R version 2.15.2 (2012-10-26) -- "Trick or Treat"
Copyright (C) 2012 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i686-pc-linux-gnu (32-bit)

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Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.

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+ ,1141
+ ,104838
+ ,49
+ ,1
+ ,46
+ ,16
+ ,63
+ ,29236
+ ,5930
+ ,44
+ ,42
+ ,680
+ ,62215
+ ,27
+ ,0
+ ,24
+ ,10
+ ,40
+ ,19546
+ ,3710
+ ,26
+ ,26
+ ,1090
+ ,69304
+ ,30
+ ,6
+ ,40
+ ,19
+ ,69
+ ,22818
+ ,705
+ ,21
+ ,21
+ ,616
+ ,53117
+ ,22
+ ,3
+ ,3
+ ,12
+ ,48
+ ,32689
+ ,443
+ ,4
+ ,4
+ ,285
+ ,19764
+ ,12
+ ,1
+ ,10
+ ,2
+ ,8
+ ,5752
+ ,2416
+ ,10
+ ,10
+ ,1145
+ ,86680
+ ,31
+ ,2
+ ,37
+ ,14
+ ,52
+ ,22197
+ ,7747
+ ,43
+ ,43
+ ,733
+ ,84105
+ ,20
+ ,0
+ ,17
+ ,17
+ ,66
+ ,20055
+ ,5432
+ ,34
+ ,34
+ ,888
+ ,77945
+ ,20
+ ,0
+ ,28
+ ,19
+ ,76
+ ,25272
+ ,4913
+ ,32
+ ,31
+ ,849
+ ,89113
+ ,39
+ ,0
+ ,19
+ ,14
+ ,43
+ ,82206
+ ,2650
+ ,20
+ ,19
+ ,1182
+ ,91005
+ ,29
+ ,3
+ ,29
+ ,11
+ ,39
+ ,32073
+ ,2370
+ ,34
+ ,34
+ ,528
+ ,40248
+ ,16
+ ,1
+ ,8
+ ,4
+ ,14
+ ,5444
+ ,775
+ ,6
+ ,6
+ ,642
+ ,64187
+ ,27
+ ,0
+ ,10
+ ,16
+ ,61
+ ,20154
+ ,5576
+ ,12
+ ,11
+ ,947
+ ,50857
+ ,21
+ ,0
+ ,15
+ ,20
+ ,71
+ ,36944
+ ,1352
+ ,24
+ ,24
+ ,819
+ ,56613
+ ,19
+ ,1
+ ,15
+ ,12
+ ,44
+ ,8019
+ ,3080
+ ,16
+ ,16
+ ,757
+ ,62792
+ ,35
+ ,0
+ ,28
+ ,15
+ ,60
+ ,30884
+ ,10205
+ ,72
+ ,72
+ ,894
+ ,72535
+ ,14
+ ,0
+ ,17
+ ,16
+ ,64
+ ,19540
+ ,6095
+ ,27
+ ,21)
+ ,dim=c(11
+ ,289)
+ ,dimnames=list(c('pageviews'
+ ,'time_in_rfc'
+ ,'logins'
+ ,'shared_compendiums'
+ ,'blogged_computations'
+ ,'compendiums_reviewed'
+ ,'feedback_messages_p1'
+ ,'totsize'
+ ,'totrevisions'
+ ,'tothyperlinks'
+ ,'totblogs')
+ ,1:289))
>  y <- array(NA,dim=c(11,289),dimnames=list(c('pageviews','time_in_rfc','logins','shared_compendiums','blogged_computations','compendiums_reviewed','feedback_messages_p1','totsize','totrevisions','tothyperlinks','totblogs'),1:289))
>  for (i in 1:dim(x)[1])
+  {
+  	for (j in 1:dim(x)[2])
+  	{
+  		y[i,j] <- as.numeric(x[i,j])
+  	}
+  }
> par4 = 'no'
> par3 = '3'
> par2 = 'none'
> par1 = '1'
> library(party)
Loading required package: survival
Loading required package: splines
Loading required package: grid
Loading required package: modeltools
Loading required package: stats4
Loading required package: coin
Loading required package: mvtnorm
Loading required package: zoo

Attaching package: 'zoo'

The following object(s) are masked from 'package:base':

    as.Date, as.Date.numeric

Loading required package: sandwich
Loading required package: strucchange
Loading required package: vcd
Loading required package: MASS
Loading required package: colorspace
> library(Hmisc)
Hmisc library by Frank E Harrell Jr

Type library(help='Hmisc'), ?Overview, or ?Hmisc.Overview')
to see overall documentation.

NOTE:Hmisc no longer redefines [.factor to drop unused levels when
subsetting.  To get the old behavior of Hmisc type dropUnusedLevels().


Attaching package: 'Hmisc'

The following object(s) are masked from 'package:survival':

    untangle.specials

The following object(s) are masked from 'package:base':

    format.pval, round.POSIXt, trunc.POSIXt, units

> par1 <- as.numeric(par1)
> par3 <- as.numeric(par3)
> x <- data.frame(t(y))
> is.data.frame(x)
[1] TRUE
> x <- x[!is.na(x[,par1]),]
> k <- length(x[1,])
> n <- length(x[,1])
> colnames(x)[par1]
[1] "pageviews"
> x[,par1]
  [1] 1418  869 1530 2172  901  463 3201  371 1192 1583 1439 1764 1495 1373 2187
 [16] 1491 4041 1706 2152 1036 1882 1929 2242 1220 1289 2515 2147 2352 1638 1222
 [31] 1812 1677 1579 1731  807 2452  829 1940 2662  186 1499  865 1793 2527 2747
 [46] 1324 2702 1383 1179 2099 4308  918 1831 3373 1713 1438  496 2253  744 1161
 [61] 2352 2144 4691 1112 2694 1973 1769 3148 2474 2084 1954 1226 1389 1496 2269
 [76] 1833 1268 1943  893 1762 1403 1425 1857 1840 1502 1441 1420 1416 2970 1317
 [91] 1644  870 1654 1054  937 3004 2008 2547 1885 1626 1468 2445 1964 1381 1369
[106] 1659 2888 1290 2845 1982 1904 1391  602 1743 1559 2014 2143 2146  874 1590
[121] 1590 1210 2072 1281 1401  834 1105 1272 1944  391  761 1605  530 1988 1386
[136] 2395  387 1742  620  449  800 1684 1050 2699 1606 1502 1204 1138  568 1459
[151] 2158 1111 1421 2833 1955 2922 1002 1060  956 2186 3604 1035 1417 3261 1587
[166] 1424 1701 1249  946 1926 3352 1641 2035 2312 1369 1577 2201  961 1900 1254
[181] 1335 1597  207 1645 2429  151  474  141 1639  872 1318 1018 1383 1314 1335
[196] 1403  910  616 1407  771  766  473 1376 1232 1521  572 1059 1544 1230 1206
[211] 1205 1255  613  721 1109  740 1126  728  689  592  995 1613 2048  705  301
[226] 1803  799  861 1186 1451  628 1161 1463  742  979  675 1241  676 1049  620
[241] 1081 1688  736  617  812 1051 1656  705  945  554 1597  982  222 1212 1143
[256]  435  532  882  608  459  578  826  509  717  637  857  830  652  707  954
[271] 1461  672  778 1141  680 1090  616  285 1145  733  888  849 1182  528  642
[286]  947  819  757  894
> if (par2 == 'kmeans') {
+ cl <- kmeans(x[,par1], par3)
+ print(cl)
+ clm <- matrix(cbind(cl$centers,1:par3),ncol=2)
+ clm <- clm[sort.list(clm[,1]),]
+ for (i in 1:par3) {
+ cl$cluster[cl$cluster==clm[i,2]] <- paste('C',i,sep='')
+ }
+ cl$cluster <- as.factor(cl$cluster)
+ print(cl$cluster)
+ x[,par1] <- cl$cluster
+ }
> if (par2 == 'quantiles') {
+ x[,par1] <- cut2(x[,par1],g=par3)
+ }
> if (par2 == 'hclust') {
+ hc <- hclust(dist(x[,par1])^2, 'cen')
+ print(hc)
+ memb <- cutree(hc, k = par3)
+ dum <- c(mean(x[memb==1,par1]))
+ for (i in 2:par3) {
+ dum <- c(dum, mean(x[memb==i,par1]))
+ }
+ hcm <- matrix(cbind(dum,1:par3),ncol=2)
+ hcm <- hcm[sort.list(hcm[,1]),]
+ for (i in 1:par3) {
+ memb[memb==hcm[i,2]] <- paste('C',i,sep='')
+ }
+ memb <- as.factor(memb)
+ print(memb)
+ x[,par1] <- memb
+ }
> if (par2=='equal') {
+ ed <- cut(as.numeric(x[,par1]),par3,labels=paste('C',1:par3,sep=''))
+ x[,par1] <- as.factor(ed)
+ }
> table(x[,par1])

 141  151  186  207  222  285  301  371  387  391  435  449  459  463  473  474 
   1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1 
 496  509  528  530  532  554  568  572  578  592  602  608  613  616  617  620 
   1    1    1    1    1    1    1    1    1    1    1    1    1    2    1    2 
 628  637  642  652  672  675  676  680  689  705  707  717  721  728  733  736 
   1    1    1    1    1    1    1    1    1    2    1    1    1    1    1    1 
 740  742  744  757  761  766  771  778  799  800  807  812  819  826  829  830 
   1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1 
 834  849  857  861  865  869  870  872  874  882  888  893  894  901  910  918 
   1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1 
 937  945  946  947  954  956  961  979  982  995 1002 1018 1035 1036 1049 1050 
   1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1 
1051 1054 1059 1060 1081 1090 1105 1109 1111 1112 1126 1138 1141 1143 1145 1161 
   1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    2 
1179 1182 1186 1192 1204 1205 1206 1210 1212 1220 1222 1226 1230 1232 1241 1249 
   1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1 
1254 1255 1268 1272 1281 1289 1290 1314 1317 1318 1324 1335 1369 1373 1376 1381 
   1    1    1    1    1    1    1    1    1    1    1    2    2    1    1    1 
1383 1386 1389 1391 1401 1403 1407 1416 1417 1418 1420 1421 1424 1425 1438 1439 
   2    1    1    1    1    2    1    1    1    1    1    1    1    1    1    1 
1441 1451 1459 1461 1463 1468 1491 1495 1496 1499 1502 1521 1530 1544 1559 1577 
   1    1    1    1    1    1    1    1    1    1    2    1    1    1    1    1 
1579 1583 1587 1590 1597 1605 1606 1613 1626 1638 1639 1641 1644 1645 1654 1656 
   1    1    1    2    2    1    1    1    1    1    1    1    1    1    1    1 
1659 1677 1684 1688 1701 1706 1713 1731 1742 1743 1762 1764 1769 1793 1803 1812 
   1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1 
1831 1833 1840 1857 1882 1885 1900 1904 1926 1929 1940 1943 1944 1954 1955 1964 
   1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1 
1973 1982 1988 2008 2014 2035 2048 2072 2084 2099 2143 2144 2146 2147 2152 2158 
   1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1 
2172 2186 2187 2201 2242 2253 2269 2312 2352 2395 2429 2445 2452 2474 2515 2527 
   1    1    1    1    1    1    1    1    2    1    1    1    1    1    1    1 
2547 2662 2694 2699 2702 2747 2833 2845 2888 2922 2970 3004 3148 3201 3261 3352 
   1    1    1    1    1    1    1    1    1    1    1    1    1    1    1    1 
3373 3604 4041 4308 4691 
   1    1    1    1    1 
> colnames(x)
 [1] "pageviews"            "time_in_rfc"          "logins"              
 [4] "shared_compendiums"   "blogged_computations" "compendiums_reviewed"
 [7] "feedback_messages_p1" "totsize"              "totrevisions"        
[10] "tothyperlinks"        "totblogs"            
> colnames(x)[par1]
[1] "pageviews"
> x[,par1]
  [1] 1418  869 1530 2172  901  463 3201  371 1192 1583 1439 1764 1495 1373 2187
 [16] 1491 4041 1706 2152 1036 1882 1929 2242 1220 1289 2515 2147 2352 1638 1222
 [31] 1812 1677 1579 1731  807 2452  829 1940 2662  186 1499  865 1793 2527 2747
 [46] 1324 2702 1383 1179 2099 4308  918 1831 3373 1713 1438  496 2253  744 1161
 [61] 2352 2144 4691 1112 2694 1973 1769 3148 2474 2084 1954 1226 1389 1496 2269
 [76] 1833 1268 1943  893 1762 1403 1425 1857 1840 1502 1441 1420 1416 2970 1317
 [91] 1644  870 1654 1054  937 3004 2008 2547 1885 1626 1468 2445 1964 1381 1369
[106] 1659 2888 1290 2845 1982 1904 1391  602 1743 1559 2014 2143 2146  874 1590
[121] 1590 1210 2072 1281 1401  834 1105 1272 1944  391  761 1605  530 1988 1386
[136] 2395  387 1742  620  449  800 1684 1050 2699 1606 1502 1204 1138  568 1459
[151] 2158 1111 1421 2833 1955 2922 1002 1060  956 2186 3604 1035 1417 3261 1587
[166] 1424 1701 1249  946 1926 3352 1641 2035 2312 1369 1577 2201  961 1900 1254
[181] 1335 1597  207 1645 2429  151  474  141 1639  872 1318 1018 1383 1314 1335
[196] 1403  910  616 1407  771  766  473 1376 1232 1521  572 1059 1544 1230 1206
[211] 1205 1255  613  721 1109  740 1126  728  689  592  995 1613 2048  705  301
[226] 1803  799  861 1186 1451  628 1161 1463  742  979  675 1241  676 1049  620
[241] 1081 1688  736  617  812 1051 1656  705  945  554 1597  982  222 1212 1143
[256]  435  532  882  608  459  578  826  509  717  637  857  830  652  707  954
[271] 1461  672  778 1141  680 1090  616  285 1145  733  888  849 1182  528  642
[286]  947  819  757  894
> if (par2 == 'none') {
+ m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
+ }
> 
> #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/fisher/rcomp/createtable")
> 
> if (par2 != 'none') {
+ m <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data = x)
+ if (par4=='yes') {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'10-Fold Cross Validation',3+2*par3,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'',1,TRUE)
+ a<-table.element(a,'Prediction (training)',par3+1,TRUE)
+ a<-table.element(a,'Prediction (testing)',par3+1,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Actual',1,TRUE)
+ for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
+ a<-table.element(a,'CV',1,TRUE)
+ for (jjj in 1:par3) a<-table.element(a,paste('C',jjj,sep=''),1,TRUE)
+ a<-table.element(a,'CV',1,TRUE)
+ a<-table.row.end(a)
+ for (i in 1:10) {
+ ind <- sample(2, nrow(x), replace=T, prob=c(0.9,0.1))
+ m.ct <- ctree(as.formula(paste('as.factor(',colnames(x)[par1],') ~ .',sep='')),data =x[ind==1,])
+ if (i==1) {
+ m.ct.i.pred <- predict(m.ct, newdata=x[ind==1,])
+ m.ct.i.actu <- x[ind==1,par1]
+ m.ct.x.pred <- predict(m.ct, newdata=x[ind==2,])
+ m.ct.x.actu <- x[ind==2,par1]
+ } else {
+ m.ct.i.pred <- c(m.ct.i.pred,predict(m.ct, newdata=x[ind==1,]))
+ m.ct.i.actu <- c(m.ct.i.actu,x[ind==1,par1])
+ m.ct.x.pred <- c(m.ct.x.pred,predict(m.ct, newdata=x[ind==2,]))
+ m.ct.x.actu <- c(m.ct.x.actu,x[ind==2,par1])
+ }
+ }
+ print(m.ct.i.tab <- table(m.ct.i.actu,m.ct.i.pred))
+ numer <- 0
+ for (i in 1:par3) {
+ print(m.ct.i.tab[i,i] / sum(m.ct.i.tab[i,]))
+ numer <- numer + m.ct.i.tab[i,i]
+ }
+ print(m.ct.i.cp <- numer / sum(m.ct.i.tab))
+ print(m.ct.x.tab <- table(m.ct.x.actu,m.ct.x.pred))
+ numer <- 0
+ for (i in 1:par3) {
+ print(m.ct.x.tab[i,i] / sum(m.ct.x.tab[i,]))
+ numer <- numer + m.ct.x.tab[i,i]
+ }
+ print(m.ct.x.cp <- numer / sum(m.ct.x.tab))
+ for (i in 1:par3) {
+ a<-table.row.start(a)
+ a<-table.element(a,paste('C',i,sep=''),1,TRUE)
+ for (jjj in 1:par3) a<-table.element(a,m.ct.i.tab[i,jjj])
+ a<-table.element(a,round(m.ct.i.tab[i,i]/sum(m.ct.i.tab[i,]),4))
+ for (jjj in 1:par3) a<-table.element(a,m.ct.x.tab[i,jjj])
+ a<-table.element(a,round(m.ct.x.tab[i,i]/sum(m.ct.x.tab[i,]),4))
+ a<-table.row.end(a)
+ }
+ a<-table.row.start(a)
+ a<-table.element(a,'Overall',1,TRUE)
+ for (jjj in 1:par3) a<-table.element(a,'-')
+ a<-table.element(a,round(m.ct.i.cp,4))
+ for (jjj in 1:par3) a<-table.element(a,'-')
+ a<-table.element(a,round(m.ct.x.cp,4))
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/fisher/rcomp/tmp/1youp1354796892.tab") 
+ }
+ }
> m

	 Conditional inference tree with 13 terminal nodes

Response:  pageviews 
Inputs:  time_in_rfc, logins, shared_compendiums, blogged_computations, compendiums_reviewed, feedback_messages_p1, totsize, totrevisions, tothyperlinks, totblogs 
Number of observations:  289 

1) time_in_rfc <= 172494; criterion = 1, statistic = 229.566
  2) time_in_rfc <= 73566; criterion = 1, statistic = 119.407
    3) time_in_rfc <= 40248; criterion = 1, statistic = 38.822
      4) time_in_rfc <= 21054; criterion = 0.996, statistic = 12.464
        5)*  weights = 7 
      4) time_in_rfc > 21054
        6)*  weights = 16 
    3) time_in_rfc > 40248
      7) logins <= 28; criterion = 0.989, statistic = 10.566
        8)*  weights = 23 
      7) logins > 28
        9)*  weights = 24 
  2) time_in_rfc > 73566
    10) logins <= 53; criterion = 1, statistic = 32.648
      11) time_in_rfc <= 119308; criterion = 1, statistic = 24.285
        12) tothyperlinks <= 23; criterion = 0.965, statistic = 8.5
          13)*  weights = 11 
        12) tothyperlinks > 23
          14)*  weights = 41 
      11) time_in_rfc > 119308
        15)*  weights = 30 
    10) logins > 53
      16) blogged_computations <= 33; criterion = 0.954, statistic = 7.974
        17)*  weights = 15 
      16) blogged_computations > 33
        18)*  weights = 31 
1) time_in_rfc > 172494
  19) time_in_rfc <= 275541; criterion = 1, statistic = 49.714
    20) logins <= 88; criterion = 1, statistic = 17.156
      21) time_in_rfc <= 210907; criterion = 0.999, statistic = 14.509
        22)*  weights = 29 
      21) time_in_rfc > 210907
        23)*  weights = 27 
    20) logins > 88
      24)*  weights = 16 
  19) time_in_rfc > 275541
    25)*  weights = 19 
> postscript(file="/var/fisher/rcomp/tmp/2kamg1354796892.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(m)
> dev.off()
null device 
          1 
> postscript(file="/var/fisher/rcomp/tmp/3u29q1354796892.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(x[,par1] ~ as.factor(where(m)),main='Response by Terminal Node',xlab='Terminal Node',ylab='Response')
> dev.off()
null device 
          1 
> if (par2 == 'none') {
+ forec <- predict(m)
+ result <- as.data.frame(cbind(x[,par1],forec,x[,par1]-forec))
+ colnames(result) <- c('Actuals','Forecasts','Residuals')
+ print(result)
+ }
    Actuals Forecasts    Residuals
1      1418 1695.2414 -277.2413793
2       869 1595.3226 -726.3225806
3      1530 1695.2414 -165.2413793
4      2172 2385.0625 -213.0625000
5       901 1335.9333 -434.9333333
6       463  669.7391 -206.7391304
7      3201 3134.5789   66.4210526
8       371  502.4375 -131.4375000
9      1192 1326.4667 -134.4666667
10     1583 1335.9333  247.0666667
11     1439 1335.9333  103.0666667
12     1764 1981.9259 -217.9259259
13     1495 1695.2414 -200.2413793
14     1373 1595.3226 -222.3225806
15     2187 1981.9259  205.0740741
16     1491 1695.2414 -204.2413793
17     4041 3134.5789  906.4210526
18     1706 1981.9259 -275.9259259
19     2152 2385.0625 -233.0625000
20     1036 1335.9333 -299.9333333
21     1882 1695.2414  186.7586207
22     1929 1981.9259  -52.9259259
23     2242 3134.5789 -892.5789474
24     1220 1335.9333 -115.9333333
25     1289 1335.9333  -46.9333333
26     2515 2385.0625  129.9375000
27     2147 2385.0625 -238.0625000
28     2352 2385.0625  -33.0625000
29     1638 1981.9259 -343.9259259
30     1222 1335.9333 -113.9333333
31     1812 1981.9259 -169.9259259
32     1677 1695.2414  -18.2413793
33     1579 1595.3226  -16.3225806
34     1731 1981.9259 -250.9259259
35      807 1076.3171 -269.3170732
36     2452 3134.5789 -682.5789474
37      829 1076.3171 -247.3170732
38     1940 1981.9259  -41.9259259
39     2662 3134.5789 -472.5789474
40      186  225.5714  -39.5714286
41     1499 1595.3226  -96.3225806
42      865 1076.3171 -211.3170732
43     1793 1595.3226  197.6774194
44     2527 2385.0625  141.9375000
45     2747 1981.9259  765.0740741
46     1324 1595.3226 -271.3225806
47     2702 2385.0625  316.9375000
48     1383 1595.3226 -212.3225806
49     1179 1076.3171  102.6829268
50     2099 1595.3226  503.6774194
51     4308 3134.5789 1173.4210526
52      918  873.0000   45.0000000
53     1831 1695.2414  135.7586207
54     3373 3134.5789  238.4210526
55     1713 1335.9333  377.0666667
56     1438 1595.3226 -157.3225806
57      496  502.4375   -6.4375000
58     2253 3134.5789 -881.5789474
59      744  669.7391   74.2608696
60     1161 1326.4667 -165.4666667
61     2352 1981.9259  370.0740741
62     2144 1981.9259  162.0740741
63     4691 3134.5789 1556.4210526
64     1112 1076.3171   35.6829268
65     2694 2385.0625  308.9375000
66     1973 2385.0625 -412.0625000
67     1769 1695.2414   73.7586207
68     3148 3134.5789   13.4210526
69     2474 2385.0625   88.9375000
70     2084 1695.2414  388.7586207
71     1954 1695.2414  258.7586207
72     1226 1695.2414 -469.2413793
73     1389 1695.2414 -306.2413793
74     1496 1595.3226  -99.3225806
75     2269 2385.0625 -116.0625000
76     1833 1695.2414  137.7586207
77     1268 1076.3171  191.6829268
78     1943 1695.2414  247.7586207
79      893  869.2083   23.7916667
80     1762 1695.2414   66.7586207
81     1403 1335.9333   67.0666667
82     1425 1335.9333   89.0666667
83     1857 1981.9259 -124.9259259
84     1840 1981.9259 -141.9259259
85     1502 1695.2414 -193.2413793
86     1441 1335.9333  105.0666667
87     1420 1335.9333   84.0666667
88     1416 1335.9333   80.0666667
89     2970 3134.5789 -164.5789474
90     1317 1326.4667   -9.4666667
91     1644 1695.2414  -51.2413793
92      870 1076.3171 -206.3170732
93     1654 1335.9333  318.0666667
94     1054 1335.9333 -281.9333333
95      937 1076.3171 -139.3170732
96     3004 3134.5789 -130.5789474
97     2008 1981.9259   26.0740741
98     2547 1595.3226  951.6774194
99     1885 1695.2414  189.7586207
100    1626 1695.2414  -69.2413793
101    1468 1335.9333  132.0666667
102    2445 1981.9259  463.0740741
103    1964 1981.9259  -17.9259259
104    1381 1335.9333   45.0666667
105    1369 1695.2414 -326.2413793
106    1659 1981.9259 -322.9259259
107    2888 2385.0625  502.9375000
108    1290 1076.3171  213.6829268
109    2845 3134.5789 -289.5789474
110    1982 2385.0625 -403.0625000
111    1904 1981.9259  -77.9259259
112    1391 1595.3226 -204.3225806
113     602  669.7391  -67.7391304
114    1743 1595.3226  147.6774194
115    1559 1595.3226  -36.3225806
116    2014 1695.2414  318.7586207
117    2143 1981.9259  161.0740741
118    2146 1981.9259  164.0740741
119     874 1076.3171 -202.3170732
120    1590 1595.3226   -5.3225806
121    1590 1595.3226   -5.3225806
122    1210  869.2083  340.7916667
123    2072 1595.3226  476.6774194
124    1281 1595.3226 -314.3225806
125    1401 1981.9259 -580.9259259
126     834 1076.3171 -242.3170732
127    1105 1076.3171   28.6829268
128    1272 1076.3171  195.6829268
129    1944 1981.9259  -37.9259259
130     391  502.4375 -111.4375000
131     761  869.2083 -108.2083333
132    1605 1595.3226    9.6774194
133     530  669.7391 -139.7391304
134    1988 1595.3226  392.6774194
135    1386 1335.9333   50.0666667
136    2395 3134.5789 -739.5789474
137     387  225.5714  161.4285714
138    1742 1695.2414   46.7586207
139     620  502.4375  117.5625000
140     449  502.4375  -53.4375000
141     800  869.2083  -69.2083333
142    1684 1595.3226   88.6774194
143    1050  873.0000  177.0000000
144    2699 2385.0625  313.9375000
145    1606 1695.2414  -89.2413793
146    1502 1076.3171  425.6829268
147    1204 1326.4667 -122.4666667
148    1138 1076.3171   61.6829268
149     568  502.4375   65.5625000
150    1459 1335.9333  123.0666667
151    2158 1981.9259  176.0740741
152    1111 1335.9333 -224.9333333
153    1421 1595.3226 -174.3225806
154    2833 3134.5789 -301.5789474
155    1955 1981.9259  -26.9259259
156    2922 3134.5789 -212.5789474
157    1002 1335.9333 -333.9333333
158    1060 1076.3171  -16.3170732
159     956 1076.3171 -120.3170732
160    2186 2385.0625 -199.0625000
161    3604 3134.5789  469.4210526
162    1035  873.0000  162.0000000
163    1417 1595.3226 -178.3225806
164    3261 3134.5789  126.4210526
165    1587 1595.3226   -8.3225806
166    1424 1695.2414 -271.2413793
167    1701 1595.3226  105.6774194
168    1249 1326.4667  -77.4666667
169     946 1595.3226 -649.3225806
170    1926 1981.9259  -55.9259259
171    3352 3134.5789  217.4210526
172    1641 1695.2414  -54.2413793
173    2035 1695.2414  339.7586207
174    2312 1981.9259  330.0740741
175    1369 1076.3171  292.6829268
176    1577 1335.9333  241.0666667
177    2201 1695.2414  505.7586207
178     961  873.0000   88.0000000
179    1900 1981.9259  -81.9259259
180    1254 1335.9333  -81.9333333
181    1335 1326.4667    8.5333333
182    1597 1595.3226    1.6774194
183     207  225.5714  -18.5714286
184    1645 1695.2414  -50.2413793
185    2429 2385.0625   43.9375000
186     151  225.5714  -74.5714286
187     474  669.7391 -195.7391304
188     141  225.5714  -84.5714286
189    1639 1335.9333  303.0666667
190     872  873.0000   -1.0000000
191    1318 1335.9333  -17.9333333
192    1018  873.0000  145.0000000
193    1383 1076.3171  306.6829268
194    1314  869.2083  444.7916667
195    1335 1335.9333   -0.9333333
196    1403 1076.3171  326.6829268
197     910  869.2083   40.7916667
198     616  669.7391  -53.7391304
199    1407 1326.4667   80.5333333
200     771  869.2083  -98.2083333
201     766 1326.4667 -560.4666667
202     473  669.7391 -196.7391304
203    1376 1595.3226 -219.3225806
204    1232 1326.4667  -94.4666667
205    1521 1076.3171  444.6829268
206     572  669.7391  -97.7391304
207    1059 1076.3171  -17.3170732
208    1544 1695.2414 -151.2413793
209    1230 1335.9333 -105.9333333
210    1206 1335.9333 -129.9333333
211    1205 1076.3171  128.6829268
212    1255 1335.9333  -80.9333333
213     613  669.7391  -56.7391304
214     721  873.0000 -152.0000000
215    1109  869.2083  239.7916667
216     740  669.7391   70.2608696
217    1126  869.2083  256.7916667
218     728  869.2083 -141.2083333
219     689  669.7391   19.2608696
220     592  873.0000 -281.0000000
221     995 1076.3171  -81.3170732
222    1613 1326.4667  286.5333333
223    2048 1595.3226  452.6774194
224     705  669.7391   35.2608696
225     301  502.4375 -201.4375000
226    1803 1595.3226  207.6774194
227     799  869.2083  -70.2083333
228     861  869.2083   -8.2083333
229    1186  869.2083  316.7916667
230    1451 1076.3171  374.6829268
231     628  502.4375  125.5625000
232    1161 1076.3171   84.6829268
233    1463 1326.4667  136.5333333
234     742  669.7391   72.2608696
235     979  869.2083  109.7916667
236     675  869.2083 -194.2083333
237    1241 1335.9333  -94.9333333
238     676  669.7391    6.2608696
239    1049 1076.3171  -27.3170732
240     620  502.4375  117.5625000
241    1081 1076.3171    4.6829268
242    1688 1326.4667  361.5333333
243     736  869.2083 -133.2083333
244     617  869.2083 -252.2083333
245     812  869.2083  -57.2083333
246    1051 1076.3171  -25.3170732
247    1656 1595.3226   60.6774194
248     705  873.0000 -168.0000000
249     945 1076.3171 -131.3170732
250     554  502.4375   51.5625000
251    1597 1326.4667  270.5333333
252     982 1076.3171  -94.3170732
253     222  225.5714   -3.5714286
254    1212 1326.4667 -114.4666667
255    1143 1076.3171   66.6829268
256     435  502.4375  -67.4375000
257     532  502.4375   29.5625000
258     882  873.0000    9.0000000
259     608  869.2083 -261.2083333
260     459  502.4375  -43.4375000
261     578  502.4375   75.5625000
262     826 1076.3171 -250.3170732
263     509  502.4375    6.5625000
264     717  669.7391   47.2608696
265     637  869.2083 -232.2083333
266     857 1076.3171 -219.3170732
267     830  869.2083  -39.2083333
268     652  869.2083 -217.2083333
269     707 1076.3171 -369.3170732
270     954 1076.3171 -122.3170732
271    1461 1326.4667  134.5333333
272     672  669.7391    2.2608696
273     778  669.7391  108.2608696
274    1141 1076.3171   64.6829268
275     680  669.7391   10.2608696
276    1090  869.2083  220.7916667
277     616  669.7391  -53.7391304
278     285  225.5714   59.4285714
279    1145 1076.3171   68.6829268
280     733 1076.3171 -343.3170732
281     888 1076.3171 -188.3170732
282     849  873.0000  -24.0000000
283    1182 1076.3171  105.6829268
284     528  502.4375   25.5625000
285     642  669.7391  -27.7391304
286     947  669.7391  277.2608696
287     819  669.7391  149.2608696
288     757  869.2083 -112.2083333
289     894  669.7391  224.2608696
> if (par2 != 'none') {
+ print(cbind(as.factor(x[,par1]),predict(m)))
+ myt <- table(as.factor(x[,par1]),predict(m))
+ print(myt)
+ }
> postscript(file="/var/fisher/rcomp/tmp/4m31z1354796892.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> if(par2=='none') {
+ op <- par(mfrow=c(2,2))
+ plot(density(result$Actuals),main='Kernel Density Plot of Actuals')
+ plot(density(result$Residuals),main='Kernel Density Plot of Residuals')
+ plot(result$Forecasts,result$Actuals,main='Actuals versus Predictions',xlab='Predictions',ylab='Actuals')
+ plot(density(result$Forecasts),main='Kernel Density Plot of Predictions')
+ par(op)
+ }
> if(par2!='none') {
+ plot(myt,main='Confusion Matrix',xlab='Actual',ylab='Predicted')
+ }
> dev.off()
null device 
          1 
> if (par2 == 'none') {
+ detcoef <- cor(result$Forecasts,result$Actuals)
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Goodness of Fit',2,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'Correlation',1,TRUE)
+ a<-table.element(a,round(detcoef,4))
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'R-squared',1,TRUE)
+ a<-table.element(a,round(detcoef*detcoef,4))
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'RMSE',1,TRUE)
+ a<-table.element(a,round(sqrt(mean((result$Residuals)^2)),4))
+ a<-table.row.end(a)
+ a<-table.end(a)
+ table.save(a,file="/var/fisher/rcomp/tmp/5laul1354796892.tab") 
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Actuals, Predictions, and Residuals',4,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'#',header=TRUE)
+ a<-table.element(a,'Actuals',header=TRUE)
+ a<-table.element(a,'Forecasts',header=TRUE)
+ a<-table.element(a,'Residuals',header=TRUE)
+ a<-table.row.end(a)
+ for (i in 1:length(result$Actuals)) {
+ a<-table.row.start(a)
+ a<-table.element(a,i,header=TRUE)
+ a<-table.element(a,result$Actuals[i])
+ a<-table.element(a,result$Forecasts[i])
+ a<-table.element(a,result$Residuals[i])
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/fisher/rcomp/tmp/6md8m1354796892.tab") 
+ }
> if (par2 != 'none') {
+ a<-table.start()
+ a<-table.row.start(a)
+ a<-table.element(a,'Confusion Matrix (predicted in columns / actuals in rows)',par3+1,TRUE)
+ a<-table.row.end(a)
+ a<-table.row.start(a)
+ a<-table.element(a,'',1,TRUE)
+ for (i in 1:par3) {
+ a<-table.element(a,paste('C',i,sep=''),1,TRUE)
+ }
+ a<-table.row.end(a)
+ for (i in 1:par3) {
+ a<-table.row.start(a)
+ a<-table.element(a,paste('C',i,sep=''),1,TRUE)
+ for (j in 1:par3) {
+ a<-table.element(a,myt[i,j])
+ }
+ a<-table.row.end(a)
+ }
+ a<-table.end(a)
+ table.save(a,file="/var/fisher/rcomp/tmp/7hi031354796892.tab") 
+ }
> 
> try(system("convert tmp/2kamg1354796892.ps tmp/2kamg1354796892.png",intern=TRUE))
character(0)
> try(system("convert tmp/3u29q1354796892.ps tmp/3u29q1354796892.png",intern=TRUE))
character(0)
> try(system("convert tmp/4m31z1354796892.ps tmp/4m31z1354796892.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  9.679   0.605  10.268