R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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Platform: x86_64-pc-linux-gnu (64-bit)

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> x <- c(21571,21493,21422,21272,22747,22676,21571,20831,20909,20909,20980,21130,21051,21643,21864,21643,22455,21935,20759,20467,20467,20610,20026,20467,20097,20467,21051,21272,21792,21571,20246,19726,19506,19726,19363,19506,19064,19805,20168,20246,21643,21643,19805,19363,19363,19584,18622,18180,17668,17817,18480,17960,19363,19584,18180,17668,17375,17668,16855,16563,15388,15680,15751,15830,17226,17076,15388,14647,14355,14725,13322,12367,10601,10750,10750,10601,11854,11926,10451,10159,9568,10380,8905,8022,6333,6697,6255,6404,7509,7730,6996,6917,6917,7879,6184,5079,3163,4709,4488,4566,6333,6112,5300,5671,5671,6996,5450,4566,3163,5008,4859,4930,6476,6333,5813,5892,6255,7067,5813,4787)
> par1 = '12'
> par1 <- '12'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P. (2012), Standard Deviation-Mean Plot (v1.0.6) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_smp.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> par1 <- as.numeric(par1)
> (n <- length(x))
[1] 120
> (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,] 21571 21051 20097 19064 17668 15388 10601 6333 3163  3163
 [2,] 21493 21643 20467 19805 17817 15680 10750 6697 4709  5008
 [3,] 21422 21864 21051 20168 18480 15751 10750 6255 4488  4859
 [4,] 21272 21643 21272 20246 17960 15830 10601 6404 4566  4930
 [5,] 22747 22455 21792 21643 19363 17226 11854 7509 6333  6476
 [6,] 22676 21935 21571 21643 19584 17076 11926 7730 6112  6333
 [7,] 21571 20759 20246 19805 18180 15388 10451 6996 5300  5813
 [8,] 20831 20467 19726 19363 17668 14647 10159 6917 5671  5892
 [9,] 20909 20467 19506 19363 17375 14355  9568 6917 5671  6255
[10,] 20909 20610 19726 19584 17668 14725 10380 7879 6996  7067
[11,] 20980 20026 19363 18622 16855 13322  8905 6184 5450  5813
[12,] 21130 20467 19506 18180 16563 12367  8022 5079 4566  4787
> 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] 21459.250 21115.583 20360.250 19790.500 17931.750 15146.250 10330.583
 [8]  6741.667  5252.083  5533.000
> arr.sd
 [1]  642.4159  763.8452  862.1609 1049.1979  889.6428 1394.4437 1101.8161
 [8]  773.4585 1023.6292 1042.5622
> arr.range
 [1] 1916 2429 2429 3463 3021 4859 3904 2800 3833 3904
> (lm1 <- lm(arr.sd~arr.mean))

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

Coefficients:
(Intercept)     arr.mean  
  1.096e+03   -9.878e-03  

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

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

Coefficients:
  (Intercept)  log(arr.mean)  
       7.8338        -0.1054  

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

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

Coefficients:
(Intercept)     arr.mean  
 4258.82109     -0.06982  

> postscript(file="/var/wessaorg/rcomp/tmp/1abl71470858460.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/2lcpb1470858460.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/3x00s1470858460.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)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4ozze1470858460.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$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/54wje1470858460.tab") 
> 
> try(system("convert tmp/1abl71470858460.ps tmp/1abl71470858460.png",intern=TRUE))
character(0)
> try(system("convert tmp/2lcpb1470858460.ps tmp/2lcpb1470858460.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.832   0.082   0.923