source('/home/pw/wessanet/cretab')



myrfcuid = 'r0578244'

x <- c(122.2,136.1,145.5,116.7,137.1,125.5,112.4,106.3,145.7,151.5,144.6,116.4,137.7,138.8,149.5,125,133.4,134.4,124.8,110.6,142.4,149.6,134.6,103.3,136.5,137.1,140.7,131.4,126.2,125.3,126.6,107.7,144.5,154.2,131.4,105.7,136.2,133.3,130,129.3,113.1,117.7,116.3,97.3,140.6,141.2,120.8,106.2,121.5,122.6,137.2,118.9,107.2,127.4,111.8,100,138.3,128,121.2,105.9,112.5,123.1,129,115.5,105.7,122.3,106.4,101.1,131.6,119.5,127,106.9,115.9,122.7,137.2,108.5,115.2,129.4,112.3,104.3,140,139.9,134.9,105.1,127,135.5,143.9,115.8,117.5,129.3,117.9,108.1,131.7,143.7,126.2,96.9,125.8,129.6,124.9,136.8,107.5,114.3,110.3,85.5,116.8,115.1,95.2,83.4,95.4,96.3,100.5,90.9,80.6,94.8,93.9,75.9,101.6,103.3,91.8,83.5,92,101.2,109.1,99.8,90.8,110.6,97.8,81.9,114.4,108.8,103.1,90.4,94.4,100.5,115.1,93.9,102.5,97.1,91.2,82.3,107.1,99.2,94.8,81.1,92.5,97.7,98.5,81.2,86.2,92,86.3,74.8,90,101.1,87.8,66.3,88.6,90,92,85.1,85.9,88.5,92.3,68,93.6,97.7,85.1,69.9,96.1,97,95.9,91.3,83.5,91.4,96.8,71,106.9,102.7,84.9,75.8,93.6,100.7,100.5,95.9,85.7,104.1,93.5,81.5,102.1,98.2,88.4,77.8,90.1,101,98.6,91.5,86.4,98.9,85.2,77.3,93,86.8,91.3,74.9,93.9,95,103.1,81.4,93.1,97.2,86.4,75.5)
par1 = '12'
par1 <- '12'
#'GNU S' R Code compiled by R2WASP v. 1.2.327 (Sat, 15 Jul 2017 00:11:16 +0200)
#Author: root
#To cite this work: Wessa P. (2017), Standard Deviation-Mean Plot (v1.0.7) in Free Statistics Software (v$_version), Office for Research Development and Education, URL https://www.wessa.net/rwasp_smp.wasp/
#Source of accompanying publication: Office for Research, Development, and Education
#
par1 <- as.numeric(par1)
(n <- length(x))
(np <- floor(n / par1))
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
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
arr.sd
arr.range
(lm1 <- lm(arr.sd~arr.mean))
(lnlm1 <- lm(log(arr.sd)~log(arr.mean)))
(lm2 <- lm(arr.range~arr.mean))
postscript(file="/home/pw/wessanet/rcomp/tmp/157cx1513866982.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()
postscript(file="/home/pw/wessanet/rcomp/tmp/2z1py1513866982.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()

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="/home/pw/wessanet/rcomp/tmp/3ev9e1513866982.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)$coefficients[2,4])
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file="/home/pw/wessanet/rcomp/tmp/4c59h1513866982.tab") 
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'alpha',header=TRUE)
a<-table.element(a,lnlm1$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="/home/pw/wessanet/rcomp/tmp/5xucl1513866982.tab") 

try(system("convert /home/pw/wessanet/rcomp/tmp/157cx1513866982.ps /home/pw/wessanet/rcomp/tmp/157cx1513866982.png",intern=TRUE))
try(system("convert /home/pw/wessanet/rcomp/tmp/2z1py1513866982.ps /home/pw/wessanet/rcomp/tmp/2z1py1513866982.png",intern=TRUE))