R version 2.9.0 (2009-04-17) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- c(1.8,1.6,1.9,1.7,1.6,1.3,1.1,1.9,2.6,2.3,2.4,2.2,2,2.9,2.6,2.3,2.3,2.6,3.1,2.8,2.5,2.9,3.1,3.1,3.2,2.5,2.6,2.9,2.6,2.4,1.7,2,2.2,1.9,1.6,1.6,1.2,1.2,1.5,1.6,1.7,1.8,1.8,1.8,1.3,1.3,1.4,1.1,1.5,2.2,2.9,3.1,3.5,3.6,4.4,4.2,5.2,5.8,5.9,5.4,5.5) > 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] 61 > (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,] 1.8 2.0 3.2 1.2 1.5 [2,] 1.6 2.9 2.5 1.2 2.2 [3,] 1.9 2.6 2.6 1.5 2.9 [4,] 1.7 2.3 2.9 1.6 3.1 [5,] 1.6 2.3 2.6 1.7 3.5 [6,] 1.3 2.6 2.4 1.8 3.6 [7,] 1.1 3.1 1.7 1.8 4.4 [8,] 1.9 2.8 2.0 1.8 4.2 [9,] 2.6 2.5 2.2 1.3 5.2 [10,] 2.3 2.9 1.9 1.3 5.8 [11,] 2.4 3.1 1.6 1.4 5.9 [12,] 2.2 3.1 1.6 1.1 5.4 > 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] 1.866667 2.683333 2.266667 1.475000 3.975000 > arr.sd [1] 0.4478907 0.3613946 0.5210712 0.2598076 1.4258172 > arr.range [1] 1.5 1.1 1.6 0.7 4.4 > (lm1 <- lm(arr.sd~arr.mean)) Call: lm(formula = arr.sd ~ arr.mean) Coefficients: (Intercept) arr.mean -0.4819 0.4423 > (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) Call: lm(formula = log(arr.sd) ~ log(arr.mean)) Coefficients: (Intercept) log(arr.mean) -1.938 1.483 > (lm2 <- lm(arr.range~arr.mean)) Call: lm(formula = arr.range ~ arr.mean) Coefficients: (Intercept) arr.mean -1.507 1.373 > postscript(file="/var/www/html/rcomp/tmp/1fpqk1259251046.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/29bco1259251046.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 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > 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/3owfj1259251046.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/40dru1259251046.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/5hlqe1259251046.tab") > > system("convert tmp/1fpqk1259251046.ps tmp/1fpqk1259251046.png") > system("convert tmp/29bco1259251046.ps tmp/29bco1259251046.png") > > > proc.time() user system elapsed 0.512 0.287 0.588