R version 2.10.1 (2009-12-14)
Copyright (C) 2009 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(31.514,27.071,29.462,26.105,22.397,23.843,21.705,18.089,20.764,25.316,17.704,15.548,28.029,29.383,36.438,32.034,22.679,24.319,18.004,17.537,20.366,22.782,19.169,13.807,29.743,25.591,29.096,26.482,22.405,27.044,17.970,18.730,19.684,19.785,18.479,10.698,31.956,29.506,34.506,27.165,26.736,23.691,18.157,17.328,18.205,20.995,17.382,9.367,31.124,26.551,30.651,25.859,25.100,25.778,20.418,18.688,20.424,24.776,19.814,12.738,31.566,30.111,30.019,31.934,25.826,26.835,20.205,17.789,20.520,22.518,15.572,11.509,25.447,24.090,27.786,26.195,20.516,22.759,19.028,16.971,20.036,22.485,18.730,14.538,27.561,25.985,34.670,32.066,27.186,29.586,21.359,21.553,19.573,24.256,22.380,16.167,27.297,28.287)
> par20 = ''
> par19 = ''
> par18 = ''
> par17 = ''
> par16 = ''
> par15 = ''
> par14 = ''
> par13 = ''
> par12 = ''
> par11 = ''
> par10 = ''
> par9 = ''
> par8 = ''
> par7 = ''
> par6 = ''
> par5 = ''
> par4 = ''
> par3 = ''
> par2 = ''
> par1 = '4'
> ylab = ''
> xlab = ''
> main = ''
> par1 <- as.numeric(par1)
> (n <- length(x))
[1] 98
> (np <- floor(n / par1))
[1] 24
> arr <- array(NA,dim=c(par1,np))
> j <- 0
> k <- 1
> for (i in 1:(np*par1))
+ {
+ j = j + 1
+ arr[j,k] <- x[i]
+ if (j == par1) {
+ j = 0
+ k=k+1
+ }
+ }
> arr
       [,1]   [,2]   [,3]   [,4]   [,5]   [,6]   [,7]   [,8]   [,9]  [,10]
[1,] 31.514 22.397 20.764 28.029 22.679 20.366 29.743 22.405 19.684 31.956
[2,] 27.071 23.843 25.316 29.383 24.319 22.782 25.591 27.044 19.785 29.506
[3,] 29.462 21.705 17.704 36.438 18.004 19.169 29.096 17.970 18.479 34.506
[4,] 26.105 18.089 15.548 32.034 17.537 13.807 26.482 18.730 10.698 27.165
      [,11]  [,12]  [,13]  [,14]  [,15]  [,16]  [,17]  [,18]  [,19]  [,20]
[1,] 26.736 18.205 31.124 25.100 20.424 31.566 25.826 20.520 25.447 20.516
[2,] 23.691 20.995 26.551 25.778 24.776 30.111 26.835 22.518 24.090 22.759
[3,] 18.157 17.382 30.651 20.418 19.814 30.019 20.205 15.572 27.786 19.028
[4,] 17.328  9.367 25.859 18.688 12.738 31.934 17.789 11.509 26.195 16.971
      [,21]  [,22]  [,23]  [,24]
[1,] 20.036 27.561 27.186 19.573
[2,] 22.485 25.985 29.586 24.256
[3,] 18.730 34.670 21.359 22.380
[4,] 14.538 32.066 21.553 16.167
> arr.mean <- array(NA,dim=np)
> arr.sd <- array(NA,dim=np)
> arr.range <- array(NA,dim=np)
> for (j in 1:np)
+ {
+ arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
+ arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
+ arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
+ }
> arr.mean
 [1] 28.53800 21.50850 19.83300 31.47100 20.63475 19.03100 27.72800 21.53725
 [9] 17.16150 30.78325 21.47800 16.48725 28.54625 22.49600 19.43800 30.90750
[17] 22.66375 17.52975 25.87950 19.81850 18.94725 30.07050 24.92100 20.59400
> arr.sd
 [1] 2.4346067 2.4475100 4.2357178 3.7056338 3.3798203 3.7930395 2.0042400
 [8] 4.1506309 4.3496512 3.1600269 4.5016839 4.9922945 2.7250139 3.4819194
[15] 4.9832324 0.9850836 4.3668368 4.9634144 1.5409574 2.4403683 3.3261457
[22] 4.0052599 4.1200210 3.5232944
> arr.range
 [1]  5.409  5.754  9.768  8.409  6.782  8.975  4.152  9.074  9.087  7.341
[11]  9.408 11.628  5.265  7.090 12.038  1.915  9.046 11.009  3.696  5.788
[21]  7.947  8.685  8.227  8.089
> (lm1 <- lm(arr.sd~arr.mean))

Call:
lm(formula = arr.sd ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
      6.437       -0.127  

> (lnlm1 <- lm(log(arr.sd)~log(arr.mean)))

Call:
lm(formula = log(arr.sd) ~ log(arr.mean))

Coefficients:
  (Intercept)  log(arr.mean)  
        4.519         -1.066  

> (lm2 <- lm(arr.range~arr.mean))

Call:
lm(formula = arr.range ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
    14.8715      -0.3088  

> postscript(file="/var/yougetitorg/rcomp/tmp/1cbwp1305863528.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
> dev.off()
null device 
          1 
> postscript(file="/var/yougetitorg/rcomp/tmp/2g8fr1305863528.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
> dev.off()
null device 
          1 
> 
> #Note: the /var/yougetitorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/yougetitorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Section',header=TRUE)
> a<-table.element(a,'Mean',header=TRUE)
> a<-table.element(a,'Standard Deviation',header=TRUE)
> a<-table.element(a,'Range',header=TRUE)
> a<-table.row.end(a)
> for (j in 1:np) {
+ a<-table.row.start(a)
+ a<-table.element(a,j,header=TRUE)
+ a<-table.element(a,arr.mean[j])
+ a<-table.element(a,arr.sd[j] )
+ a<-table.element(a,arr.range[j] )
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/yougetitorg/rcomp/tmp/3fiod1305863528.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/yougetitorg/rcomp/tmp/4on0h1305863528.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Lambda',header=TRUE)
> a<-table.element(a,1-lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/yougetitorg/rcomp/tmp/5w0jd1305863528.tab") 
> try(system("convert tmp/1cbwp1305863528.ps tmp/1cbwp1305863528.png",intern=TRUE))
character(0)
> try(system("convert tmp/2g8fr1305863528.ps tmp/2g8fr1305863528.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
   0.63    0.37    0.83