R version 3.2.3 (2015-12-10) -- "Wooden Christmas-Tree" Copyright (C) 2015 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(102.96,107.5,103.5,107.36,103.59,99.04,93.19,93.28,104.48,93.22,106.43,95.25,113.86,101.6,93.83,119.15,95.81,92.14,97.92,86.57,92.39,93.58,101.66,102.37,104.47,87.44,88.74,100.52,101.26,94.76,95.97,78.36,81.6,90.96,90.16,95.01,114.54,105.85,104.14,106.94,94.27,84.31,78.89,69.28,67.15,75.21,77.74,77.86,111.44,107.1,117.78,116.71,97.74,88.71,90.67,83.69,90.61,85.59,93.53,103.14,112.93,108.31,99.52,96.13,90.74,85.08,86.62,76.78,74.59,79.62,90.55,91.17,98.19,109.92,109.43,104.43,102.49,98.68,97.15,92.22,84.55,94.1,95.94,98.17,106.92,104.86,108.51,116.13,109.21,110,98.57,89.41,86.52,83.37,89.42,97.08,106.25,101.33,98.06,103.66,88.34,86.5,91,75.06,81.39,77.88,89.28,93.92,103.45,106.15,98.29,113.29,101.54,94.54,90.92,86.86,90.69,99.29,99.51,94.15) > par1 = '120' > par1 <- '120' > #'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] 120 > (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 [38] 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 [75] 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 [112] 1 1 1 1 1 1 1 1 1 > arr [,1] [,2] [1,] 102.96 NA [2,] 107.50 NA [3,] 103.50 NA [4,] 107.36 NA [5,] 103.59 NA [6,] 99.04 NA [7,] 93.19 NA [8,] 93.28 NA [9,] 104.48 NA [10,] 93.22 NA [11,] 106.43 NA [12,] 95.25 NA [13,] 113.86 NA [14,] 101.60 NA [15,] 93.83 NA [16,] 119.15 NA [17,] 95.81 NA [18,] 92.14 NA [19,] 97.92 NA [20,] 86.57 NA [21,] 92.39 NA [22,] 93.58 NA [23,] 101.66 NA [24,] 102.37 NA [25,] 104.47 NA [26,] 87.44 NA [27,] 88.74 NA [28,] 100.52 NA [29,] 101.26 NA [30,] 94.76 NA [31,] 95.97 NA [32,] 78.36 NA [33,] 81.60 NA [34,] 90.96 NA [35,] 90.16 NA [36,] 95.01 NA [37,] 114.54 NA [38,] 105.85 NA [39,] 104.14 NA [40,] 106.94 NA [41,] 94.27 NA [42,] 84.31 NA [43,] 78.89 NA [44,] 69.28 NA [45,] 67.15 NA [46,] 75.21 NA [47,] 77.74 NA [48,] 77.86 NA [49,] 111.44 NA [50,] 107.10 NA [51,] 117.78 NA [52,] 116.71 NA [53,] 97.74 NA [54,] 88.71 NA [55,] 90.67 NA [56,] 83.69 NA [57,] 90.61 NA [58,] 85.59 NA [59,] 93.53 NA [60,] 103.14 NA [61,] 112.93 NA [62,] 108.31 NA [63,] 99.52 NA [64,] 96.13 NA [65,] 90.74 NA [66,] 85.08 NA [67,] 86.62 NA [68,] 76.78 NA [69,] 74.59 NA [70,] 79.62 NA [71,] 90.55 NA [72,] 91.17 NA [73,] 98.19 NA [74,] 109.92 NA [75,] 109.43 NA [76,] 104.43 NA [77,] 102.49 NA [78,] 98.68 NA [79,] 97.15 NA [80,] 92.22 NA [81,] 84.55 NA [82,] 94.10 NA [83,] 95.94 NA [84,] 98.17 NA [85,] 106.92 NA [86,] 104.86 NA [87,] 108.51 NA [88,] 116.13 NA [89,] 109.21 NA [90,] 110.00 NA [91,] 98.57 NA [92,] 89.41 NA [93,] 86.52 NA [94,] 83.37 NA [95,] 89.42 NA [96,] 97.08 NA [97,] 106.25 NA [98,] 101.33 NA [99,] 98.06 NA [100,] 103.66 NA [101,] 88.34 NA [102,] 86.50 NA [103,] 91.00 NA [104,] 75.06 NA [105,] 81.39 NA [106,] 77.88 NA [107,] 89.28 NA [108,] 93.92 NA [109,] 103.45 NA [110,] 106.15 NA [111,] 98.29 NA [112,] 113.29 NA [113,] 101.54 NA [114,] 94.54 NA [115,] 90.92 NA [116,] 86.86 NA [117,] 90.69 NA [118,] 99.29 NA [119,] 99.51 NA [120,] 94.15 NA > darr [,1] [,2] [1,] 4.54 NA [2,] -4.00 NA [3,] 3.86 NA [4,] -3.77 NA [5,] -4.55 NA [6,] -5.85 NA [7,] 0.09 NA [8,] 11.20 NA [9,] -11.26 NA [10,] 13.21 NA [11,] -11.18 NA [12,] 18.61 NA [13,] -12.26 NA [14,] -7.77 NA [15,] 25.32 NA [16,] -23.34 NA [17,] -3.67 NA [18,] 5.78 NA [19,] -11.35 NA [20,] 5.82 NA [21,] 1.19 NA [22,] 8.08 NA [23,] 0.71 NA [24,] 2.10 NA [25,] -17.03 NA [26,] 1.30 NA [27,] 11.78 NA [28,] 0.74 NA [29,] -6.50 NA [30,] 1.21 NA [31,] -17.61 NA [32,] 3.24 NA [33,] 9.36 NA [34,] -0.80 NA [35,] 4.85 NA [36,] 19.53 NA [37,] -8.69 NA [38,] -1.71 NA [39,] 2.80 NA [40,] -12.67 NA [41,] -9.96 NA [42,] -5.42 NA [43,] -9.61 NA [44,] -2.13 NA [45,] 8.06 NA [46,] 2.53 NA [47,] 0.12 NA [48,] 33.58 NA [49,] -4.34 NA [50,] 10.68 NA [51,] -1.07 NA [52,] -18.97 NA [53,] -9.03 NA [54,] 1.96 NA [55,] -6.98 NA [56,] 6.92 NA [57,] -5.02 NA [58,] 7.94 NA [59,] 9.61 NA [60,] 9.79 NA [61,] -4.62 NA [62,] -8.79 NA [63,] -3.39 NA [64,] -5.39 NA [65,] -5.66 NA [66,] 1.54 NA [67,] -9.84 NA [68,] -2.19 NA [69,] 5.03 NA [70,] 10.93 NA [71,] 0.62 NA [72,] 7.02 NA [73,] 11.73 NA [74,] -0.49 NA [75,] -5.00 NA [76,] -1.94 NA [77,] -3.81 NA [78,] -1.53 NA [79,] -4.93 NA [80,] -7.67 NA [81,] 9.55 NA [82,] 1.84 NA [83,] 2.23 NA [84,] 8.75 NA [85,] -2.06 NA [86,] 3.65 NA [87,] 7.62 NA [88,] -6.92 NA [89,] 0.79 NA [90,] -11.43 NA [91,] -9.16 NA [92,] -2.89 NA [93,] -3.15 NA [94,] 6.05 NA [95,] 7.66 NA [96,] 9.17 NA [97,] -4.92 NA [98,] -3.27 NA [99,] 5.60 NA [100,] -15.32 NA [101,] -1.84 NA [102,] 4.50 NA [103,] -15.94 NA [104,] 6.33 NA [105,] -3.51 NA [106,] 11.40 NA [107,] 4.64 NA [108,] 9.53 NA [109,] 2.70 NA [110,] -7.86 NA [111,] 15.00 NA [112,] -11.75 NA [113,] -7.00 NA [114,] -3.62 NA [115,] -4.06 NA [116,] 3.83 NA [117,] 8.60 NA [118,] 0.22 NA [119,] -5.36 NA [120,] 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/14aky1457193201.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/2qhl31457193201.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/3zaiy1457193201.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/4nk6m1457193201.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] [1,] 102.96 107.5 103.5 107.36 103.59 99.04 93.19 93.28 104.48 93.22 106.43 [2,] 102.96 107.5 103.5 107.36 103.59 99.04 93.19 93.28 104.48 93.22 106.43 [3,] 102.96 107.5 103.5 107.36 103.59 99.04 93.19 93.28 104.48 93.22 106.43 [4,] 102.96 107.5 103.5 107.36 103.59 99.04 93.19 93.28 104.48 93.22 106.43 [5,] 102.96 107.5 103.5 107.36 103.59 99.04 93.19 93.28 104.48 93.22 106.43 [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [1,] 95.25 113.86 101.6 93.83 119.15 95.81 92.14 97.92 86.57 92.39 93.58 101.66 [2,] 95.25 113.86 101.6 93.83 119.15 95.81 92.14 97.92 86.57 92.39 93.58 101.66 [3,] 95.25 113.86 101.6 93.83 119.15 95.81 92.14 97.92 86.57 92.39 93.58 101.66 [4,] 95.25 113.86 101.6 93.83 119.15 95.81 92.14 97.92 86.57 92.39 93.58 101.66 [5,] 95.25 113.86 101.6 93.83 119.15 95.81 92.14 97.92 86.57 92.39 93.58 101.66 [,24] [,25] [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [1,] 102.37 104.47 87.44 88.74 100.52 101.26 94.76 95.97 78.36 81.6 90.96 [2,] 102.37 104.47 87.44 88.74 100.52 101.26 94.76 95.97 78.36 81.6 90.96 [3,] 102.37 104.47 87.44 88.74 100.52 101.26 94.76 95.97 78.36 81.6 90.96 [4,] 102.37 104.47 87.44 88.74 100.52 101.26 94.76 95.97 78.36 81.6 90.96 [5,] 102.37 104.47 87.44 88.74 100.52 101.26 94.76 95.97 78.36 81.6 90.96 [,35] [,36] [,37] [,38] [,39] [,40] [,41] [,42] [,43] [,44] [,45] [1,] 90.16 95.01 114.54 105.85 104.14 106.94 94.27 84.31 78.89 69.28 67.15 [2,] 90.16 95.01 114.54 105.85 104.14 106.94 94.27 84.31 78.89 69.28 67.15 [3,] 90.16 95.01 114.54 105.85 104.14 106.94 94.27 84.31 78.89 69.28 67.15 [4,] 90.16 95.01 114.54 105.85 104.14 106.94 94.27 84.31 78.89 69.28 67.15 [5,] 90.16 95.01 114.54 105.85 104.14 106.94 94.27 84.31 78.89 69.28 67.15 [,46] [,47] [,48] [,49] [,50] [,51] [,52] [,53] [,54] [,55] [,56] [,57] [1,] 75.21 77.74 77.86 111.44 107.1 117.78 116.71 97.74 88.71 90.67 83.69 90.61 [2,] 75.21 77.74 77.86 111.44 107.1 117.78 116.71 97.74 88.71 90.67 83.69 90.61 [3,] 75.21 77.74 77.86 111.44 107.1 117.78 116.71 97.74 88.71 90.67 83.69 90.61 [4,] 75.21 77.74 77.86 111.44 107.1 117.78 116.71 97.74 88.71 90.67 83.69 90.61 [5,] 75.21 77.74 77.86 111.44 107.1 117.78 116.71 97.74 88.71 90.67 83.69 90.61 [,58] [,59] [,60] [,61] [,62] [,63] [,64] [,65] [,66] [,67] [,68] [,69] [1,] 85.59 93.53 103.14 112.93 108.31 99.52 96.13 90.74 85.08 86.62 76.78 74.59 [2,] 85.59 93.53 103.14 112.93 108.31 99.52 96.13 90.74 85.08 86.62 76.78 74.59 [3,] 85.59 93.53 103.14 112.93 108.31 99.52 96.13 90.74 85.08 86.62 76.78 74.59 [4,] 85.59 93.53 103.14 112.93 108.31 99.52 96.13 90.74 85.08 86.62 76.78 74.59 [5,] 85.59 93.53 103.14 112.93 108.31 99.52 96.13 90.74 85.08 86.62 76.78 74.59 [,70] [,71] [,72] [,73] [,74] [,75] [,76] [,77] [,78] [,79] [,80] [1,] 79.62 90.55 91.17 98.19 109.92 109.43 104.43 102.49 98.68 97.15 92.22 [2,] 79.62 90.55 91.17 98.19 109.92 109.43 104.43 102.49 98.68 97.15 92.22 [3,] 79.62 90.55 91.17 98.19 109.92 109.43 104.43 102.49 98.68 97.15 92.22 [4,] 79.62 90.55 91.17 98.19 109.92 109.43 104.43 102.49 98.68 97.15 92.22 [5,] 79.62 90.55 91.17 98.19 109.92 109.43 104.43 102.49 98.68 97.15 92.22 [,81] [,82] [,83] [,84] [,85] [,86] [,87] [,88] [,89] [,90] [,91] [1,] 84.55 94.1 95.94 98.17 106.92 104.86 108.51 116.13 109.21 110 98.57 [2,] 84.55 94.1 95.94 98.17 106.92 104.86 108.51 116.13 109.21 110 98.57 [3,] 84.55 94.1 95.94 98.17 106.92 104.86 108.51 116.13 109.21 110 98.57 [4,] 84.55 94.1 95.94 98.17 106.92 104.86 108.51 116.13 109.21 110 98.57 [5,] 84.55 94.1 95.94 98.17 106.92 104.86 108.51 116.13 109.21 110 98.57 [,92] [,93] [,94] [,95] [,96] [,97] [,98] [,99] [,100] [,101] [,102] [1,] 89.41 86.52 83.37 89.42 97.08 106.25 101.33 98.06 103.66 88.34 86.5 [2,] 89.41 86.52 83.37 89.42 97.08 106.25 101.33 98.06 103.66 88.34 86.5 [3,] 89.41 86.52 83.37 89.42 97.08 106.25 101.33 98.06 103.66 88.34 86.5 [4,] 89.41 86.52 83.37 89.42 97.08 106.25 101.33 98.06 103.66 88.34 86.5 [5,] 89.41 86.52 83.37 89.42 97.08 106.25 101.33 98.06 103.66 88.34 86.5 [,103] [,104] [,105] [,106] [,107] [,108] [,109] [,110] [,111] [,112] [1,] 91 75.06 81.39 77.88 89.28 93.92 103.45 106.15 98.29 113.29 [2,] 91 75.06 81.39 77.88 89.28 93.92 103.45 106.15 98.29 113.29 [3,] 91 75.06 81.39 77.88 89.28 93.92 103.45 106.15 98.29 113.29 [4,] 91 75.06 81.39 77.88 89.28 93.92 103.45 106.15 98.29 113.29 [5,] 91 75.06 81.39 77.88 89.28 93.92 103.45 106.15 98.29 113.29 [,113] [,114] [,115] [,116] [,117] [,118] [,119] [,120] [1,] 101.54 94.54 90.92 86.86 90.69 99.29 99.51 94.15 [2,] 101.54 94.54 90.92 86.86 90.69 99.29 99.51 94.15 [3,] 101.54 94.54 90.92 86.86 90.69 99.29 99.51 94.15 [4,] 101.54 94.54 90.92 86.86 90.69 99.29 99.51 94.15 [5,] 101.54 94.54 90.92 86.86 90.69 99.29 99.51 94.15 $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 [38] 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 [75] 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 [112] 1 1 1 1 1 1 1 1 1 $conf [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [1,] 102.96 107.5 103.5 107.36 103.59 99.04 93.19 93.28 104.48 93.22 106.43 [2,] 102.96 107.5 103.5 107.36 103.59 99.04 93.19 93.28 104.48 93.22 106.43 [,12] [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [1,] 95.25 113.86 101.6 93.83 119.15 95.81 92.14 97.92 86.57 92.39 93.58 101.66 [2,] 95.25 113.86 101.6 93.83 119.15 95.81 92.14 97.92 86.57 92.39 93.58 101.66 [,24] [,25] [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [1,] 102.37 104.47 87.44 88.74 100.52 101.26 94.76 95.97 78.36 81.6 90.96 [2,] 102.37 104.47 87.44 88.74 100.52 101.26 94.76 95.97 78.36 81.6 90.96 [,35] [,36] [,37] [,38] [,39] [,40] [,41] [,42] [,43] [,44] [,45] [1,] 90.16 95.01 114.54 105.85 104.14 106.94 94.27 84.31 78.89 69.28 67.15 [2,] 90.16 95.01 114.54 105.85 104.14 106.94 94.27 84.31 78.89 69.28 67.15 [,46] [,47] [,48] [,49] [,50] [,51] [,52] [,53] [,54] [,55] [,56] [,57] [1,] 75.21 77.74 77.86 111.44 107.1 117.78 116.71 97.74 88.71 90.67 83.69 90.61 [2,] 75.21 77.74 77.86 111.44 107.1 117.78 116.71 97.74 88.71 90.67 83.69 90.61 [,58] [,59] [,60] [,61] [,62] [,63] [,64] [,65] [,66] [,67] [,68] [,69] [1,] 85.59 93.53 103.14 112.93 108.31 99.52 96.13 90.74 85.08 86.62 76.78 74.59 [2,] 85.59 93.53 103.14 112.93 108.31 99.52 96.13 90.74 85.08 86.62 76.78 74.59 [,70] [,71] [,72] [,73] [,74] [,75] [,76] [,77] [,78] [,79] [,80] [1,] 79.62 90.55 91.17 98.19 109.92 109.43 104.43 102.49 98.68 97.15 92.22 [2,] 79.62 90.55 91.17 98.19 109.92 109.43 104.43 102.49 98.68 97.15 92.22 [,81] [,82] [,83] [,84] [,85] [,86] [,87] [,88] [,89] [,90] [,91] [1,] 84.55 94.1 95.94 98.17 106.92 104.86 108.51 116.13 109.21 110 98.57 [2,] 84.55 94.1 95.94 98.17 106.92 104.86 108.51 116.13 109.21 110 98.57 [,92] [,93] [,94] [,95] [,96] [,97] [,98] [,99] [,100] [,101] [,102] [1,] 89.41 86.52 83.37 89.42 97.08 106.25 101.33 98.06 103.66 88.34 86.5 [2,] 89.41 86.52 83.37 89.42 97.08 106.25 101.33 98.06 103.66 88.34 86.5 [,103] [,104] [,105] [,106] [,107] [,108] [,109] [,110] [,111] [,112] [1,] 91 75.06 81.39 77.88 89.28 93.92 103.45 106.15 98.29 113.29 [2,] 91 75.06 81.39 77.88 89.28 93.92 103.45 106.15 98.29 113.29 [,113] [,114] [,115] [,116] [,117] [,118] [,119] [,120] [1,] 101.54 94.54 90.92 86.86 90.69 99.29 99.51 94.15 [2,] 101.54 94.54 90.92 86.86 90.69 99.29 99.51 94.15 $out numeric(0) $group numeric(0) $names [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" [13] "13" "14" "15" "16" "17" "18" "19" "20" "21" "22" "23" "24" [25] "25" "26" "27" "28" "29" "30" "31" "32" "33" "34" "35" "36" [37] "37" "38" "39" "40" "41" "42" "43" "44" "45" "46" "47" "48" [49] "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" [73] "73" "74" "75" "76" "77" "78" "79" "80" "81" "82" "83" "84" [85] "85" "86" "87" "88" "89" "90" "91" "92" "93" "94" "95" "96" [97] "97" "98" "99" "100" "101" "102" "103" "104" "105" "106" "107" "108" [109] "109" "110" "111" "112" "113" "114" "115" "116" "117" "118" "119" "120" > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5qzk21457193201.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] [1,] 4.54 -4 3.86 -3.77 -4.55 -5.85 0.09 11.2 -11.26 13.21 -11.18 18.61 [2,] 4.54 -4 3.86 -3.77 -4.55 -5.85 0.09 11.2 -11.26 13.21 -11.18 18.61 [3,] 4.54 -4 3.86 -3.77 -4.55 -5.85 0.09 11.2 -11.26 13.21 -11.18 18.61 [4,] 4.54 -4 3.86 -3.77 -4.55 -5.85 0.09 11.2 -11.26 13.21 -11.18 18.61 [5,] 4.54 -4 3.86 -3.77 -4.55 -5.85 0.09 11.2 -11.26 13.21 -11.18 18.61 [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [1,] -12.26 -7.77 25.32 -23.34 -3.67 5.78 -11.35 5.82 1.19 8.08 0.71 2.1 [2,] -12.26 -7.77 25.32 -23.34 -3.67 5.78 -11.35 5.82 1.19 8.08 0.71 2.1 [3,] -12.26 -7.77 25.32 -23.34 -3.67 5.78 -11.35 5.82 1.19 8.08 0.71 2.1 [4,] -12.26 -7.77 25.32 -23.34 -3.67 5.78 -11.35 5.82 1.19 8.08 0.71 2.1 [5,] -12.26 -7.77 25.32 -23.34 -3.67 5.78 -11.35 5.82 1.19 8.08 0.71 2.1 [,25] [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [1,] -17.03 1.3 11.78 0.74 -6.5 1.21 -17.61 3.24 9.36 -0.8 4.85 19.53 [2,] -17.03 1.3 11.78 0.74 -6.5 1.21 -17.61 3.24 9.36 -0.8 4.85 19.53 [3,] -17.03 1.3 11.78 0.74 -6.5 1.21 -17.61 3.24 9.36 -0.8 4.85 19.53 [4,] -17.03 1.3 11.78 0.74 -6.5 1.21 -17.61 3.24 9.36 -0.8 4.85 19.53 [5,] -17.03 1.3 11.78 0.74 -6.5 1.21 -17.61 3.24 9.36 -0.8 4.85 19.53 [,37] [,38] [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47] [,48] [1,] -8.69 -1.71 2.8 -12.67 -9.96 -5.42 -9.61 -2.13 8.06 2.53 0.12 33.58 [2,] -8.69 -1.71 2.8 -12.67 -9.96 -5.42 -9.61 -2.13 8.06 2.53 0.12 33.58 [3,] -8.69 -1.71 2.8 -12.67 -9.96 -5.42 -9.61 -2.13 8.06 2.53 0.12 33.58 [4,] -8.69 -1.71 2.8 -12.67 -9.96 -5.42 -9.61 -2.13 8.06 2.53 0.12 33.58 [5,] -8.69 -1.71 2.8 -12.67 -9.96 -5.42 -9.61 -2.13 8.06 2.53 0.12 33.58 [,49] [,50] [,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58] [,59] [,60] [1,] -4.34 10.68 -1.07 -18.97 -9.03 1.96 -6.98 6.92 -5.02 7.94 9.61 9.79 [2,] -4.34 10.68 -1.07 -18.97 -9.03 1.96 -6.98 6.92 -5.02 7.94 9.61 9.79 [3,] -4.34 10.68 -1.07 -18.97 -9.03 1.96 -6.98 6.92 -5.02 7.94 9.61 9.79 [4,] -4.34 10.68 -1.07 -18.97 -9.03 1.96 -6.98 6.92 -5.02 7.94 9.61 9.79 [5,] -4.34 10.68 -1.07 -18.97 -9.03 1.96 -6.98 6.92 -5.02 7.94 9.61 9.79 [,61] [,62] [,63] [,64] [,65] [,66] [,67] [,68] [,69] [,70] [,71] [,72] [1,] -4.62 -8.79 -3.39 -5.39 -5.66 1.54 -9.84 -2.19 5.03 10.93 0.62 7.02 [2,] -4.62 -8.79 -3.39 -5.39 -5.66 1.54 -9.84 -2.19 5.03 10.93 0.62 7.02 [3,] -4.62 -8.79 -3.39 -5.39 -5.66 1.54 -9.84 -2.19 5.03 10.93 0.62 7.02 [4,] -4.62 -8.79 -3.39 -5.39 -5.66 1.54 -9.84 -2.19 5.03 10.93 0.62 7.02 [5,] -4.62 -8.79 -3.39 -5.39 -5.66 1.54 -9.84 -2.19 5.03 10.93 0.62 7.02 [,73] [,74] [,75] [,76] [,77] [,78] [,79] [,80] [,81] [,82] [,83] [,84] [1,] 11.73 -0.49 -5 -1.94 -3.81 -1.53 -4.93 -7.67 9.55 1.84 2.23 8.75 [2,] 11.73 -0.49 -5 -1.94 -3.81 -1.53 -4.93 -7.67 9.55 1.84 2.23 8.75 [3,] 11.73 -0.49 -5 -1.94 -3.81 -1.53 -4.93 -7.67 9.55 1.84 2.23 8.75 [4,] 11.73 -0.49 -5 -1.94 -3.81 -1.53 -4.93 -7.67 9.55 1.84 2.23 8.75 [5,] 11.73 -0.49 -5 -1.94 -3.81 -1.53 -4.93 -7.67 9.55 1.84 2.23 8.75 [,85] [,86] [,87] [,88] [,89] [,90] [,91] [,92] [,93] [,94] [,95] [,96] [1,] -2.06 3.65 7.62 -6.92 0.79 -11.43 -9.16 -2.89 -3.15 6.05 7.66 9.17 [2,] -2.06 3.65 7.62 -6.92 0.79 -11.43 -9.16 -2.89 -3.15 6.05 7.66 9.17 [3,] -2.06 3.65 7.62 -6.92 0.79 -11.43 -9.16 -2.89 -3.15 6.05 7.66 9.17 [4,] -2.06 3.65 7.62 -6.92 0.79 -11.43 -9.16 -2.89 -3.15 6.05 7.66 9.17 [5,] -2.06 3.65 7.62 -6.92 0.79 -11.43 -9.16 -2.89 -3.15 6.05 7.66 9.17 [,97] [,98] [,99] [,100] [,101] [,102] [,103] [,104] [,105] [,106] [,107] [1,] -4.92 -3.27 5.6 -15.32 -1.84 4.5 -15.94 6.33 -3.51 11.4 4.64 [2,] -4.92 -3.27 5.6 -15.32 -1.84 4.5 -15.94 6.33 -3.51 11.4 4.64 [3,] -4.92 -3.27 5.6 -15.32 -1.84 4.5 -15.94 6.33 -3.51 11.4 4.64 [4,] -4.92 -3.27 5.6 -15.32 -1.84 4.5 -15.94 6.33 -3.51 11.4 4.64 [5,] -4.92 -3.27 5.6 -15.32 -1.84 4.5 -15.94 6.33 -3.51 11.4 4.64 [,108] [,109] [,110] [,111] [,112] [,113] [,114] [,115] [,116] [,117] [1,] 9.53 2.7 -7.86 15 -11.75 -7 -3.62 -4.06 3.83 8.6 [2,] 9.53 2.7 -7.86 15 -11.75 -7 -3.62 -4.06 3.83 8.6 [3,] 9.53 2.7 -7.86 15 -11.75 -7 -3.62 -4.06 3.83 8.6 [4,] 9.53 2.7 -7.86 15 -11.75 -7 -3.62 -4.06 3.83 8.6 [5,] 9.53 2.7 -7.86 15 -11.75 -7 -3.62 -4.06 3.83 8.6 [,118] [,119] [,120] [1,] 0.22 -5.36 NA [2,] 0.22 -5.36 NA [3,] 0.22 -5.36 NA [4,] 0.22 -5.36 NA [5,] 0.22 -5.36 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 [38] 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 [75] 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 [112] 1 1 1 1 1 1 1 1 0 $conf [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [1,] 4.54 -4 3.86 -3.77 -4.55 -5.85 0.09 11.2 -11.26 13.21 -11.18 18.61 [2,] 4.54 -4 3.86 -3.77 -4.55 -5.85 0.09 11.2 -11.26 13.21 -11.18 18.61 [,13] [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [1,] -12.26 -7.77 25.32 -23.34 -3.67 5.78 -11.35 5.82 1.19 8.08 0.71 2.1 [2,] -12.26 -7.77 25.32 -23.34 -3.67 5.78 -11.35 5.82 1.19 8.08 0.71 2.1 [,25] [,26] [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [1,] -17.03 1.3 11.78 0.74 -6.5 1.21 -17.61 3.24 9.36 -0.8 4.85 19.53 [2,] -17.03 1.3 11.78 0.74 -6.5 1.21 -17.61 3.24 9.36 -0.8 4.85 19.53 [,37] [,38] [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47] [,48] [1,] -8.69 -1.71 2.8 -12.67 -9.96 -5.42 -9.61 -2.13 8.06 2.53 0.12 33.58 [2,] -8.69 -1.71 2.8 -12.67 -9.96 -5.42 -9.61 -2.13 8.06 2.53 0.12 33.58 [,49] [,50] [,51] [,52] [,53] [,54] [,55] [,56] [,57] [,58] [,59] [,60] [1,] -4.34 10.68 -1.07 -18.97 -9.03 1.96 -6.98 6.92 -5.02 7.94 9.61 9.79 [2,] -4.34 10.68 -1.07 -18.97 -9.03 1.96 -6.98 6.92 -5.02 7.94 9.61 9.79 [,61] [,62] [,63] [,64] [,65] [,66] [,67] [,68] [,69] [,70] [,71] [,72] [1,] -4.62 -8.79 -3.39 -5.39 -5.66 1.54 -9.84 -2.19 5.03 10.93 0.62 7.02 [2,] -4.62 -8.79 -3.39 -5.39 -5.66 1.54 -9.84 -2.19 5.03 10.93 0.62 7.02 [,73] [,74] [,75] [,76] [,77] [,78] [,79] [,80] [,81] [,82] [,83] [,84] [1,] 11.73 -0.49 -5 -1.94 -3.81 -1.53 -4.93 -7.67 9.55 1.84 2.23 8.75 [2,] 11.73 -0.49 -5 -1.94 -3.81 -1.53 -4.93 -7.67 9.55 1.84 2.23 8.75 [,85] [,86] [,87] [,88] [,89] [,90] [,91] [,92] [,93] [,94] [,95] [,96] [1,] -2.06 3.65 7.62 -6.92 0.79 -11.43 -9.16 -2.89 -3.15 6.05 7.66 9.17 [2,] -2.06 3.65 7.62 -6.92 0.79 -11.43 -9.16 -2.89 -3.15 6.05 7.66 9.17 [,97] [,98] [,99] [,100] [,101] [,102] [,103] [,104] [,105] [,106] [,107] [1,] -4.92 -3.27 5.6 -15.32 -1.84 4.5 -15.94 6.33 -3.51 11.4 4.64 [2,] -4.92 -3.27 5.6 -15.32 -1.84 4.5 -15.94 6.33 -3.51 11.4 4.64 [,108] [,109] [,110] [,111] [,112] [,113] [,114] [,115] [,116] [,117] [1,] 9.53 2.7 -7.86 15 -11.75 -7 -3.62 -4.06 3.83 8.6 [2,] 9.53 2.7 -7.86 15 -11.75 -7 -3.62 -4.06 3.83 8.6 [,118] [,119] [,120] [1,] 0.22 -5.36 NA [2,] 0.22 -5.36 NA $out numeric(0) $group numeric(0) $names [1] "1" "2" "3" "4" "5" "6" "7" "8" "9" "10" "11" "12" [13] "13" "14" "15" "16" "17" "18" "19" "20" "21" "22" "23" "24" [25] "25" "26" "27" "28" "29" "30" "31" "32" "33" "34" "35" "36" [37] "37" "38" "39" "40" "41" "42" "43" "44" "45" "46" "47" "48" [49] "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" [73] "73" "74" "75" "76" "77" "78" "79" "80" "81" "82" "83" "84" [85] "85" "86" "87" "88" "89" "90" "91" "92" "93" "94" "95" "96" [97] "97" "98" "99" "100" "101" "102" "103" "104" "105" "106" "107" "108" [109] "109" "110" "111" "112" "113" "114" "115" "116" "117" "118" "119" "120" > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/674za1457193201.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,] 69.280 NA [2,] 89.345 NA [3,] 95.875 NA [4,] 103.625 NA [5,] 119.150 NA $n [1] 120 0 $conf [,1] [,2] [1,] 93.81534 NA [2,] 97.93466 NA $out [1] 67.15 $group [1] 1 $names [1] "1" NA > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/7kxld1457193201.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,] 69.280 69.280 69.280 [2,] 89.345 89.345 89.345 [3,] 95.875 95.875 95.875 [4,] 103.625 103.625 103.625 [5,] 119.150 119.150 119.150 $n [1] 120 120 120 $conf [,1] [,2] [,3] [1,] 93.81534 93.81534 93.81534 [2,] 97.93466 97.93466 97.93466 $out [1] 67.15 67.15 67.15 $group [1] 1 2 3 $names [1] "mean" "median" "midrange" > dev.off() null device 1 > > try(system("convert tmp/14aky1457193201.ps tmp/14aky1457193201.png",intern=TRUE)) character(0) > try(system("convert tmp/2qhl31457193201.ps tmp/2qhl31457193201.png",intern=TRUE)) character(0) > try(system("convert tmp/3zaiy1457193201.ps tmp/3zaiy1457193201.png",intern=TRUE)) character(0) > try(system("convert tmp/4nk6m1457193201.ps tmp/4nk6m1457193201.png",intern=TRUE)) character(0) > try(system("convert tmp/5qzk21457193201.ps tmp/5qzk21457193201.png",intern=TRUE)) character(0) > try(system("convert tmp/674za1457193201.ps tmp/674za1457193201.png",intern=TRUE)) character(0) > try(system("convert tmp/7kxld1457193201.ps tmp/7kxld1457193201.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.595 0.426 3.045