R version 2.13.0 (2011-04-13)
Copyright (C) 2011 The R Foundation for Statistical Computing
ISBN 3-900051-07-0
Platform: i486-pc-linux-gnu (32-bit)

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> x <- c(588264,577918,567562,546859,756344,745987,588264,483527,493873,493873,504229,526055,462824,399492,347630,347630,546859,567562,409838,231412,325803,325803,399492,442021,431664,325803,378790,357986,536412,493873,325803,200263,315447,347630,378790,420195,336150,263595,294755,305101,577918,577918,420195,399492,462824,431664,515709,620447,641250,493873,452367,409838,694135,714939,661953,714939,704481,620447,714939,819676,862205,735641,651596,714939,987746,1071790,1051088,1092483,1082137,977399,1155825,1198354,1260562,1071790,998102,1082137,1282389,1460814,1418286,1418286,1439089,1366423,1555307,1555307,1523124,1344597,1376780,1397583,1534503,1712929,1586355,1649698,1596712,1565653,1807421,1754435,1680746,1576009,1680746,1733732,1796963,1880998,1796963,1848826,1785585,1775239,2037699,2059525,1975491,1828123,1953664,2006549,2069882,2164273,2069882,2143570,2111388,1996193,2237951,2237951)
> par1 = '4'
> #'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] 120
> (np <- floor(n / par1))
[1] 30
> 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,] 588264 756344 493873 462824 546859 325803 431664 536412 315447 336150
[2,] 577918 745987 493873 399492 567562 325803 325803 493873 347630 263595
[3,] 567562 588264 504229 347630 409838 399492 378790 325803 378790 294755
[4,] 546859 483527 526055 347630 231412 442021 357986 200263 420195 305101
      [,11]  [,12]  [,13]  [,14]  [,15]  [,16]   [,17]   [,18]   [,19]   [,20]
[1,] 577918 462824 641250 694135 704481 862205  987746 1082137 1260562 1282389
[2,] 577918 431664 493873 714939 620447 735641 1071790  977399 1071790 1460814
[3,] 420195 515709 452367 661953 714939 651596 1051088 1155825  998102 1418286
[4,] 399492 620447 409838 714939 819676 714939 1092483 1198354 1082137 1418286
       [,21]   [,22]   [,23]   [,24]   [,25]   [,26]   [,27]   [,28]   [,29]
[1,] 1439089 1523124 1534503 1596712 1680746 1796963 1785585 1975491 2069882
[2,] 1366423 1344597 1712929 1565653 1576009 1880998 1775239 1828123 2164273
[3,] 1555307 1376780 1586355 1807421 1680746 1796963 2037699 1953664 2069882
[4,] 1555307 1397583 1649698 1754435 1733732 1848826 2059525 2006549 2143570
       [,30]
[1,] 2111388
[2,] 1996193
[3,] 2237951
[4,] 2237951
> 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]  570150.8  643530.5  504507.5  389394.0  438917.8  373279.8  373560.8
 [8]  389087.8  365515.5  299900.2  493880.8  507661.0  499332.0  696491.5
[15]  714885.8  741095.2 1050776.8 1103428.8 1103147.8 1394943.8 1479031.5
[22] 1410521.0 1620871.2 1681055.2 1667808.2 1830937.5 1914512.0 1940956.8
[29] 2111901.8 2145870.8
> arr.sd
 [1]  17678.87 131503.77  15171.88  54718.67 155032.17  57505.14  44447.38
 [8] 155289.12  44694.54  29920.10  97405.24  82807.71 100640.29  25027.20
[15]  81665.86  88301.73  45291.43  96769.50 111413.07  77668.49  92937.22
[22]  78169.17  77365.92 118017.45  66100.46  41370.62 155159.00  78289.82
[29]  49250.87 116261.25
> arr.range
 [1]  41405 272817  32182 115194 336150 116218 105861 336149 104748  72555
[11] 178426 188783 231412  52986 199229 210609 104737 220955 262460 178425
[21] 188884 178527 178426 241768 157723  84035 284286 178426  94391 241758
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  6.851e+04    1.085e-02  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
        7.847          0.241  

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

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

Coefficients:
(Intercept)     arr.mean  
  1.554e+05    1.733e-02  

> postscript(file="/var/wessaorg/rcomp/tmp/13p3w1312453324.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/wessaorg/rcomp/tmp/2p1v21312453324.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/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/wessaorg/rcomp/tmp/3i68o1312453324.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/49gmv1312453325.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/wessaorg/rcomp/tmp/5by8z1312453325.tab") 
> 
> try(system("convert tmp/13p3w1312453324.ps tmp/13p3w1312453324.png",intern=TRUE))
character(0)
> try(system("convert tmp/2p1v21312453324.ps tmp/2p1v21312453324.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.648   0.120   0.759