hedgehog'
+ ,-0.10237290870956
+ ,0.54406804435028
+ ,6.6
+ ,0.61278385671974
+ ,0.77815125038364
+ ,1.6232492903979
+ ,2
+ ,2
+ ,2
+ ,'Galago'
+ ,-0.69897000433602
+ ,0.69897000433602
+ ,9.5
+ ,0.079181246047625
+ ,1.01703333929878
+ ,2.07918124604762
+ ,2
+ ,2
+ ,2
+ ,'Goat'
+ ,1.44185217577329
+ ,2.06069784035361
+ ,3.3
+ ,-0.30102999566398
+ ,1.30102999566398
+ ,2.17026171539496
+ ,5
+ ,5
+ ,5
+ ,'Hamster'
+ ,-0.92081875395238
+ ,0
+ ,11
+ ,0.53147891704226
+ ,0.5910646070265
+ ,1.20411998265592
+ ,3
+ ,1
+ ,2
+ ,'Seal'
+ ,1.92941892571429
+ ,2.51188336097887
+ ,4.7
+ ,0.17609125905568
+ ,1.61278385671974
+ ,2.49136169383427
+ ,1
+ ,3
+ ,1
+ ,'Squirrel'
+ ,-1
+ ,0.60205999132796
+ ,10.4
+ ,0.53147891704226
+ ,0.95424250943932
+ ,1.44715803134222
+ ,5
+ ,1
+ ,3
+ ,'Guinea_pig'
+ ,0.01703333929878
+ ,0.74036268949424
+ ,7.4
+ ,-0.096910013008056
+ ,0.88081359228079
+ ,1.83250891270624
+ ,5
+ ,3
+ ,4
+ ,'Horse'
+ ,2.71683772329952
+ ,2.81624129999178
+ ,2.1
+ ,-0.096910013008056
+ ,1.66275783168157
+ ,2.52633927738984
+ ,5
+ ,5
+ ,5
+ ,'L.bat'
+ ,-2
+ ,-0.60205999132796
+ ,17.9
+ ,0.30102999566398
+ ,1.38021124171161
+ ,1.69897000433602
+ ,1
+ ,1
+ ,1
+ ,'Man'
+ ,1.79239168949825
+ ,3.12057393120585
+ ,6.1
+ ,0.27875360095283
+ ,2
+ ,2.42651126136458
+ ,1
+ ,1
+ ,1
+ ,'Mouse'
+ ,-1.69897000433602
+ ,-0.39794000867204
+ ,11.9
+ ,0.11394335230684
+ ,0.50514997831991
+ ,1.27875360095283
+ ,4
+ ,1
+ ,3
+ ,'N.opossum'
+ ,0.23044892137827
+ ,0.79934054945358
+ ,13.8
+ ,0.7481880270062
+ ,0.69897000433602
+ ,1.07918124604762
+ ,2
+ ,1
+ ,1
+ ,'Armadillo'
+ ,0.54406804435028
+ ,1.03342375548695
+ ,14.3
+ ,0.49136169383427
+ ,0.81291335664286
+ ,2.07918124604762
+ ,2
+ ,1
+ ,1
+ ,'O.monkey'
+ ,-0.31875876262441
+ ,1.19033169817029
+ ,15.2
+ ,0.25527250510331
+ ,1.07918124604762
+ ,2.14612803567824
+ ,2
+ ,2
+ ,2
+ ,'Patas'
+ ,1
+ ,2.06069784035361
+ ,10
+ ,-0.045757490560675
+ ,1.30535136944662
+ ,2.23044892137827
+ ,4
+ ,4
+ ,4
+ ,'Phalanger'
+ ,0.20951501454263
+ ,1.05690485133647
+ ,11.9
+ ,0.25527250510331
+ ,1.11394335230684
+ ,1.23044892137827
+ ,2
+ ,1
+ ,2
+ ,'Pig'
+ ,2.28330122870355
+ ,2.25527250510331
+ ,6.5
+ ,0.27875360095283
+ ,1.43136376415899
+ ,2.06069784035361
+ ,4
+ ,4
+ ,4
+ ,'Rabbit'
+ ,0.39794000867204
+ ,1.08278537031645
+ ,7.5
+ ,-0.045757490560675
+ ,1.25527250510331
+ ,1.49136169383427
+ ,5
+ ,5
+ ,5
+ ,'Rat'
+ ,-0.55284196865778
+ ,0.27875360095283
+ ,10.6
+ ,0.41497334797082
+ ,0.67209785793572
+ ,1.32221929473392
+ ,3
+ ,1
+ ,3
+ ,'Fox'
+ ,0.62736585659273
+ ,1.70243053644553
+ ,7.4
+ ,0.38021124171161
+ ,0.99122607569249
+ ,1.7160033436348
+ ,1
+ ,1
+ ,1
+ ,'Rhesus'
+ ,0.83250891270624
+ ,2.25285303097989
+ ,8.4
+ ,0.079181246047625
+ ,1.46239799789896
+ ,2.2148438480477
+ ,2
+ ,3
+ ,2
+ ,'G.hyrax'
+ ,-0.1249387366083
+ ,1.0899051114394
+ ,5.7
+ ,-0.045757490560675
+ ,0.84509804001426
+ ,2.35218251811136
+ ,2
+ ,2
+ ,2
+ ,'R.hyrax'
+ ,0.55630250076729
+ ,1.32221929473392
+ ,4.9
+ ,-0.30102999566398
+ ,0.77815125038364
+ ,2.35218251811136
+ ,3
+ ,2
+ ,3
+ ,'Sheep'
+ ,1.74429298312268
+ ,2.24303804868629
+ ,3.2
+ ,-0.22184874961636
+ ,1.30102999566398
+ ,2.17897694729317
+ ,5
+ ,5
+ ,5
+ ,'Tenrec'
+ ,-0.045757490560675
+ ,0.41497334797082
+ ,11
+ ,0.36172783601759
+ ,0.65321251377534
+ ,1.77815125038364
+ ,2
+ ,1
+ ,2
+ ,'T.hyrax'
+ ,0.30102999566398
+ ,1.0899051114394
+ ,4.9
+ ,-0.30102999566398
+ ,0.8750612633917
+ ,2.30102999566398
+ ,3
+ ,1
+ ,3
+ ,'Tree_shrew'
+ ,-1
+ ,0.39794000867204
+ ,13.2
+ ,0.41497334797082
+ ,0.36172783601759
+ ,1.66275783168157
+ ,3
+ ,2
+ ,2
+ ,'Vervet'
+ ,0.6222140229663
+ ,1.76342799356294
+ ,9.7
+ ,-0.22184874961636
+ ,1.38021124171161
+ ,2.32221929473392
+ ,4
+ ,3
+ ,4
+ ,'L.opossum'
+ ,0.54406804435028
+ ,0.5910646070265
+ ,12.8
+ ,0.81954393554187
+ ,0.47712125471966
+ ,1.14612803567824
+ ,2
+ ,1
+ ,1)
+ ,dim=c(10
+ ,39)
+ ,dimnames=list(c('label'
+ ,'logWb'
+ ,'logWbr'
+ ,'SWS'
+ ,'logPS'
+ ,'logL'
+ ,'logtg'
+ ,'P'
+ ,'S'
+ ,'D')
+ ,1:39))
>  y <- array(NA,dim=c(10,39),dimnames=list(c('label','logWb','logWbr','SWS','logPS','logL','logtg','P','S','D'),1:39))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
There were 39 warnings (use warnings() to see them)
> par1 = '2'
> par1 <- '2'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Patrick Wessa
> #To cite this work: Wessa P., 2010, Factor Analysis (v1.0.0) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_factor_analysis.wasp/
> #Source of accompanying publication: 
> #Technical description: 
> 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
                 logWb      logWbr  SWS       logPS      logL    logtg P S D
A.rat       0.00000000  0.81954394  6.3  0.30103000 0.6532125 1.623249 3 1 3
Elephant    3.40602894  3.66304097  2.1  0.25527251 1.8388491 2.795185 3 5 4
Baboon      1.02325246  2.25406445  9.1 -0.15490196 1.4313638 2.255273 4 4 4
B.bat      -1.69897000 -0.52287875 15.8  0.59106461 1.2787536 1.544068 1 1 1
Tapir       2.20411998  2.22788670  5.2  0.00000000 1.4828736 2.593286 4 5 4
Cat         0.51851394  1.40823997 10.9  0.55630250 1.4471580 1.799341 1 2 1
Chimp       1.71733758  2.64345268  8.3  0.14612804 1.6989700 2.361728 1 1 1
Chinchilla -0.36653154  0.80617997 11.0  0.17609126 0.8450980 2.049218 5 4 4
Cow         2.66745295  2.62634037  3.2 -0.15490196 1.4771213 2.448706 5 5 5
Mole       -1.09691001  0.07918125  6.3  0.32221929 0.5440680 1.623249 1 1 1
Hedgehog   -0.10237291  0.54406804  6.6  0.61278386 0.7781513 1.623249 2 2 2
Galago     -0.69897000  0.69897000  9.5  0.07918125 1.0170333 2.079181 2 2 2
Goat        1.44185218  2.06069784  3.3 -0.30103000 1.3010300 2.170262 5 5 5
Hamster    -0.92081875  0.00000000 11.0  0.53147892 0.5910646 1.204120 3 1 2
Seal        1.92941893  2.51188336  4.7  0.17609126 1.6127839 2.491362 1 3 1
Squirrel   -1.00000000  0.60205999 10.4  0.53147892 0.9542425 1.447158 5 1 3
Guinea_pig  0.01703334  0.74036269  7.4 -0.09691001 0.8808136 1.832509 5 3 4
Horse       2.71683772  2.81624130  2.1 -0.09691001 1.6627578 2.526339 5 5 5
L.bat      -2.00000000 -0.60205999 17.9  0.30103000 1.3802112 1.698970 1 1 1
Man         1.79239169  3.12057393  6.1  0.27875360 2.0000000 2.426511 1 1 1
Mouse      -1.69897000 -0.39794001 11.9  0.11394335 0.5051500 1.278754 4 1 3
N.opossum   0.23044892  0.79934055 13.8  0.74818803 0.6989700 1.079181 2 1 1
Armadillo   0.54406804  1.03342376 14.3  0.49136169 0.8129134 2.079181 2 1 1
O.monkey   -0.31875876  1.19033170 15.2  0.25527251 1.0791812 2.146128 2 2 2
Patas       1.00000000  2.06069784 10.0 -0.04575749 1.3053514 2.230449 4 4 4
Phalanger   0.20951501  1.05690485 11.9  0.25527251 1.1139434 1.230449 2 1 2
Pig         2.28330123  2.25527251  6.5  0.27875360 1.4313638 2.060698 4 4 4
Rabbit      0.39794001  1.08278537  7.5 -0.04575749 1.2552725 1.491362 5 5 5
Rat        -0.55284197  0.27875360 10.6  0.41497335 0.6720979 1.322219 3 1 3
Fox         0.62736586  1.70243054  7.4  0.38021124 0.9912261 1.716003 1 1 1
Rhesus      0.83250891  2.25285303  8.4  0.07918125 1.4623980 2.214844 2 3 2
G.hyrax    -0.12493874  1.08990511  5.7 -0.04575749 0.8450980 2.352183 2 2 2
R.hyrax     0.55630250  1.32221929  4.9 -0.30103000 0.7781513 2.352183 3 2 3
Sheep       1.74429298  2.24303805  3.2 -0.22184875 1.3010300 2.178977 5 5 5
Tenrec     -0.04575749  0.41497335 11.0  0.36172784 0.6532125 1.778151 2 1 2
T.hyrax     0.30103000  1.08990511  4.9 -0.30103000 0.8750613 2.301030 3 1 3
Tree_shrew -1.00000000  0.39794001 13.2  0.41497335 0.3617278 1.662758 3 2 2
Vervet      0.62221402  1.76342799  9.7 -0.22184875 1.3802112 2.322219 4 3 4
L.opossum   0.54406804  0.59106461 12.8  0.81954394 0.4771213 1.146128 2 1 1
> fit <- principal(y, nfactors=par1, rotate='varimax')
> fit
Principal Components Analysis
Call: principal(r = y, nfactors = par1, rotate = "varimax")
       item   RC1   RC2   h2   u2
logWb     1  0.88       0.84 0.16
logWbr    2  0.94       0.92 0.08
SWS       3 -0.63 -0.48 0.63 0.37
logPS     4 -0.40 -0.69 0.63 0.37
logL      5  0.86       0.74 0.26
logtg     6  0.85       0.77 0.23
P         7        0.96 0.92 0.08
S         8  0.52  0.74 0.82 0.18
D         9        0.96 0.97 0.03

                RC1  RC2
SS loadings    3.98 3.25
Proportion Var 0.44 0.36
Cumulative Var 0.44 0.80

Test of the hypothesis that 2 factors are sufficient.

The degrees of freedom for the null model are  36  and the objective function was  11.19
The degrees of freedom for the model are 19  and the objective function was  2.14 
The number of observations was  39  with Chi Square =  70.14  with prob <  8.7e-08 

Fit based upon off diagonal values = 0.99> fs <- factor.scores(y,fit)
> fs
                   RC1         RC2
A.rat      -0.67333412  0.14430791
Elephant    2.27195211  0.13577555
Baboon      0.54722538  0.81740962
B.bat      -0.87752649 -1.31250154
Tapir       1.11503374  0.82177474
Cat         0.47115336 -1.38509192
Chimp       1.54628278 -1.47853951
Chinchilla -0.78649138  1.21491197
Cow         1.09697959  1.45498884
Mole       -0.74835419 -0.76792559
Hedgehog   -0.47518895 -0.47814383
Galago     -0.22624044 -0.29629280
Goat        0.45910187  1.73678501
Hamster    -1.39921415 -0.18592978
Seal        1.72646978 -1.14806693
Squirrel   -1.19537030  0.41799514
Guinea_pig -0.72353315  1.34686071
Horse       1.35216258  1.34881334
L.bat      -0.86369879 -1.19176621
Man         1.98372192 -1.67485751
Mouse      -1.88251200  0.68079595
N.opossum  -0.86089718 -1.03896124
Armadillo  -0.15725699 -1.05886992
O.monkey   -0.13487541 -0.61472110
Patas       0.36353005  0.78668537
Phalanger  -0.44108361 -0.59411190
Pig         0.75189386  0.54846034
Rabbit     -0.51369283  1.68980627
Rat        -1.20005054  0.07225323
Fox         0.31089681 -1.18822762
Rhesus      0.89710111 -0.49318534
G.hyrax     0.13352292 -0.16060969
R.hyrax     0.11244367  0.52563110
Sheep       0.56877200  1.65761291
Tenrec     -0.65810209 -0.49430045
T.hyrax     0.01504164  0.39648269
Tree_shrew -1.26532417 -0.02454352
Vervet      0.30023560  0.78454344
L.opossum  -0.94077399 -0.99524773
> postscript(file="/var/www/html/rcomp/tmp/1eny01269171591.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> fa.diagram(fit)
> dev.off()
null device 
          1 
> postscript(file="/var/www/html/rcomp/tmp/20uq91269171591.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(fs,pch=20)
> text(fs,labels=rownames(y),pos=3)
> dev.off()
null device 
          1 
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/rcomp/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="/var/www/html/rcomp/tmp/38f6o1269171591.tab") 
> 
> try(system("convert tmp/1eny01269171591.ps tmp/1eny01269171591.png",intern=TRUE))
character(0)
> try(system("convert tmp/20uq91269171591.ps tmp/20uq91269171591.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.617   0.326   0.753