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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Type 'contributors()' for more information and
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Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- array(list(3.66356
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+ ,5.5
+ ,1.1
+ ,0.9
+ ,138
+ ,24
+ ,199
+ ,2.3979
+ ,7.10003
+ ,-4
+ ,5.8
+ ,-0.4
+ ,78.4
+ ,11
+ ,399
+ ,2.63906
+ ,7.65681
+ ,-0.2
+ ,2.4
+ ,0
+ ,41
+ ,19
+ ,157
+ ,2.56495
+ ,4.70953
+ ,-2.8
+ ,1.8
+ ,1.4
+ ,198.9
+ ,3
+ ,537
+ ,3.3322
+ ,5.60212
+ ,3.8
+ ,3.9
+ ,-0.2
+ ,85
+ ,5
+ ,187
+ ,2.56495
+ ,7.85127
+ ,0.2
+ ,2.8
+ ,0.1
+ ,78
+ ,17
+ ,112
+ ,3.68888
+ ,7.89655
+ ,12.8
+ ,6.8
+ ,-0.6
+ ,227.7
+ ,15
+ ,583
+ ,2.3979
+ ,7.20638
+ ,-0.8
+ ,1.6
+ ,1.7
+ ,192.6
+ ,22
+ ,469
+ ,2.3979
+ ,4.89035
+ ,-10.8
+ ,1.5
+ ,0.2
+ ,57
+ ,3
+ ,460
+ ,4.68213
+ ,7.56735
+ ,-10.2
+ ,0.6
+ ,2.4
+ ,110.8
+ ,10
+ ,465
+ ,3.04452
+ ,7.61135
+ ,0.8
+ ,3.1
+ ,-0.1
+ ,65.6
+ ,19
+ ,429
+ ,3.04452
+ ,6.66823
+ ,4.1
+ ,1.4
+ ,0.2
+ ,139.8
+ ,24
+ ,572
+ ,2.19722
+ ,5.0689
+ ,4.3
+ ,4.9
+ ,0.1
+ ,82
+ ,2
+ ,212
+ ,3.17805
+ ,7.46107
+ ,-2.8
+ ,1.4
+ ,-0.1
+ ,243
+ ,20
+ ,102
+ ,4.48864
+ ,7.68018
+ ,-0.4
+ ,0.8
+ ,2.6
+ ,147
+ ,21
+ ,49
+ ,2.30259
+ ,7.80344
+ ,2.4
+ ,3.9
+ ,0.2
+ ,14.3
+ ,20
+ ,574
+ ,3.29584
+ ,8.26256
+ ,3.4
+ ,0.9
+ ,0.3
+ ,228
+ ,16
+ ,109
+ ,3.17805
+ ,7.6695
+ ,12.1
+ ,2.8
+ ,-3.2
+ ,256
+ ,13
+ ,203
+ ,4.06044
+ ,5.33272
+ ,-2.5
+ ,2
+ ,1.3
+ ,80.7
+ ,3
+ ,532
+ ,4.15888
+ ,6.30992
+ ,-4.5
+ ,2
+ ,0.3
+ ,90
+ ,24
+ ,100
+ ,3.09104
+ ,6.67456
+ ,2.2
+ ,7.1
+ ,0.1
+ ,37.9
+ ,6
+ ,557
+ ,4.41884
+ ,8.09316
+ ,-4.7
+ ,1.4
+ ,1.2
+ ,276.8
+ ,18
+ ,445
+ ,2.89037
+ ,6.56667
+ ,0.1
+ ,2.1
+ ,-0.2
+ ,247.4
+ ,6
+ ,543
+ ,1.09861
+ ,5.83481
+ ,-5.8
+ ,7.7
+ ,0.1
+ ,47
+ ,7
+ ,90
+ ,3.43399
+ ,7.794
+ ,3.3
+ ,4.3
+ ,0.8
+ ,217
+ ,17
+ ,105
+ ,3.52636
+ ,7.76089
+ ,2
+ ,1.7
+ ,1.1
+ ,234
+ ,15
+ ,121
+ ,3.13549
+ ,7.67276
+ ,1.3
+ ,4.2
+ ,0.2
+ ,169
+ ,10
+ ,61
+ ,2.19722
+ ,7.979
+ ,1.4
+ ,5
+ ,-0.1
+ ,40.7
+ ,9
+ ,480
+ ,3.13549
+ ,7.78406
+ ,6.1
+ ,1.9
+ ,0.4
+ ,171
+ ,21
+ ,210
+ ,2.07944
+ ,5.95842
+ ,-3.1
+ ,4.2
+ ,-0.1
+ ,52.5
+ ,2
+ ,426
+ ,3.63759
+ ,4.54329
+ ,-11.5
+ ,1.7
+ ,3.7
+ ,90.4
+ ,4
+ ,465
+ ,3.73767
+ ,5.62762
+ ,-6.6
+ ,1
+ ,-0.1
+ ,200
+ ,2
+ ,445
+ ,2.48491
+ ,5.66643
+ ,-3.8
+ ,2.1
+ ,0.6
+ ,73
+ ,3
+ ,77
+ ,1.94591
+ ,7.54539
+ ,6.5
+ ,9.4
+ ,-0.9
+ ,250
+ ,11
+ ,160
+ ,1.94591
+ ,6.23832
+ ,-0.4
+ ,3.3
+ ,0.3
+ ,215.1
+ ,24
+ ,470
+ ,2.77259
+ ,4.56435
+ ,-6.3
+ ,2
+ ,2.3
+ ,223
+ ,3
+ ,148
+ ,2.70805
+ ,6.58203
+ ,2.2
+ ,1.8
+ ,0.1
+ ,64.2
+ ,6
+ ,549
+ ,1.79176
+ ,5.31321
+ ,-4.9
+ ,4.2
+ ,0.3
+ ,353
+ ,2
+ ,117
+ ,2.30259
+ ,5.61677
+ ,-1.3
+ ,2.8
+ ,-0.1
+ ,65.2
+ ,1
+ ,486
+ ,4.11087
+ ,7.7111
+ ,-5.1
+ ,0.7
+ ,0.3
+ ,60
+ ,10
+ ,99
+ ,3.4012
+ ,6.2519
+ ,0.1
+ ,1
+ ,0.2
+ ,87
+ ,24
+ ,111
+ ,3.68888
+ ,7.85516
+ ,6.5
+ ,5.2
+ ,-0.2
+ ,69
+ ,19
+ ,196
+ ,4.17439
+ ,8.24512
+ ,8.6
+ ,1.6
+ ,-1
+ ,258.8
+ ,15
+ ,530)
+ ,dim=c(8
+ ,500)
+ ,dimnames=list(c('PM10'
+ ,'Cars'
+ ,'Temp'
+ ,'Windspeed'
+ ,'Tempdiff'
+ ,'Winddir'
+ ,'hour'
+ ,'day')
+ ,1:500))
>  y <- array(NA,dim=c(8,500),dimnames=list(c('PM10','Cars','Temp','Windspeed','Tempdiff','Winddir','hour','day'),1:500))
>  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 = '1'
> par2 = 'quantiles'
> par1 = '1'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Dr. Ian E. Holliday
> #To cite this work: Ian E. Holliday, 2009, YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/
> #Source of accompanying publication: 
> #Technical description: 
> 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.numeric 

Loading required package: sandwich
Loading required package: strucchange
Loading required package: vcd
Loading required package: MASS
Loading required package: colorspace
> library(Hmisc)

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] "PM10"
> x[,par1]
  [1] 3.66356 3.04452 3.71357 2.94444 4.06044 3.68888 3.33220 3.36730 2.07944
 [10] 1.94591 3.33220 3.21888 1.09861 5.38450 3.93183 3.36730 2.83321 3.04452
 [19] 2.99573 4.21951 3.04452 3.76120 3.58352 2.48491 2.48491 3.33220 3.13549
 [28] 2.07944 3.68888 2.99573 3.98898 3.04452 3.55535 1.79176 3.04452 2.56495
 [37] 4.36945 3.46574 4.60517 3.09104 4.15888 1.79176 2.48491 3.21888 3.73767
 [46] 4.24850 3.87120 4.00733 2.94444 3.09104 1.94591 3.52636 3.87120 2.99573
 [55] 4.07754 3.21888 3.49651 3.25810 2.99573 2.70805 3.09104 4.06044 3.61092
 [64] 2.56495 1.60944 5.08760 2.30259 3.25810 3.66356 3.04452 3.40120 3.04452
 [73] 3.40120 3.55535 3.97029 4.72739 4.30407 2.56495 3.78419 4.95583 3.66356
 [82] 5.26786 3.46574 2.07944 3.36730 3.29584 2.19722 3.43399 3.25810 2.83321
 [91] 3.63759 2.70805 2.99573 4.00733 3.43399 0.69315 3.52636 2.63906 1.94591
[100] 3.71357 2.83321 3.43399 3.29584 3.17805 4.81218 4.63473 3.04452 3.87120
[109] 3.68888 4.33073 4.61512 4.43082 3.40120 2.48491 3.29584 2.94444 3.36730
[118] 2.89037 4.90527 2.63906 3.29584 3.71357 4.39445 3.82864 2.56495 3.33220
[127] 3.13549 0.69315 4.00733 3.25810 3.25810 4.84419 2.63906 1.38629 3.25810
[136] 2.30259 3.09104 2.94444 3.40120 2.99573 3.82864 2.30259 4.29046 4.41884
[145] 3.36730 2.30259 3.98898 4.12713 3.68888 2.30259 3.29584 3.13549 2.07944
[154] 5.25227 3.78419 3.97029 2.99573 2.56495 3.21888 1.38629 3.13549 4.06044
[163] 4.27667 3.49651 3.21888 4.07754 4.20469 4.18965 2.48491 1.09861 2.48491
[172] 2.48491 0.69315 4.34381 2.63906 3.29584 4.17439 3.71357 4.02535 4.85203
[181] 4.64439 3.63759 3.40120 1.79176 4.11087 3.36730 4.44265 2.77259 3.71357
[190] 5.17048 3.09104 2.70805 4.11087 4.79579 2.39790 2.99573 3.13549 3.43399
[199] 3.40120 3.09104 4.45435 4.18965 3.73767 4.20469 2.56495 2.56495 4.85981
[208] 5.25227 2.63906 3.13549 1.94591 3.40120 4.72739 3.36730 3.25810 3.73767
[217] 1.79176 4.06044 3.91202 0.69315 1.60944 4.46591 3.17805 2.89037 4.17439
[226] 3.73767 4.00733 3.04452 2.63906 4.11087 4.47734 3.17805 3.33220 0.69315
[235] 4.58497 0.69315 3.40120 2.07944 4.55388 3.21888 2.77259 3.29584 3.33220
[244] 4.02535 4.38203 2.99573 3.55535 3.25810 4.47734 4.06044 3.21888 4.46591
[253] 3.13549 2.30259 3.61092 3.13549 3.89182 3.21888 3.17805 3.73767 2.39790
[262] 3.68888 4.26268 4.94164 3.29584 2.07944 2.19722 2.07944 4.54329 2.07944
[271] 4.36945 3.97029 3.98898 2.99573 3.52636 2.99573 5.39363 3.63759 2.30259
[280] 4.92725 2.94444 2.70805 2.07944 3.40120 5.05625 4.93447 2.56495 3.04452
[289] 1.38629 2.77259 3.91202 4.35671 3.40120 4.02535 3.73767 2.94444 4.09434
[298] 3.04452 3.17805 2.56495 2.63906 3.09104 3.40120 2.19722 3.76120 2.77259
[307] 3.40120 3.61092 3.36730 0.69315 2.94444 4.17439 2.83321 3.04452 3.25810
[316] 3.21888 4.23411 4.81218 4.39445 2.63906 3.25810 1.94591 2.94444 2.56495
[325] 3.21888 2.77259 4.61512 1.60944 2.07944 3.87120 3.17805 3.58352 4.68213
[334] 2.56495 2.30259 3.55535 3.46574 2.48491 4.21951 2.30259 2.70805 2.99573
[343] 2.48491 3.13549 4.15888 1.79176 3.29584 2.83321 3.52636 3.25810 3.98898
[352] 1.60944 3.49651 3.17805 4.67283 3.43399 2.07944 3.29584 2.30259 2.07944
[361] 0.69315 3.13549 3.82864 3.87120 2.99573 3.25810 3.33220 3.49651 1.94591
[370] 4.57471 3.91202 3.80666 3.93183 2.48491 3.13549 2.94444 3.40120 1.94591
[379] 3.17805 3.21888 2.63906 3.33220 2.70805 3.78419 3.78419 1.60944 3.36730
[388] 3.04452 4.45435 1.94591 2.63906 3.33220 3.43399 3.89182 2.19722 4.59512
[397] 3.49651 2.83321 2.19722 2.89037 3.40120 2.99573 3.73767 2.94444 3.58352
[406] 3.29584 4.87520 4.33073 3.29584 3.78419 3.61092 2.83321 3.76120 3.58352
[415] 3.17805 3.52636 4.21951 3.93183 2.30259 3.25810 2.70805 3.55535 1.94591
[424] 4.36945 4.70048 2.48491 1.60944 3.78419 1.94591 3.09104 3.21888 2.48491
[433] 2.19722 4.93447 4.04305 4.51086 1.94591 3.09104 4.60517 3.63759 3.46574
[442] 3.87120 5.15329 3.04452 3.49651 2.56495 3.85015 2.48491 2.07944 2.99573
[451] 1.38629 3.17805 2.19722 3.55535 3.87120 3.40120 3.04452 4.34381 2.39790
[460] 2.63906 2.56495 3.33220 2.56495 3.68888 2.39790 2.39790 4.68213 3.04452
[469] 3.04452 2.19722 3.17805 4.48864 2.30259 3.29584 3.17805 4.06044 4.15888
[478] 3.09104 4.41884 2.89037 1.09861 3.43399 3.52636 3.13549 2.19722 3.13549
[487] 2.07944 3.63759 3.73767 2.48491 1.94591 1.94591 2.77259 2.70805 1.79176
[496] 2.30259 4.11087 3.40120 3.68888 4.17439
> 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])

[0.693,5.39] 
         500 
> colnames(x)
[1] "PM10"      "Cars"      "Temp"      "Windspeed" "Tempdiff"  "Winddir"  
[7] "hour"      "day"      
> colnames(x)[par1]
[1] "PM10"
> x[,par1]
  [1] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
  [6] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [11] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [16] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [21] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [26] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [31] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [36] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [41] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [46] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [51] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [56] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [61] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [66] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [71] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [76] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [81] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [86] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [91] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
 [96] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[101] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[106] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[111] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[116] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[121] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[126] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[131] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[136] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[141] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[146] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[151] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[156] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[161] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[166] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[171] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[176] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[181] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[186] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[191] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[196] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[201] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[206] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[211] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[216] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[221] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[226] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[231] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[236] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[241] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[246] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[251] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[256] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[261] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[266] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[271] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[276] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[281] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[286] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[291] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[296] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[301] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[306] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[311] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[316] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[321] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[326] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[331] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[336] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[341] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[346] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[351] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[356] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[361] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[366] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[371] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[376] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[381] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[386] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[391] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[396] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[401] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[406] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[411] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[416] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[421] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[426] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[431] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[436] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[441] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[446] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[451] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[456] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[461] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[466] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[471] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[476] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[481] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[486] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[491] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
[496] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39] [0.693,5.39]
Levels: [0.693,5.39]
> if (par2 == 'none') {
+ m <- ctree(as.formula(paste(colnames(x)[par1],' ~ .',sep='')),data = x)
+ }
> 
> #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/html/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/www/html/rcomp/tmp/1yz5j1291979012.tab") 
+ }
+ }
Warning messages:
1: In ff_trafo(x) : factors at only one level may lead to problems
2: In factor_trafo(x) : factors at only one level may lead to problems
> m

	 Conditional inference tree with 1 terminal nodes

Response:  as.factor(PM10) 
Inputs:  Cars, Temp, Windspeed, Tempdiff, Winddir, hour, day 
Number of observations:  500 

1)*  weights = 500 
> postscript(file="/var/www/html/rcomp/tmp/2yz5j1291979012.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/www/html/rcomp/tmp/3qqm41291979012.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)
+ }
> if (par2 != 'none') {
+ print(cbind(as.factor(x[,par1]),predict(m)))
+ myt <- table(as.factor(x[,par1]),predict(m))
+ print(myt)
+ }
       [,1] [,2]
  [1,]    1    1
  [2,]    1    1
  [3,]    1    1
  [4,]    1    1
  [5,]    1    1
  [6,]    1    1
  [7,]    1    1
  [8,]    1    1
  [9,]    1    1
 [10,]    1    1
 [11,]    1    1
 [12,]    1    1
 [13,]    1    1
 [14,]    1    1
 [15,]    1    1
 [16,]    1    1
 [17,]    1    1
 [18,]    1    1
 [19,]    1    1
 [20,]    1    1
 [21,]    1    1
 [22,]    1    1
 [23,]    1    1
 [24,]    1    1
 [25,]    1    1
 [26,]    1    1
 [27,]    1    1
 [28,]    1    1
 [29,]    1    1
 [30,]    1    1
 [31,]    1    1
 [32,]    1    1
 [33,]    1    1
 [34,]    1    1
 [35,]    1    1
 [36,]    1    1
 [37,]    1    1
 [38,]    1    1
 [39,]    1    1
 [40,]    1    1
 [41,]    1    1
 [42,]    1    1
 [43,]    1    1
 [44,]    1    1
 [45,]    1    1
 [46,]    1    1
 [47,]    1    1
 [48,]    1    1
 [49,]    1    1
 [50,]    1    1
 [51,]    1    1
 [52,]    1    1
 [53,]    1    1
 [54,]    1    1
 [55,]    1    1
 [56,]    1    1
 [57,]    1    1
 [58,]    1    1
 [59,]    1    1
 [60,]    1    1
 [61,]    1    1
 [62,]    1    1
 [63,]    1    1
 [64,]    1    1
 [65,]    1    1
 [66,]    1    1
 [67,]    1    1
 [68,]    1    1
 [69,]    1    1
 [70,]    1    1
 [71,]    1    1
 [72,]    1    1
 [73,]    1    1
 [74,]    1    1
 [75,]    1    1
 [76,]    1    1
 [77,]    1    1
 [78,]    1    1
 [79,]    1    1
 [80,]    1    1
 [81,]    1    1
 [82,]    1    1
 [83,]    1    1
 [84,]    1    1
 [85,]    1    1
 [86,]    1    1
 [87,]    1    1
 [88,]    1    1
 [89,]    1    1
 [90,]    1    1
 [91,]    1    1
 [92,]    1    1
 [93,]    1    1
 [94,]    1    1
 [95,]    1    1
 [96,]    1    1
 [97,]    1    1
 [98,]    1    1
 [99,]    1    1
[100,]    1    1
[101,]    1    1
[102,]    1    1
[103,]    1    1
[104,]    1    1
[105,]    1    1
[106,]    1    1
[107,]    1    1
[108,]    1    1
[109,]    1    1
[110,]    1    1
[111,]    1    1
[112,]    1    1
[113,]    1    1
[114,]    1    1
[115,]    1    1
[116,]    1    1
[117,]    1    1
[118,]    1    1
[119,]    1    1
[120,]    1    1
[121,]    1    1
[122,]    1    1
[123,]    1    1
[124,]    1    1
[125,]    1    1
[126,]    1    1
[127,]    1    1
[128,]    1    1
[129,]    1    1
[130,]    1    1
[131,]    1    1
[132,]    1    1
[133,]    1    1
[134,]    1    1
[135,]    1    1
[136,]    1    1
[137,]    1    1
[138,]    1    1
[139,]    1    1
[140,]    1    1
[141,]    1    1
[142,]    1    1
[143,]    1    1
[144,]    1    1
[145,]    1    1
[146,]    1    1
[147,]    1    1
[148,]    1    1
[149,]    1    1
[150,]    1    1
[151,]    1    1
[152,]    1    1
[153,]    1    1
[154,]    1    1
[155,]    1    1
[156,]    1    1
[157,]    1    1
[158,]    1    1
[159,]    1    1
[160,]    1    1
[161,]    1    1
[162,]    1    1
[163,]    1    1
[164,]    1    1
[165,]    1    1
[166,]    1    1
[167,]    1    1
[168,]    1    1
[169,]    1    1
[170,]    1    1
[171,]    1    1
[172,]    1    1
[173,]    1    1
[174,]    1    1
[175,]    1    1
[176,]    1    1
[177,]    1    1
[178,]    1    1
[179,]    1    1
[180,]    1    1
[181,]    1    1
[182,]    1    1
[183,]    1    1
[184,]    1    1
[185,]    1    1
[186,]    1    1
[187,]    1    1
[188,]    1    1
[189,]    1    1
[190,]    1    1
[191,]    1    1
[192,]    1    1
[193,]    1    1
[194,]    1    1
[195,]    1    1
[196,]    1    1
[197,]    1    1
[198,]    1    1
[199,]    1    1
[200,]    1    1
[201,]    1    1
[202,]    1    1
[203,]    1    1
[204,]    1    1
[205,]    1    1
[206,]    1    1
[207,]    1    1
[208,]    1    1
[209,]    1    1
[210,]    1    1
[211,]    1    1
[212,]    1    1
[213,]    1    1
[214,]    1    1
[215,]    1    1
[216,]    1    1
[217,]    1    1
[218,]    1    1
[219,]    1    1
[220,]    1    1
[221,]    1    1
[222,]    1    1
[223,]    1    1
[224,]    1    1
[225,]    1    1
[226,]    1    1
[227,]    1    1
[228,]    1    1
[229,]    1    1
[230,]    1    1
[231,]    1    1
[232,]    1    1
[233,]    1    1
[234,]    1    1
[235,]    1    1
[236,]    1    1
[237,]    1    1
[238,]    1    1
[239,]    1    1
[240,]    1    1
[241,]    1    1
[242,]    1    1
[243,]    1    1
[244,]    1    1
[245,]    1    1
[246,]    1    1
[247,]    1    1
[248,]    1    1
[249,]    1    1
[250,]    1    1
[251,]    1    1
[252,]    1    1
[253,]    1    1
[254,]    1    1
[255,]    1    1
[256,]    1    1
[257,]    1    1
[258,]    1    1
[259,]    1    1
[260,]    1    1
[261,]    1    1
[262,]    1    1
[263,]    1    1
[264,]    1    1
[265,]    1    1
[266,]    1    1
[267,]    1    1
[268,]    1    1
[269,]    1    1
[270,]    1    1
[271,]    1    1
[272,]    1    1
[273,]    1    1
[274,]    1    1
[275,]    1    1
[276,]    1    1
[277,]    1    1
[278,]    1    1
[279,]    1    1
[280,]    1    1
[281,]    1    1
[282,]    1    1
[283,]    1    1
[284,]    1    1
[285,]    1    1
[286,]    1    1
[287,]    1    1
[288,]    1    1
[289,]    1    1
[290,]    1    1
[291,]    1    1
[292,]    1    1
[293,]    1    1
[294,]    1    1
[295,]    1    1
[296,]    1    1
[297,]    1    1
[298,]    1    1
[299,]    1    1
[300,]    1    1
[301,]    1    1
[302,]    1    1
[303,]    1    1
[304,]    1    1
[305,]    1    1
[306,]    1    1
[307,]    1    1
[308,]    1    1
[309,]    1    1
[310,]    1    1
[311,]    1    1
[312,]    1    1
[313,]    1    1
[314,]    1    1
[315,]    1    1
[316,]    1    1
[317,]    1    1
[318,]    1    1
[319,]    1    1
[320,]    1    1
[321,]    1    1
[322,]    1    1
[323,]    1    1
[324,]    1    1
[325,]    1    1
[326,]    1    1
[327,]    1    1
[328,]    1    1
[329,]    1    1
[330,]    1    1
[331,]    1    1
[332,]    1    1
[333,]    1    1
[334,]    1    1
[335,]    1    1
[336,]    1    1
[337,]    1    1
[338,]    1    1
[339,]    1    1
[340,]    1    1
[341,]    1    1
[342,]    1    1
[343,]    1    1
[344,]    1    1
[345,]    1    1
[346,]    1    1
[347,]    1    1
[348,]    1    1
[349,]    1    1
[350,]    1    1
[351,]    1    1
[352,]    1    1
[353,]    1    1
[354,]    1    1
[355,]    1    1
[356,]    1    1
[357,]    1    1
[358,]    1    1
[359,]    1    1
[360,]    1    1
[361,]    1    1
[362,]    1    1
[363,]    1    1
[364,]    1    1
[365,]    1    1
[366,]    1    1
[367,]    1    1
[368,]    1    1
[369,]    1    1
[370,]    1    1
[371,]    1    1
[372,]    1    1
[373,]    1    1
[374,]    1    1
[375,]    1    1
[376,]    1    1
[377,]    1    1
[378,]    1    1
[379,]    1    1
[380,]    1    1
[381,]    1    1
[382,]    1    1
[383,]    1    1
[384,]    1    1
[385,]    1    1
[386,]    1    1
[387,]    1    1
[388,]    1    1
[389,]    1    1
[390,]    1    1
[391,]    1    1
[392,]    1    1
[393,]    1    1
[394,]    1    1
[395,]    1    1
[396,]    1    1
[397,]    1    1
[398,]    1    1
[399,]    1    1
[400,]    1    1
[401,]    1    1
[402,]    1    1
[403,]    1    1
[404,]    1    1
[405,]    1    1
[406,]    1    1
[407,]    1    1
[408,]    1    1
[409,]    1    1
[410,]    1    1
[411,]    1    1
[412,]    1    1
[413,]    1    1
[414,]    1    1
[415,]    1    1
[416,]    1    1
[417,]    1    1
[418,]    1    1
[419,]    1    1
[420,]    1    1
[421,]    1    1
[422,]    1    1
[423,]    1    1
[424,]    1    1
[425,]    1    1
[426,]    1    1
[427,]    1    1
[428,]    1    1
[429,]    1    1
[430,]    1    1
[431,]    1    1
[432,]    1    1
[433,]    1    1
[434,]    1    1
[435,]    1    1
[436,]    1    1
[437,]    1    1
[438,]    1    1
[439,]    1    1
[440,]    1    1
[441,]    1    1
[442,]    1    1
[443,]    1    1
[444,]    1    1
[445,]    1    1
[446,]    1    1
[447,]    1    1
[448,]    1    1
[449,]    1    1
[450,]    1    1
[451,]    1    1
[452,]    1    1
[453,]    1    1
[454,]    1    1
[455,]    1    1
[456,]    1    1
[457,]    1    1
[458,]    1    1
[459,]    1    1
[460,]    1    1
[461,]    1    1
[462,]    1    1
[463,]    1    1
[464,]    1    1
[465,]    1    1
[466,]    1    1
[467,]    1    1
[468,]    1    1
[469,]    1    1
[470,]    1    1
[471,]    1    1
[472,]    1    1
[473,]    1    1
[474,]    1    1
[475,]    1    1
[476,]    1    1
[477,]    1    1
[478,]    1    1
[479,]    1    1
[480,]    1    1
[481,]    1    1
[482,]    1    1
[483,]    1    1
[484,]    1    1
[485,]    1    1
[486,]    1    1
[487,]    1    1
[488,]    1    1
[489,]    1    1
[490,]    1    1
[491,]    1    1
[492,]    1    1
[493,]    1    1
[494,]    1    1
[495,]    1    1
[496,]    1    1
[497,]    1    1
[498,]    1    1
[499,]    1    1
[500,]    1    1
              
               [0.693,5.39]
  [0.693,5.39]          500
> postscript(file="/var/www/html/rcomp/tmp/41zl71291979012.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')
+ }
Error in rep.int(0, ydim) : invalid 'times' value
Calls: plot ... mosaicplot.default -> mosaic.cell -> Recall -> mosaic.cell -> rep.int
Execution halted