R version 2.12.0 (2010-10-15)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(6.4,7.7,9.2,8.6,7.4,8.6,6.2,6,6.6,5.1,4.7,5,3.6,1.9,-0.1,-5.7,-5.6,-6.4,-7.7,-8,-11.9,-15.4,-15.5,-13.4,-10.9,-10.8,-7.3,-6.5,-5.1,-5.3,-6.8,-8.4,-8.4,-9.7,-8.8,-9.6,-11.5,-11,-14.9,-16.2,-14.4,-17.3,-15.7,-12.6,-9.4,-8.1,-5.4,-4.6,-4.9,-4,-3.1,-1.3,0,-0.4,3,0.4,1.2,0.6,-1.3,-3.2,-1.8,-3.6,-4.2,-6.9,-8,-7.5,-8.2,-7.6,-3.7,-1.7,-0.7,0.2,0.6,2.2,3.3,5.3,5.5,6.3,7.7,6.5,5.5,6.9,5.7,6.9,6.1,4.8,3.7,5.8,6.8,8.5,7.2,5,4.7,2.3,2.4,0.1,1.9,1.7,2,-1.9,0.5,-1.3,-3.3,-2.8,-8,-13.9,-21.9,-28.8,-27.6,-31.4,-31.8,-29.4,-27.6,-23.6,-22.8,-18.2,-17.8,-14.2,-8.8,-7.9,-7,-7,-3.6,-2.4,-4.9,-7.7,-6.5,-5.1,-3.4,-2.8,0.8)
> par1 = '12'
> #'GNU S' R Code compiled by R2WASP v. 1.0.44 ()
> #Author: Prof. Dr. P. Wessa
> #To cite this work: AUTHOR(S), (YEAR), 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: Office for Research, Development, and Education
> #Technical description: Write here your technical program description (don't use hard returns!)
> par1 <- as.numeric(par1)
> (n <- length(x))
[1] 131
> (np <- floor(n / par1))
[1] 10
> 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,]  6.4   3.6 -10.9 -11.5 -4.9 -1.8  0.6  6.1   1.9 -27.6
 [2,]  7.7   1.9 -10.8 -11.0 -4.0 -3.6  2.2  4.8   1.7 -31.4
 [3,]  9.2  -0.1  -7.3 -14.9 -3.1 -4.2  3.3  3.7   2.0 -31.8
 [4,]  8.6  -5.7  -6.5 -16.2 -1.3 -6.9  5.3  5.8  -1.9 -29.4
 [5,]  7.4  -5.6  -5.1 -14.4  0.0 -8.0  5.5  6.8   0.5 -27.6
 [6,]  8.6  -6.4  -5.3 -17.3 -0.4 -7.5  6.3  8.5  -1.3 -23.6
 [7,]  6.2  -7.7  -6.8 -15.7  3.0 -8.2  7.7  7.2  -3.3 -22.8
 [8,]  6.0  -8.0  -8.4 -12.6  0.4 -7.6  6.5  5.0  -2.8 -18.2
 [9,]  6.6 -11.9  -8.4  -9.4  1.2 -3.7  5.5  4.7  -8.0 -17.8
[10,]  5.1 -15.4  -9.7  -8.1  0.6 -1.7  6.9  2.3 -13.9 -14.2
[11,]  4.7 -15.5  -8.8  -5.4 -1.3 -0.7  5.7  2.4 -21.9  -8.8
[12,]  5.0 -13.4  -9.6  -4.6 -3.2  0.2  6.9  0.1 -28.8  -7.9
> 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]   6.791667  -7.016667  -8.133333 -11.758333  -1.083333  -4.475000
 [7]   5.200000   4.783333  -6.316667 -21.758333
> arr.sd
 [1]  1.512048  6.413456  1.961601  4.208100  2.340875  3.067461  2.113592
 [8]  2.364446 10.100570  8.368497
> arr.range
 [1]  4.5 19.1  5.8 12.7  7.9  8.4  7.1  8.4 30.8 23.9
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
     3.2706      -0.2227  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
        2.846         -1.270  

Warning message:
In log(arr.mean) : NaNs produced
> (lm2 <- lm(arr.range~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
    10.2015      -0.6074  

> postscript(file="/var/www/rcomp/tmp/19cd61293199498.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/www/rcomp/tmp/29cd61293199498.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/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/www/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/www/rcomp/tmp/3uccc1293199498.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/rcomp/tmp/4xvsi1293199498.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/www/rcomp/tmp/5jv9o1293199498.tab") 
> 
> try(system("convert tmp/19cd61293199498.ps tmp/19cd61293199498.png",intern=TRUE))
character(0)
> try(system("convert tmp/29cd61293199498.ps tmp/29cd61293199498.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
   0.59    0.40    0.98