R version 2.6.0 (2007-10-03)
Copyright (C) 2007 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> x <- c(263418000000,262752000000,266433000000,267722000000,266003000000,262971000000,265521000000,264676000000,270223000000,269508000000,268457000000,265814000000,266680000000,263018000000,269285000000,269829000000,270911000000,266844000000,271244000000,269907000000,271296000000,270157000000,271322000000,267179000000,264101000000,265518000000,269419000000,268714000000,272482000000,268351000000,268175000000,270674000000,272764000000,272599000000,270333000000,270846000000,270491000000,269160000000,274027000000,273784000000,276663000000,274525000000,271344000000,271115000000,270798000000,273911000000,273985000000,271917000000,273338000000,270601000000,273547000000,275363000000,281229000000,277793000000,279913000000,282500000000,280041000000,282166000000,290304000000,283519000000)
> 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] 60
> (np <- floor(n / par1))
[1] 5
> 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]
 [1,] 2.63418e+11 2.66680e+11 2.64101e+11 2.70491e+11 2.73338e+11
 [2,] 2.62752e+11 2.63018e+11 2.65518e+11 2.69160e+11 2.70601e+11
 [3,] 2.66433e+11 2.69285e+11 2.69419e+11 2.74027e+11 2.73547e+11
 [4,] 2.67722e+11 2.69829e+11 2.68714e+11 2.73784e+11 2.75363e+11
 [5,] 2.66003e+11 2.70911e+11 2.72482e+11 2.76663e+11 2.81229e+11
 [6,] 2.62971e+11 2.66844e+11 2.68351e+11 2.74525e+11 2.77793e+11
 [7,] 2.65521e+11 2.71244e+11 2.68175e+11 2.71344e+11 2.79913e+11
 [8,] 2.64676e+11 2.69907e+11 2.70674e+11 2.71115e+11 2.82500e+11
 [9,] 2.70223e+11 2.71296e+11 2.72764e+11 2.70798e+11 2.80041e+11
[10,] 2.69508e+11 2.70157e+11 2.72599e+11 2.73911e+11 2.82166e+11
[11,] 2.68457e+11 2.71322e+11 2.70333e+11 2.73985e+11 2.90304e+11
[12,] 2.65814e+11 2.67179e+11 2.70846e+11 2.71917e+11 2.83519e+11
> 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] 266124833333 268972666667 269498000000 272643333333 279192833333
> arr.sd
[1] 2478095047 2547773657 2725958747 2154153001 5426668823
> arr.range
[1] 6.8050e+09 8.5700e+09 6.3310e+09 8.9410e+09 2.4301e+10
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
 -5.762e+10    2.237e-01  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
      -393.03          15.76  

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

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

Coefficients:
(Intercept)     arr.mean  
 -3.651e+11    1.386e+00  

> postscript(file="/var/www/html/rcomp/tmp/1os381197626094.ps",horizontal=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/html/rcomp/tmp/2bphv1197626094.ps",horizontal=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 
> load(file='/var/www/html/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/html/rcomp/tmp/3h9kq1197626094.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/www/html/rcomp/tmp/4aoq71197626094.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/html/rcomp/tmp/5ji4a1197626095.tab") 
> 
> system("convert tmp/1os381197626094.ps tmp/1os381197626094.png")
> system("convert tmp/2bphv1197626094.ps tmp/2bphv1197626094.png")
> 
> 
> proc.time()
   user  system elapsed 
  0.737   0.282   0.858