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Type 'q()' to quit R. > x <- c(989,1215,2911,2372,2013,2050,1580,1407,903,709,490,206,1101,1189,2877,2489,2145,1837,1613,1296,849,642,475,224,920,1263,2999,2988,2163,2391,1556,1089,976,626,392,203,1052,1034,2353,3075,2309,2009,1464,1099,1035,792,406,187,862,822,2128,2264,1987,1728,1311,1152,945,704,526,361,1035,869,2698,2367,1926,1843,1404,1314,1007,865,587,339,1143,1807,2380,2337,2117,1789,1569,1305,952,810,473,278,993,1038,2257,2284,1747,1515,1233,882,1029,707,391,239,592,692,2127,1854,1468,1535,1203,880,821,604,315,139,528,654,1895,1598,1519,1242,1027,762,735,485,281,131,651,611,1898,1385,1047,1008,843,833,711,444,315,204,473,566,1611,1301,1154,1158,862,801,559,404,223,158,548,647,1757,1326,1308,1175,992,808,758,553,310,146) > 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] 156 > (np <- floor(n / par1)) [1] 13 > 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] [1,] 989 1101 920 1052 862 1035 1143 993 592 528 651 473 548 [2,] 1215 1189 1263 1034 822 869 1807 1038 692 654 611 566 647 [3,] 2911 2877 2999 2353 2128 2698 2380 2257 2127 1895 1898 1611 1757 [4,] 2372 2489 2988 3075 2264 2367 2337 2284 1854 1598 1385 1301 1326 [5,] 2013 2145 2163 2309 1987 1926 2117 1747 1468 1519 1047 1154 1308 [6,] 2050 1837 2391 2009 1728 1843 1789 1515 1535 1242 1008 1158 1175 [7,] 1580 1613 1556 1464 1311 1404 1569 1233 1203 1027 843 862 992 [8,] 1407 1296 1089 1099 1152 1314 1305 882 880 762 833 801 808 [9,] 903 849 976 1035 945 1007 952 1029 821 735 711 559 758 [10,] 709 642 626 792 704 865 810 707 604 485 444 404 553 [11,] 490 475 392 406 526 587 473 391 315 281 315 223 310 [12,] 206 224 203 187 361 339 278 239 139 131 204 158 146 > 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] 1403.7500 1394.7500 1463.8333 1401.2500 1232.5000 1354.5000 1413.3333 [8] 1192.9167 1019.1667 904.7500 829.1667 772.5000 860.6667 > arr.sd [1] 811.2743 821.3064 962.5652 864.6086 648.0565 720.9802 703.1065 654.4765 [9] 619.1362 554.7422 469.8019 455.1370 467.2432 > arr.range [1] 2705 2653 2796 2888 1903 2359 2102 2045 1988 1764 1694 1453 1611 > (lm1 <- lm(arr.sd~arr.mean)) Call: lm(formula = arr.sd ~ arr.mean) Coefficients: (Intercept) arr.mean -8.2970 0.5813 > (lnlm1 <- lm(log(arr.sd)~log(arr.mean))) Call: lm(formula = log(arr.sd) ~ log(arr.mean)) Coefficients: (Intercept) log(arr.mean) -0.4627 0.9865 > (lm2 <- lm(arr.range~arr.mean)) Call: lm(formula = arr.range ~ arr.mean) Coefficients: (Intercept) arr.mean 202.804 1.661 > postscript(file="/var/wessaorg/rcomp/tmp/1tqr31449330733.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=13.888888888889,height=8.3333333333333) > 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/2c38s1449330733.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=13.888888888889,height=8.3333333333333) > 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/37maj1449330733.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/4nem81449330733.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/5jea21449330733.tab") > > try(system("convert tmp/1tqr31449330733.ps tmp/1tqr31449330733.png",intern=TRUE)) character(0) > try(system("convert tmp/2c38s1449330733.ps tmp/2c38s1449330733.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.032 0.188 1.225