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Type 'q()' to quit R. > x <- c(1120,1120,1190,1190,1190,1190,1070,1200,1090,1130,1140,1240,1180,1080,1190,1140,1160,1200,980,1260,1100,1210,1150,1140,1110,1120,1100,1170,1120,1250,910,1260,1090,1240,1130,1200,1120,1120,1120,1070,1100,1230,930,1240,980,1270,1140,1160,1160,1220,1160,1090,1060,1230,1070,1240,1050,1350,1100,1130,1170,1360,1150,1180,1010,1190,1000,1270,990,1470,1130,1150,1150,1410,1190,1180,990,1170,1080,1350,960,1490,1120,1090,1220,1370,1180,1190,1000,1250,1090,1370,980,1530,1150,1120,1290,1370,1130,1200,910,1220,1040,1340,950,1500,1120,1150) > 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] 108 > (np <- floor(n / par1)) [1] 27 > 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] [,11] [,12] [,13] [,14] [1,] 1120 1190 1090 1180 1160 1100 1110 1120 1090 1120 1100 980 1160 1060 [2,] 1120 1190 1130 1080 1200 1210 1120 1250 1240 1120 1230 1270 1220 1230 [3,] 1190 1070 1140 1190 980 1150 1100 910 1130 1120 930 1140 1160 1070 [4,] 1190 1200 1240 1140 1260 1140 1170 1260 1200 1070 1240 1160 1090 1240 [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] [1,] 1050 1170 1010 990 1150 990 960 1220 1000 980 1290 910 [2,] 1350 1360 1190 1470 1410 1170 1490 1370 1250 1530 1370 1220 [3,] 1100 1150 1000 1130 1190 1080 1120 1180 1090 1150 1130 1040 [4,] 1130 1180 1270 1150 1180 1350 1090 1190 1370 1120 1200 1340 [,27] [1,] 950 [2,] 1500 [3,] 1120 [4,] 1150 > 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] 1155.0 1162.5 1150.0 1147.5 1150.0 1150.0 1125.0 1135.0 1165.0 1107.5 [11] 1125.0 1137.5 1157.5 1150.0 1157.5 1215.0 1117.5 1185.0 1232.5 1147.5 [21] 1165.0 1240.0 1177.5 1195.0 1247.5 1127.5 1180.0 > arr.sd [1] 40.41452 61.84658 63.77042 49.91660 120.55428 45.46061 31.09126 [8] 162.99284 67.57712 25.00000 144.79871 119.54776 53.15073 98.31921 [15] 132.50786 97.46794 134.00871 202.89570 119.54776 153.70426 227.52289 [22] 88.31761 164.79786 235.30123 104.68206 190.32866 230.79572 > arr.range [1] 70 130 150 110 280 110 70 350 150 50 310 290 130 180 300 210 270 480 260 [20] 360 530 190 370 550 240 430 550 > (lm1 <- lm(arr.sd~arr.mean)) Call: lm(formula = arr.sd ~ arr.mean) Coefficients: (Intercept) arr.mean -222.4821 0.2921 > (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) Call: lm(formula = log(arr.sd) ~ log(arr.mean)) Coefficients: (Intercept) log(arr.mean) -32.288 5.226 > (lm2 <- lm(arr.range~arr.mean)) Call: lm(formula = arr.range ~ arr.mean) Coefficients: (Intercept) arr.mean -592.2300 0.7359 > postscript(file="/var/wessaorg/rcomp/tmp/16fe51313866853.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/2herz1313866853.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/3ae9w1313866853.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/42yhi1313866853.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/56rcm1313866853.tab") > > try(system("convert tmp/16fe51313866853.ps tmp/16fe51313866853.png",intern=TRUE)) character(0) > try(system("convert tmp/2herz1313866853.ps tmp/2herz1313866853.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 0.613 0.139 0.850