R version 3.3.2 (2016-10-31) -- "Sincere Pumpkin Patch" Copyright (C) 2016 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu (64-bit) 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(92.81,92.82,92.82,92.88,93.38,93.89,94.1,94.18,94.3,94.31,94.36,94.38,94.38,94.5,94.57,94.89,96.71,97.57,97.88,97.97,98.4,98.51,98.46,98.46,98.48,98.6,98.6,98.71,99.13,99.2,99.3,100.18,101.37,101.77,102.28,102.38,102.35,103.23,105.37,106.62,107,107.24,107.31,107.35,107.42,107.58,107.64,107.64,107.68,108.51,110.37,111.31,111.57,111.66,111.69,111.9,111.95,112.04,112.13,112.14,112.13,113.59,115.03,115.7,116.1,116.12,116.32,116.51,116.63,116.92,116.96,117.15) > par1 = '72' > par1 <- '72' > #'GNU S' R Code compiled by R2WASP v. 1.2.327 (Mon, 30 Nov 2015 07:01:18 +0000) > #Author: root > #To cite this work: Wessa P., (2015), Mean Plot (v1.0.5) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_meanplot.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > # > par1 <- as.numeric(par1) > x <- na.omit(x) > (n <- length(x)) [1] 72 > (np <- floor(n / par1)) [1] 1 > arr <- array(NA,dim=c(par1,np+1)) > darr <- array(NA,dim=c(par1,np+1)) > ari <- array(0,dim=par1) > dx <- diff(x) > j <- 0 > for (i in 1:n) + { + j = j + 1 + ari[j] = ari[j] + 1 + arr[j,ari[j]] <- x[i] + darr[j,ari[j]] <- dx[i] + if (j == par1) j = 0 + } > ari [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [39] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 > arr [,1] [,2] [1,] 92.81 NA [2,] 92.82 NA [3,] 92.82 NA [4,] 92.88 NA [5,] 93.38 NA [6,] 93.89 NA [7,] 94.10 NA [8,] 94.18 NA [9,] 94.30 NA [10,] 94.31 NA [11,] 94.36 NA [12,] 94.38 NA [13,] 94.38 NA [14,] 94.50 NA [15,] 94.57 NA [16,] 94.89 NA [17,] 96.71 NA [18,] 97.57 NA [19,] 97.88 NA [20,] 97.97 NA [21,] 98.40 NA [22,] 98.51 NA [23,] 98.46 NA [24,] 98.46 NA [25,] 98.48 NA [26,] 98.60 NA [27,] 98.60 NA [28,] 98.71 NA [29,] 99.13 NA [30,] 99.20 NA [31,] 99.30 NA [32,] 100.18 NA [33,] 101.37 NA [34,] 101.77 NA [35,] 102.28 NA [36,] 102.38 NA [37,] 102.35 NA [38,] 103.23 NA [39,] 105.37 NA [40,] 106.62 NA [41,] 107.00 NA [42,] 107.24 NA [43,] 107.31 NA [44,] 107.35 NA [45,] 107.42 NA [46,] 107.58 NA [47,] 107.64 NA [48,] 107.64 NA [49,] 107.68 NA [50,] 108.51 NA [51,] 110.37 NA [52,] 111.31 NA [53,] 111.57 NA [54,] 111.66 NA [55,] 111.69 NA [56,] 111.90 NA [57,] 111.95 NA [58,] 112.04 NA [59,] 112.13 NA [60,] 112.14 NA [61,] 112.13 NA [62,] 113.59 NA [63,] 115.03 NA [64,] 115.70 NA [65,] 116.10 NA [66,] 116.12 NA [67,] 116.32 NA [68,] 116.51 NA [69,] 116.63 NA [70,] 116.92 NA [71,] 116.96 NA [72,] 117.15 NA > darr [,1] [,2] [1,] 0.01 NA [2,] 0.00 NA [3,] 0.06 NA [4,] 0.50 NA [5,] 0.51 NA [6,] 0.21 NA [7,] 0.08 NA [8,] 0.12 NA [9,] 0.01 NA [10,] 0.05 NA [11,] 0.02 NA [12,] 0.00 NA [13,] 0.12 NA [14,] 0.07 NA [15,] 0.32 NA [16,] 1.82 NA [17,] 0.86 NA [18,] 0.31 NA [19,] 0.09 NA [20,] 0.43 NA [21,] 0.11 NA [22,] -0.05 NA [23,] 0.00 NA [24,] 0.02 NA [25,] 0.12 NA [26,] 0.00 NA [27,] 0.11 NA [28,] 0.42 NA [29,] 0.07 NA [30,] 0.10 NA [31,] 0.88 NA [32,] 1.19 NA [33,] 0.40 NA [34,] 0.51 NA [35,] 0.10 NA [36,] -0.03 NA [37,] 0.88 NA [38,] 2.14 NA [39,] 1.25 NA [40,] 0.38 NA [41,] 0.24 NA [42,] 0.07 NA [43,] 0.04 NA [44,] 0.07 NA [45,] 0.16 NA [46,] 0.06 NA [47,] 0.00 NA [48,] 0.04 NA [49,] 0.83 NA [50,] 1.86 NA [51,] 0.94 NA [52,] 0.26 NA [53,] 0.09 NA [54,] 0.03 NA [55,] 0.21 NA [56,] 0.05 NA [57,] 0.09 NA [58,] 0.09 NA [59,] 0.01 NA [60,] -0.01 NA [61,] 1.46 NA [62,] 1.44 NA [63,] 0.67 NA [64,] 0.40 NA [65,] 0.02 NA [66,] 0.20 NA [67,] 0.19 NA [68,] 0.12 NA [69,] 0.29 NA [70,] 0.04 NA [71,] 0.19 NA [72,] NA NA > arr.mean <- array(NA,dim=par1) > arr.median <- array(NA,dim=par1) > arr.midrange <- array(NA,dim=par1) > for (j in 1:par1) + { + arr.mean[j] <- mean(arr[j,],na.rm=TRUE) + arr.median[j] <- median(arr[j,],na.rm=TRUE) + arr.midrange[j] <- (quantile(arr[j,],0.75,na.rm=TRUE) + quantile(arr[j,],0.25,na.rm=TRUE)) / 2 + } > overall.mean <- mean(x) > overall.median <- median(x) > overall.midrange <- (quantile(x,0.75) + quantile(x,0.25)) / 2 > postscript(file="/var/wessaorg/rcomp/tmp/1l90m1489519758.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(arr.mean,type='b',ylab='mean',main='Mean Plot',xlab='Periodic Index') > mtext(paste('#blocks = ',np)) > abline(overall.mean,0) > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/20mp61489519758.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(arr.median,type='b',ylab='median',main='Median Plot',xlab='Periodic Index') > mtext(paste('#blocks = ',np)) > abline(overall.median,0) > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/36i951489519758.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(arr.midrange,type='b',ylab='midrange',main='Midrange Plot',xlab='Periodic Index') > mtext(paste('#blocks = ',np)) > abline(overall.midrange,0) > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4ktyi1489519758.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > z <- data.frame(t(arr)) > names(z) <- c(1:par1) > (boxplot(z,notch=TRUE,col='grey',xlab='Periodic Index',ylab='Value',main='Notched Box Plots - Periodic Subseries')) $stats [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [1,] 92.81 92.82 92.82 92.88 93.38 93.89 94.1 94.18 94.3 94.31 94.36 94.38 [2,] 92.81 92.82 92.82 92.88 93.38 93.89 94.1 94.18 94.3 94.31 94.36 94.38 [3,] 92.81 92.82 92.82 92.88 93.38 93.89 94.1 94.18 94.3 94.31 94.36 94.38 [4,] 92.81 92.82 92.82 92.88 93.38 93.89 94.1 94.18 94.3 94.31 94.36 94.38 [5,] 92.81 92.82 92.82 92.88 93.38 93.89 94.1 94.18 94.3 94.31 94.36 94.38 [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [1,] 94.38 94.5 94.57 94.89 96.71 97.57 97.88 97.97 98.4 98.51 98.46 98.46 [2,] 94.38 94.5 94.57 94.89 96.71 97.57 97.88 97.97 98.4 98.51 98.46 98.46 [3,] 94.38 94.5 94.57 94.89 96.71 97.57 97.88 97.97 98.4 98.51 98.46 98.46 [4,] 94.38 94.5 94.57 94.89 96.71 97.57 97.88 97.97 98.4 98.51 98.46 98.46 [5,] 94.38 94.5 94.57 94.89 96.71 97.57 97.88 97.97 98.4 98.51 98.46 98.46 [,25] [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [1,] 98.48 98.6 98.6 98.71 99.13 99.2 99.3 100.18 101.37 101.77 102.28 [2,] 98.48 98.6 98.6 98.71 99.13 99.2 99.3 100.18 101.37 101.77 102.28 [3,] 98.48 98.6 98.6 98.71 99.13 99.2 99.3 100.18 101.37 101.77 102.28 [4,] 98.48 98.6 98.6 98.71 99.13 99.2 99.3 100.18 101.37 101.77 102.28 [5,] 98.48 98.6 98.6 98.71 99.13 99.2 99.3 100.18 101.37 101.77 102.28 [,36] [,37] [,38] [,39] [,40] [,41] [,42] [,43] [,44] [,45] [1,] 102.38 102.35 103.23 105.37 106.62 107 107.24 107.31 107.35 107.42 [2,] 102.38 102.35 103.23 105.37 106.62 107 107.24 107.31 107.35 107.42 [3,] 102.38 102.35 103.23 105.37 106.62 107 107.24 107.31 107.35 107.42 [4,] 102.38 102.35 103.23 105.37 106.62 107 107.24 107.31 107.35 107.42 [5,] 102.38 102.35 103.23 105.37 106.62 107 107.24 107.31 107.35 107.42 [,46] [,47] [,48] [,49] [,50] [,51] [,52] [,53] [,54] [,55] [1,] 107.58 107.64 107.64 107.68 108.51 110.37 111.31 111.57 111.66 111.69 [2,] 107.58 107.64 107.64 107.68 108.51 110.37 111.31 111.57 111.66 111.69 [3,] 107.58 107.64 107.64 107.68 108.51 110.37 111.31 111.57 111.66 111.69 [4,] 107.58 107.64 107.64 107.68 108.51 110.37 111.31 111.57 111.66 111.69 [5,] 107.58 107.64 107.64 107.68 108.51 110.37 111.31 111.57 111.66 111.69 [,56] [,57] [,58] [,59] [,60] [,61] [,62] [,63] [,64] [,65] [,66] [1,] 111.9 111.95 112.04 112.13 112.14 112.13 113.59 115.03 115.7 116.1 116.12 [2,] 111.9 111.95 112.04 112.13 112.14 112.13 113.59 115.03 115.7 116.1 116.12 [3,] 111.9 111.95 112.04 112.13 112.14 112.13 113.59 115.03 115.7 116.1 116.12 [4,] 111.9 111.95 112.04 112.13 112.14 112.13 113.59 115.03 115.7 116.1 116.12 [5,] 111.9 111.95 112.04 112.13 112.14 112.13 113.59 115.03 115.7 116.1 116.12 [,67] [,68] [,69] [,70] [,71] [,72] [1,] 116.32 116.51 116.63 116.92 116.96 117.15 [2,] 116.32 116.51 116.63 116.92 116.96 117.15 [3,] 116.32 116.51 116.63 116.92 116.96 117.15 [4,] 116.32 116.51 116.63 116.92 116.96 117.15 [5,] 116.32 116.51 116.63 116.92 116.96 117.15 $n [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [39] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 $conf [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [1,] 92.81 92.82 92.82 92.88 93.38 93.89 94.1 94.18 94.3 94.31 94.36 94.38 [2,] 92.81 92.82 92.82 92.88 93.38 93.89 94.1 94.18 94.3 94.31 94.36 94.38 [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [1,] 94.38 94.5 94.57 94.89 96.71 97.57 97.88 97.97 98.4 98.51 98.46 98.46 [2,] 94.38 94.5 94.57 94.89 96.71 97.57 97.88 97.97 98.4 98.51 98.46 98.46 [,25] [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [1,] 98.48 98.6 98.6 98.71 99.13 99.2 99.3 100.18 101.37 101.77 102.28 [2,] 98.48 98.6 98.6 98.71 99.13 99.2 99.3 100.18 101.37 101.77 102.28 [,36] [,37] [,38] [,39] [,40] [,41] [,42] [,43] [,44] [,45] [1,] 102.38 102.35 103.23 105.37 106.62 107 107.24 107.31 107.35 107.42 [2,] 102.38 102.35 103.23 105.37 106.62 107 107.24 107.31 107.35 107.42 [,46] [,47] [,48] [,49] [,50] [,51] [,52] [,53] [,54] [,55] [1,] 107.58 107.64 107.64 107.68 108.51 110.37 111.31 111.57 111.66 111.69 [2,] 107.58 107.64 107.64 107.68 108.51 110.37 111.31 111.57 111.66 111.69 [,56] [,57] [,58] [,59] [,60] [,61] [,62] [,63] [,64] [,65] [,66] [1,] 111.9 111.95 112.04 112.13 112.14 112.13 113.59 115.03 115.7 116.1 116.12 [2,] 111.9 111.95 112.04 112.13 112.14 112.13 113.59 115.03 115.7 116.1 116.12 [,67] [,68] [,69] [,70] [,71] [,72] [1,] 116.32 116.51 116.63 116.92 116.96 117.15 [2,] 116.32 116.51 116.63 116.92 116.96 117.15 $out numeric(0) $group numeric(0) $names [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14" "15" [16] "16" "17" "18" "19" "20" "21" "22" "23" "24" "25" "26" "27" "28" "29" "30" [31] "31" "32" "33" "34" "35" "36" "37" "38" "39" "40" "41" "42" "43" "44" "45" [46] "46" "47" "48" "49" "50" "51" "52" "53" "54" "55" "56" "57" "58" "59" "60" [61] "61" "62" "63" "64" "65" "66" "67" "68" "69" "70" "71" "72" > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/58g621489519758.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > z <- data.frame(t(darr)) > names(z) <- c(1:par1) > (boxplot(z,notch=TRUE,col='grey',xlab='Periodic Index',ylab='Value',main='Notched Box Plots - Differenced Periodic Subseries')) $stats [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] 0.01 0 0.06 0.5 0.51 0.21 0.08 0.12 0.01 0.05 0.02 0 0.12 0.07 [2,] 0.01 0 0.06 0.5 0.51 0.21 0.08 0.12 0.01 0.05 0.02 0 0.12 0.07 [3,] 0.01 0 0.06 0.5 0.51 0.21 0.08 0.12 0.01 0.05 0.02 0 0.12 0.07 [4,] 0.01 0 0.06 0.5 0.51 0.21 0.08 0.12 0.01 0.05 0.02 0 0.12 0.07 [5,] 0.01 0 0.06 0.5 0.51 0.21 0.08 0.12 0.01 0.05 0.02 0 0.12 0.07 [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] [1,] 0.32 1.82 0.86 0.31 0.09 0.43 0.11 -0.05 0 0.02 0.12 0 [2,] 0.32 1.82 0.86 0.31 0.09 0.43 0.11 -0.05 0 0.02 0.12 0 [3,] 0.32 1.82 0.86 0.31 0.09 0.43 0.11 -0.05 0 0.02 0.12 0 [4,] 0.32 1.82 0.86 0.31 0.09 0.43 0.11 -0.05 0 0.02 0.12 0 [5,] 0.32 1.82 0.86 0.31 0.09 0.43 0.11 -0.05 0 0.02 0.12 0 [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37] [,38] [1,] 0.11 0.42 0.07 0.1 0.88 1.19 0.4 0.51 0.1 -0.03 0.88 2.14 [2,] 0.11 0.42 0.07 0.1 0.88 1.19 0.4 0.51 0.1 -0.03 0.88 2.14 [3,] 0.11 0.42 0.07 0.1 0.88 1.19 0.4 0.51 0.1 -0.03 0.88 2.14 [4,] 0.11 0.42 0.07 0.1 0.88 1.19 0.4 0.51 0.1 -0.03 0.88 2.14 [5,] 0.11 0.42 0.07 0.1 0.88 1.19 0.4 0.51 0.1 -0.03 0.88 2.14 [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47] [,48] [,49] [,50] [1,] 1.25 0.38 0.24 0.07 0.04 0.07 0.16 0.06 0 0.04 0.83 1.86 [2,] 1.25 0.38 0.24 0.07 0.04 0.07 0.16 0.06 0 0.04 0.83 1.86 [3,] 1.25 0.38 0.24 0.07 0.04 0.07 0.16 0.06 0 0.04 0.83 1.86 [4,] 1.25 0.38 0.24 0.07 0.04 0.07 0.16 0.06 0 0.04 0.83 1.86 [5,] 1.25 0.38 0.24 0.07 0.04 0.07 0.16 0.06 0 0.04 0.83 1.86 [,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58] [,59] [,60] [,61] [,62] [1,] 0.94 0.26 0.09 0.03 0.21 0.05 0.09 0.09 0.01 -0.01 1.46 1.44 [2,] 0.94 0.26 0.09 0.03 0.21 0.05 0.09 0.09 0.01 -0.01 1.46 1.44 [3,] 0.94 0.26 0.09 0.03 0.21 0.05 0.09 0.09 0.01 -0.01 1.46 1.44 [4,] 0.94 0.26 0.09 0.03 0.21 0.05 0.09 0.09 0.01 -0.01 1.46 1.44 [5,] 0.94 0.26 0.09 0.03 0.21 0.05 0.09 0.09 0.01 -0.01 1.46 1.44 [,63] [,64] [,65] [,66] [,67] [,68] [,69] [,70] [,71] [,72] [1,] 0.67 0.4 0.02 0.2 0.19 0.12 0.29 0.04 0.19 NA [2,] 0.67 0.4 0.02 0.2 0.19 0.12 0.29 0.04 0.19 NA [3,] 0.67 0.4 0.02 0.2 0.19 0.12 0.29 0.04 0.19 NA [4,] 0.67 0.4 0.02 0.2 0.19 0.12 0.29 0.04 0.19 NA [5,] 0.67 0.4 0.02 0.2 0.19 0.12 0.29 0.04 0.19 NA $n [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [39] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 $conf [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14] [1,] 0.01 0 0.06 0.5 0.51 0.21 0.08 0.12 0.01 0.05 0.02 0 0.12 0.07 [2,] 0.01 0 0.06 0.5 0.51 0.21 0.08 0.12 0.01 0.05 0.02 0 0.12 0.07 [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26] [1,] 0.32 1.82 0.86 0.31 0.09 0.43 0.11 -0.05 0 0.02 0.12 0 [2,] 0.32 1.82 0.86 0.31 0.09 0.43 0.11 -0.05 0 0.02 0.12 0 [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37] [,38] [1,] 0.11 0.42 0.07 0.1 0.88 1.19 0.4 0.51 0.1 -0.03 0.88 2.14 [2,] 0.11 0.42 0.07 0.1 0.88 1.19 0.4 0.51 0.1 -0.03 0.88 2.14 [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47] [,48] [,49] [,50] [1,] 1.25 0.38 0.24 0.07 0.04 0.07 0.16 0.06 0 0.04 0.83 1.86 [2,] 1.25 0.38 0.24 0.07 0.04 0.07 0.16 0.06 0 0.04 0.83 1.86 [,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58] [,59] [,60] [,61] [,62] [1,] 0.94 0.26 0.09 0.03 0.21 0.05 0.09 0.09 0.01 -0.01 1.46 1.44 [2,] 0.94 0.26 0.09 0.03 0.21 0.05 0.09 0.09 0.01 -0.01 1.46 1.44 [,63] [,64] [,65] [,66] [,67] [,68] [,69] [,70] [,71] [,72] [1,] 0.67 0.4 0.02 0.2 0.19 0.12 0.29 0.04 0.19 NA [2,] 0.67 0.4 0.02 0.2 0.19 0.12 0.29 0.04 0.19 NA $out numeric(0) $group numeric(0) $names [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" "13" "14" "15" [16] "16" "17" "18" "19" "20" "21" "22" "23" "24" "25" "26" "27" "28" "29" "30" [31] "31" "32" "33" "34" "35" "36" "37" "38" "39" "40" "41" "42" "43" "44" "45" [46] "46" "47" "48" "49" "50" "51" "52" "53" "54" "55" "56" "57" "58" "59" "60" [61] "61" "62" "63" "64" "65" "66" "67" "68" "69" "70" "71" "72" > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/6502k1489519758.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > z <- data.frame(arr) > names(z) <- c(1:np) > (boxplot(z,notch=TRUE,col='grey',xlab='Block Index',ylab='Value',main='Notched Box Plots - Sequential Blocks')) $stats [,1] [,2] [1,] 92.810 NA [2,] 97.725 NA [3,] 102.365 NA [4,] 111.675 NA [5,] 117.150 NA $n [1] 72 0 $conf [,1] [,2] [1,] 99.76744 NA [2,] 104.96256 NA $out numeric(0) $group numeric(0) $names [1] "1" NA > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/7bz201489519758.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > z <- data.frame(cbind(arr.mean,arr.median,arr.midrange)) > names(z) <- list('mean','median','midrange') > (boxplot(z,notch=TRUE,col='grey',ylab='Overall Central Tendency',main='Notched Box Plots')) $stats [,1] [,2] [,3] [1,] 92.810 92.810 92.810 [2,] 97.725 97.725 97.725 [3,] 102.365 102.365 102.365 [4,] 111.675 111.675 111.675 [5,] 117.150 117.150 117.150 $n [1] 72 72 72 $conf [,1] [,2] [,3] [1,] 99.76744 99.76744 99.76744 [2,] 104.96256 104.96256 104.96256 $out numeric(0) $group numeric(0) $names [1] "mean" "median" "midrange" > dev.off() null device 1 > > try(system("convert tmp/1l90m1489519758.ps tmp/1l90m1489519758.png",intern=TRUE)) character(0) > try(system("convert tmp/20mp61489519758.ps tmp/20mp61489519758.png",intern=TRUE)) character(0) > try(system("convert tmp/36i951489519758.ps tmp/36i951489519758.png",intern=TRUE)) character(0) > try(system("convert tmp/4ktyi1489519758.ps tmp/4ktyi1489519758.png",intern=TRUE)) character(0) > try(system("convert tmp/58g621489519758.ps tmp/58g621489519758.png",intern=TRUE)) character(0) > try(system("convert tmp/6502k1489519758.ps tmp/6502k1489519758.png",intern=TRUE)) character(0) > try(system("convert tmp/7bz201489519758.ps tmp/7bz201489519758.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.572 0.215 2.836