R version 2.11.1 (2010-05-31) Copyright (C) 2010 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 <- array(list(1 + ,3 + ,13 + ,13 + ,14 + ,13 + ,2 + ,5 + ,12 + ,12 + ,8 + ,13 + ,3 + ,6 + ,15 + ,10 + ,12 + ,16 + ,4 + ,6 + ,12 + ,9 + ,7 + ,12 + ,5 + ,5 + ,10 + ,10 + ,10 + ,11 + ,6 + ,3 + ,12 + ,12 + ,7 + ,12 + ,7 + ,8 + ,15 + ,13 + ,16 + ,18 + ,8 + ,4 + ,9 + ,12 + ,11 + ,11 + ,9 + ,4 + ,12 + ,12 + ,14 + ,14 + ,10 + ,4 + ,11 + ,6 + ,6 + ,9 + ,11 + ,6 + ,11 + ,5 + ,16 + ,14 + ,12 + ,6 + ,11 + ,12 + ,11 + ,12 + ,13 + ,5 + ,15 + ,11 + ,16 + ,11 + ,14 + ,4 + ,7 + ,14 + ,12 + ,12 + ,15 + ,6 + ,11 + ,14 + ,7 + ,13 + ,16 + ,4 + ,11 + ,12 + ,13 + ,11 + ,17 + ,6 + ,10 + ,12 + ,11 + ,12 + ,18 + ,6 + ,14 + ,11 + ,15 + ,16 + ,19 + ,4 + ,10 + ,11 + ,7 + ,9 + ,20 + ,4 + ,6 + ,7 + ,9 + ,11 + ,21 + ,2 + ,11 + ,9 + ,7 + ,13 + ,22 + ,7 + ,15 + ,11 + ,14 + ,15 + ,23 + ,5 + ,11 + ,11 + ,15 + ,10 + ,24 + ,4 + ,12 + ,12 + ,7 + ,11 + ,25 + ,6 + ,14 + ,12 + ,15 + ,13 + ,26 + ,6 + ,15 + ,11 + ,17 + ,16 + ,27 + ,7 + ,9 + ,11 + ,15 + ,15 + ,28 + ,5 + ,13 + ,8 + ,14 + ,14 + ,29 + ,6 + 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,11 + ,14 + ,14 + ,117 + ,6 + ,16 + ,12 + ,14 + ,14 + ,118 + ,6 + ,11 + ,12 + ,8 + ,16 + ,119 + ,6 + ,14 + ,12 + ,15 + ,14 + ,120 + ,4 + ,14 + ,11 + ,12 + ,12 + ,121 + ,4 + ,12 + ,12 + ,12 + ,13 + ,122 + ,5 + ,14 + ,11 + ,16 + ,12 + ,123 + ,4 + ,8 + ,11 + ,9 + ,12 + ,124 + ,6 + ,13 + ,13 + ,15 + ,14 + ,125 + ,6 + ,16 + ,12 + ,15 + ,14 + ,126 + ,5 + ,12 + ,12 + ,6 + ,14 + ,127 + ,8 + ,16 + ,12 + ,14 + ,16 + ,128 + ,6 + ,12 + ,12 + ,15 + ,13 + ,129 + ,5 + ,11 + ,8 + ,10 + ,14 + ,130 + ,4 + ,4 + ,8 + ,6 + ,4 + ,131 + ,8 + ,16 + ,12 + ,14 + ,16 + ,132 + ,6 + ,15 + ,11 + ,12 + ,13 + ,133 + ,4 + ,10 + ,12 + ,8 + ,16 + ,134 + ,6 + ,13 + ,13 + ,11 + ,15 + ,135 + ,6 + ,15 + ,12 + ,13 + ,14 + ,136 + ,4 + ,12 + ,12 + ,9 + ,13 + ,137 + ,6 + ,14 + ,11 + ,15 + ,14 + ,138 + ,3 + ,7 + ,12 + ,13 + ,12 + ,139 + ,6 + ,19 + ,12 + ,15 + ,15 + ,140 + ,5 + ,12 + ,10 + ,14 + ,14 + ,141 + ,4 + ,12 + ,11 + ,16 + ,13 + ,142 + ,6 + ,13 + ,12 + ,14 + ,14 + ,143 + ,4 + ,15 + ,12 + ,14 + ,16 + ,144 + ,4 + ,8 + ,10 + ,10 + ,6 + ,145 + ,4 + ,12 + ,12 + ,10 + ,13 + ,146 + ,6 + ,10 + ,13 + ,4 + ,13 + ,147 + ,5 + ,8 + ,12 + ,8 + ,14 + ,148 + ,6 + ,10 + ,15 + ,15 + ,15 + ,149 + ,6 + ,15 + ,11 + ,16 + ,14 + ,150 + ,8 + ,16 + ,12 + ,12 + ,15 + ,151 + ,7 + ,13 + ,11 + ,12 + ,13 + ,152 + ,7 + ,16 + ,12 + ,15 + ,16 + ,153 + ,4 + ,9 + ,11 + ,9 + ,12 + ,154 + ,6 + ,14 + ,10 + ,12 + ,15 + ,155 + ,6 + ,14 + ,11 + ,14 + ,12 + ,156 + ,2 + ,12 + ,11 + ,11 + ,14) + ,dim=c(6 + ,156) + ,dimnames=list(c('nr' + ,'Celebrity' + ,'Popularity' + ,'FindingFriends' + ,'KnowingPeople' + ,'Liked ') + ,1:156)) > y <- array(NA,dim=c(6,156),dimnames=list(c('nr','Celebrity','Popularity','FindingFriends','KnowingPeople','Liked '),1:156)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '2' > #'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!) > library(lattice) > library(lmtest) Loading required package: zoo > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x Celebrity nr Popularity FindingFriends KnowingPeople Liked\r t 1 3 1 13 13 14 13 1 2 5 2 12 12 8 13 2 3 6 3 15 10 12 16 3 4 6 4 12 9 7 12 4 5 5 5 10 10 10 11 5 6 3 6 12 12 7 12 6 7 8 7 15 13 16 18 7 8 4 8 9 12 11 11 8 9 4 9 12 12 14 14 9 10 4 10 11 6 6 9 10 11 6 11 11 5 16 14 11 12 6 12 11 12 11 12 12 13 5 13 15 11 16 11 13 14 4 14 7 14 12 12 14 15 6 15 11 14 7 13 15 16 4 16 11 12 13 11 16 17 6 17 10 12 11 12 17 18 6 18 14 11 15 16 18 19 4 19 10 11 7 9 19 20 4 20 6 7 9 11 20 21 2 21 11 9 7 13 21 22 7 22 15 11 14 15 22 23 5 23 11 11 15 10 23 24 4 24 12 12 7 11 24 25 6 25 14 12 15 13 25 26 6 26 15 11 17 16 26 27 7 27 9 11 15 15 27 28 5 28 13 8 14 14 28 29 6 29 13 9 14 14 29 30 4 30 16 12 8 14 30 31 4 31 13 10 8 8 31 32 7 32 12 10 14 13 32 33 7 33 14 12 14 15 33 34 4 34 11 8 8 13 34 35 4 35 9 12 11 11 35 36 6 36 16 11 16 15 36 37 6 37 12 12 10 15 37 38 5 38 10 7 8 9 38 39 6 39 13 11 14 13 39 40 7 40 16 11 16 16 40 41 6 41 14 12 13 13 41 42 3 42 15 9 5 11 42 43 3 43 5 15 8 12 43 44 4 44 8 11 10 12 44 45 6 45 11 11 8 12 45 46 7 46 16 11 13 14 46 47 5 47 17 11 15 14 47 48 4 48 9 15 6 8 48 49 5 49 9 11 12 13 49 50 6 50 13 12 16 16 50 51 6 51 10 12 5 13 51 52 6 52 6 9 15 11 52 53 5 53 12 12 12 14 53 54 4 54 8 12 8 13 54 55 5 55 14 13 13 13 55 56 5 56 12 11 14 13 56 57 4 57 11 9 12 12 57 58 6 58 16 9 16 16 58 59 2 59 8 11 10 15 59 60 8 60 15 11 15 15 60 61 3 61 7 12 8 12 61 62 6 62 16 12 16 14 62 63 6 63 14 9 19 12 63 64 6 64 16 11 14 15 64 65 5 65 9 9 6 12 65 66 5 66 14 12 13 13 66 67 6 67 11 12 15 12 67 68 5 68 13 12 7 12 68 69 6 69 15 12 13 13 69 70 2 70 5 14 4 5 70 71 5 71 15 11 14 13 71 72 5 72 13 12 13 13 72 73 5 73 11 11 11 14 73 74 6 74 11 6 14 17 74 75 6 75 12 10 12 13 75 76 6 76 12 12 15 13 76 77 5 77 12 13 14 12 77 78 5 78 12 8 13 13 78 79 4 79 14 12 8 14 79 80 2 80 6 12 6 11 80 81 4 81 7 12 7 12 81 82 6 82 14 6 13 12 82 83 6 83 14 11 13 16 83 84 5 84 10 10 11 12 84 85 3 85 13 12 5 12 85 86 6 86 12 13 12 12 86 87 4 87 9 11 8 10 87 88 5 88 12 7 11 15 88 89 8 89 16 11 14 15 89 90 4 90 10 11 9 12 90 91 6 91 14 11 10 16 91 92 6 92 10 11 13 15 92 93 7 93 16 12 16 16 93 94 6 94 15 10 16 13 94 95 5 95 12 11 11 12 95 96 4 96 10 12 8 11 96 97 6 97 8 7 4 13 97 98 3 98 8 13 7 10 98 99 5 99 11 8 14 15 99 100 6 100 13 12 11 13 100 101 7 101 16 11 17 16 101 102 7 102 16 12 15 15 102 103 6 103 14 14 17 18 103 104 3 104 11 10 5 13 104 105 2 105 4 10 4 10 105 106 8 106 14 13 10 16 106 107 3 107 9 10 11 13 107 108 8 108 14 11 15 15 108 109 3 109 8 10 10 14 109 110 4 110 8 7 9 15 110 111 5 111 11 10 12 14 111 112 7 112 12 8 15 13 112 113 6 113 11 12 7 13 113 114 6 114 14 12 13 15 114 115 7 115 15 12 12 16 115 116 6 116 16 11 14 14 116 117 6 117 16 12 14 14 117 118 6 118 11 12 8 16 118 119 6 119 14 12 15 14 119 120 4 120 14 11 12 12 120 121 4 121 12 12 12 13 121 122 5 122 14 11 16 12 122 123 4 123 8 11 9 12 123 124 6 124 13 13 15 14 124 125 6 125 16 12 15 14 125 126 5 126 12 12 6 14 126 127 8 127 16 12 14 16 127 128 6 128 12 12 15 13 128 129 5 129 11 8 10 14 129 130 4 130 4 8 6 4 130 131 8 131 16 12 14 16 131 132 6 132 15 11 12 13 132 133 4 133 10 12 8 16 133 134 6 134 13 13 11 15 134 135 6 135 15 12 13 14 135 136 4 136 12 12 9 13 136 137 6 137 14 11 15 14 137 138 3 138 7 12 13 12 138 139 6 139 19 12 15 15 139 140 5 140 12 10 14 14 140 141 4 141 12 11 16 13 141 142 6 142 13 12 14 14 142 143 4 143 15 12 14 16 143 144 4 144 8 10 10 6 144 145 4 145 12 12 10 13 145 146 6 146 10 13 4 13 146 147 5 147 8 12 8 14 147 148 6 148 10 15 15 15 148 149 6 149 15 11 16 14 149 150 8 150 16 12 12 15 150 151 7 151 13 11 12 13 151 152 7 152 16 12 15 16 152 153 4 153 9 11 9 12 153 154 6 154 14 10 12 15 154 155 6 155 14 11 14 12 155 156 2 156 12 11 11 14 156 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) nr Popularity FindingFriends KnowingPeople 0.4178099 0.0004860 0.1541880 -0.0205822 0.1035727 `Liked\r` t 0.1459054 NA > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -3.299445 -0.612920 0.001786 0.580783 2.269402 Coefficients: (1 not defined because of singularities) Estimate Std. Error t value Pr(>|t|) (Intercept) 0.417810 0.708265 0.590 0.55614 nr 0.000486 0.001895 0.256 0.79798 Popularity 0.154188 0.038463 4.009 9.59e-05 *** FindingFriends -0.020582 0.048050 -0.428 0.66901 KnowingPeople 0.103573 0.030955 3.346 0.00104 ** `Liked\r` 0.145905 0.049024 2.976 0.00340 ** t NA NA NA NA --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 1.047 on 150 degrees of freedom Multiple R-squared: 0.4592, Adjusted R-squared: 0.4411 F-statistic: 25.47 on 5 and 150 DF, p-value: < 2.2e-16 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 0.650443082 0.699113836 0.34955692 [2,] 0.779021572 0.441956856 0.22097843 [3,] 0.862399285 0.275201430 0.13760071 [4,] 0.866086272 0.267827456 0.13391373 [5,] 0.812175991 0.375648017 0.18782401 [6,] 0.744000849 0.511998302 0.25599915 [7,] 0.688939217 0.622121565 0.31106078 [8,] 0.635991579 0.728016843 0.36400842 [9,] 0.679025207 0.641949586 0.32097479 [10,] 0.609348165 0.781303671 0.39065184 [11,] 0.610618261 0.778763479 0.38938174 [12,] 0.961049793 0.077900414 0.03895021 [13,] 0.955307267 0.089385466 0.04469273 [14,] 0.938232319 0.123535362 0.06176768 [15,] 0.917559733 0.164880534 0.08244027 [16,] 0.890002816 0.219994367 0.10999718 [17,] 0.866941922 0.266116155 0.13305808 [18,] 0.873312304 0.253375392 0.12668770 [19,] 0.858362348 0.283275304 0.14163765 [20,] 0.820155053 0.359689895 0.17984495 [21,] 0.833569698 0.332860604 0.16643030 [22,] 0.801116954 0.397766093 0.19888305 [23,] 0.831995813 0.336008373 0.16800419 [24,] 0.816653675 0.366692650 0.18334633 [25,] 0.806941220 0.386117559 0.19305878 [26,] 0.778306201 0.443387598 0.22169380 [27,] 0.739951062 0.520097876 0.26004894 [28,] 0.701739761 0.596520478 0.29826024 [29,] 0.690717892 0.618564217 0.30928211 [30,] 0.643325180 0.713349641 0.35667482 [31,] 0.592554886 0.814890229 0.40744511 [32,] 0.542375575 0.915248850 0.45762443 [33,] 0.594831403 0.810337195 0.40516860 [34,] 0.601474896 0.797050208 0.39852510 [35,] 0.560832047 0.878335907 0.43916795 [36,] 0.606427416 0.787145168 0.39357258 [37,] 0.591823686 0.816352629 0.40817631 [38,] 0.630898964 0.738202072 0.36910104 [39,] 0.601084781 0.797830438 0.39891522 [40,] 0.555898672 0.888202656 0.44410133 [41,] 0.514756830 0.970486341 0.48524317 [42,] 0.577950207 0.844099585 0.42204979 [43,] 0.613679335 0.772641329 0.38632066 [44,] 0.581644783 0.836710435 0.41835522 [45,] 0.555124707 0.889750586 0.44487529 [46,] 0.519863880 0.960272239 0.48013612 [47,] 0.484020198 0.968040396 0.51597980 [48,] 0.487959400 0.975918800 0.51204060 [49,] 0.458986272 0.917972544 0.54101373 [50,] 0.741676781 0.516646438 0.25832322 [51,] 0.807396794 0.385206411 0.19260321 [52,] 0.796705036 0.406589929 0.20329496 [53,] 0.764161701 0.471676598 0.23583830 [54,] 0.725887302 0.548225396 0.27411270 [55,] 0.688351569 0.623296862 0.31164843 [56,] 0.678886584 0.642226833 0.32111342 [57,] 0.648167241 0.703665517 0.35183276 [58,] 0.629041798 0.741916404 0.37095820 [59,] 0.588470247 0.823059507 0.41152975 [60,] 0.544366297 0.911267406 0.45563370 [61,] 0.498794684 0.997589369 0.50120532 [62,] 0.484993556 0.969987112 0.51500644 [63,] 0.446268804 0.892537608 0.55373120 [64,] 0.399961734 0.799923469 0.60003827 [65,] 0.355482667 0.710965334 0.64451733 [66,] 0.333047572 0.666095144 0.66695243 [67,] 0.300569580 0.601139161 0.69943042 [68,] 0.262154029 0.524308058 0.73784597 [69,] 0.229955101 0.459910202 0.77004490 [70,] 0.250066692 0.500133385 0.74993331 [71,] 0.276863879 0.553727758 0.72313612 [72,] 0.240244893 0.480489787 0.75975511 [73,] 0.209588469 0.419176938 0.79041153 [74,] 0.177848868 0.355697735 0.82215113 [75,] 0.150656103 0.301312206 0.84934390 [76,] 0.211796187 0.423592373 0.78820381 [77,] 0.202457224 0.404914447 0.79754278 [78,] 0.171452328 0.342904656 0.82854767 [79,] 0.149409525 0.298819051 0.85059047 [80,] 0.186996692 0.373993384 0.81300331 [81,] 0.165366927 0.330733854 0.83463307 [82,] 0.140580458 0.281160916 0.85941954 [83,] 0.129958559 0.259917118 0.87004144 [84,] 0.107843653 0.215687305 0.89215635 [85,] 0.087684187 0.175368373 0.91231581 [86,] 0.070452184 0.140904367 0.92954782 [87,] 0.058241895 0.116483791 0.94175810 [88,] 0.105371669 0.210743338 0.89462833 [89,] 0.101274262 0.202548524 0.89872574 [90,] 0.087429916 0.174859832 0.91257008 [91,] 0.073961066 0.147922132 0.92603893 [92,] 0.058918959 0.117837919 0.94108104 [93,] 0.047890737 0.095781474 0.95210926 [94,] 0.040571191 0.081142383 0.95942881 [95,] 0.061249700 0.122499400 0.93875030 [96,] 0.059390119 0.118780237 0.94060988 [97,] 0.103028678 0.206057355 0.89697132 [98,] 0.137958738 0.275917476 0.86204126 [99,] 0.209304693 0.418609386 0.79069531 [100,] 0.244098795 0.488197590 0.75590121 [101,] 0.215297800 0.430595599 0.78470220 [102,] 0.181295264 0.362590528 0.81870474 [103,] 0.241586377 0.483172753 0.75841362 [104,] 0.237496895 0.474993790 0.76250310 [105,] 0.197997964 0.395995928 0.80200204 [106,] 0.183953847 0.367907695 0.81604615 [107,] 0.150646203 0.301292405 0.84935380 [108,] 0.122244901 0.244489802 0.87775510 [109,] 0.114276021 0.228552041 0.88572398 [110,] 0.091173235 0.182346470 0.90882677 [111,] 0.121521306 0.243042612 0.87847869 [112,] 0.137911515 0.275823030 0.86208849 [113,] 0.127880255 0.255760509 0.87211975 [114,] 0.101125039 0.202250077 0.89887496 [115,] 0.077144834 0.154289669 0.92285517 [116,] 0.064037421 0.128074842 0.93596258 [117,] 0.053126735 0.106253469 0.94687327 [118,] 0.062441751 0.124883502 0.93755825 [119,] 0.049430846 0.098861692 0.95056915 [120,] 0.039714290 0.079428579 0.96028571 [121,] 0.055285709 0.110571417 0.94471429 [122,] 0.091600268 0.183200536 0.90839973 [123,] 0.070378007 0.140756013 0.92962199 [124,] 0.052346038 0.104692077 0.94765396 [125,] 0.038944915 0.077889831 0.96105508 [126,] 0.026646297 0.053292594 0.97335370 [127,] 0.023860655 0.047721311 0.97613934 [128,] 0.019641967 0.039283935 0.98035803 [129,] 0.014582085 0.029164170 0.98541792 [130,] 0.014111626 0.028223253 0.98588837 [131,] 0.012372557 0.024745113 0.98762744 [132,] 0.008124700 0.016249400 0.99187530 [133,] 0.004999254 0.009998508 0.99500075 [134,] 0.023117271 0.046234542 0.97688273 [135,] 0.011950123 0.023900245 0.98804988 [136,] 0.104485762 0.208971524 0.89551424 [137,] 0.092368096 0.184736191 0.90763190 > postscript(file="/var/www/rcomp/tmp/1e8l31290533427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/2pz261290533427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/3pz261290533427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/4pz261290533427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/5z81r1290533427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 156 Frequency = 1 1 2 3 4 5 6 -2.50195929 0.25259656 -0.10362459 1.43935622 0.60301589 -1.49986919 7 8 9 10 11 12 1.25007667 -0.30666227 -1.51814644 0.07017090 0.28384922 1.23711250 13 14 15 16 17 18 -0.77266558 -0.20951567 1.54520421 -0.82607122 1.38887076 -0.24686164 19 20 21 22 23 24 0.21932352 0.25430487 -2.56062231 0.84648459 0.08870504 -0.36271090 25 26 27 28 29 30 0.20803506 -0.61208258 1.66561029 -0.76389617 0.25620005 -1.52366752 31 32 33 34 35 36 -0.22732136 1.57541777 1.01590932 -0.69109449 -0.31978293 -0.52165204 37 38 39 40 41 42 0.73663218 1.02418915 0.43841027 0.33049876 0.40740517 -1.68862323 43 44 45 46 47 48 -0.48035940 -0.23288337 1.51121194 0.93011182 -1.43170746 0.69122568 49 50 51 52 53 54 0.25744814 -0.19121453 1.84787900 1.65848284 -0.33238294 -0.15592080 55 56 57 58 59 60 -0.57881597 -0.41566287 -0.95007442 -0.71941268 -2.67788882 1.72444582 61 62 63 64 65 66 -0.85922903 -0.36779919 -0.14056278 -0.32811334 0.97584996 -0.60474359 67 68 69 70 71 72 0.79609459 0.31581387 0.23961054 -0.07843381 -0.88551618 -0.45347128 73 74 75 76 77 78 -0.10492344 0.04324563 0.76166722 0.49162762 -0.23879811 -0.38452762 79 80 81 82 83 84 -1.23910305 -1.36122336 0.23462462 0.40989362 -0.07130310 0.31514776 85 86 87 88 89 90 -1.48530197 0.96397365 0.09098885 -0.49463476 1.65973790 -0.46004047 91 92 93 94 95 96 0.23552727 0.68698081 0.32532555 -0.12442052 0.02200843 -0.19289595 97 98 99 100 101 102 2.13456315 -0.61543160 -0.63592801 0.74006743 0.19728312 0.57043005 103 104 105 106 107 108 -0.72537705 -1.37322872 -0.75310970 2.26940234 -1.68774649 1.85530822 109 110 111 112 113 114 -1.57686311 -0.68142829 -0.24754438 1.39180475 1.45641674 0.08011999 115 116 117 118 119 120 0.88311329 -0.20747736 -0.18738115 0.91269813 0.01645032 -1.40208902 121 122 123 124 125 126 -1.21952217 -0.81735155 -0.16770080 0.18879075 -0.29484141 0.25357863 127 128 129 130 131 132 1.51594855 0.46635820 -0.09031049 1.86186428 1.51400475 0.29198616 133 134 135 136 137 138 -0.94040310 0.45231648 0.06163242 -0.91609346 -0.01287895 -1.41451051 139 140 141 142 143 144 -0.91011417 -0.62297027 -1.66411398 0.26303414 -2.33763864 0.57337181 145 146 147 148 149 150 -1.02403967 1.92586853 0.65298042 0.53495092 -0.27647103 1.85782240 151 152 153 154 155 156 1.59112913 0.40022713 -0.33646733 0.12309031 0.37375740 -3.29944534 > postscript(file="/var/www/rcomp/tmp/6z81r1290533427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 156 Frequency = 1 lag(myerror, k = 1) myerror 0 -2.50195929 NA 1 0.25259656 -2.50195929 2 -0.10362459 0.25259656 3 1.43935622 -0.10362459 4 0.60301589 1.43935622 5 -1.49986919 0.60301589 6 1.25007667 -1.49986919 7 -0.30666227 1.25007667 8 -1.51814644 -0.30666227 9 0.07017090 -1.51814644 10 0.28384922 0.07017090 11 1.23711250 0.28384922 12 -0.77266558 1.23711250 13 -0.20951567 -0.77266558 14 1.54520421 -0.20951567 15 -0.82607122 1.54520421 16 1.38887076 -0.82607122 17 -0.24686164 1.38887076 18 0.21932352 -0.24686164 19 0.25430487 0.21932352 20 -2.56062231 0.25430487 21 0.84648459 -2.56062231 22 0.08870504 0.84648459 23 -0.36271090 0.08870504 24 0.20803506 -0.36271090 25 -0.61208258 0.20803506 26 1.66561029 -0.61208258 27 -0.76389617 1.66561029 28 0.25620005 -0.76389617 29 -1.52366752 0.25620005 30 -0.22732136 -1.52366752 31 1.57541777 -0.22732136 32 1.01590932 1.57541777 33 -0.69109449 1.01590932 34 -0.31978293 -0.69109449 35 -0.52165204 -0.31978293 36 0.73663218 -0.52165204 37 1.02418915 0.73663218 38 0.43841027 1.02418915 39 0.33049876 0.43841027 40 0.40740517 0.33049876 41 -1.68862323 0.40740517 42 -0.48035940 -1.68862323 43 -0.23288337 -0.48035940 44 1.51121194 -0.23288337 45 0.93011182 1.51121194 46 -1.43170746 0.93011182 47 0.69122568 -1.43170746 48 0.25744814 0.69122568 49 -0.19121453 0.25744814 50 1.84787900 -0.19121453 51 1.65848284 1.84787900 52 -0.33238294 1.65848284 53 -0.15592080 -0.33238294 54 -0.57881597 -0.15592080 55 -0.41566287 -0.57881597 56 -0.95007442 -0.41566287 57 -0.71941268 -0.95007442 58 -2.67788882 -0.71941268 59 1.72444582 -2.67788882 60 -0.85922903 1.72444582 61 -0.36779919 -0.85922903 62 -0.14056278 -0.36779919 63 -0.32811334 -0.14056278 64 0.97584996 -0.32811334 65 -0.60474359 0.97584996 66 0.79609459 -0.60474359 67 0.31581387 0.79609459 68 0.23961054 0.31581387 69 -0.07843381 0.23961054 70 -0.88551618 -0.07843381 71 -0.45347128 -0.88551618 72 -0.10492344 -0.45347128 73 0.04324563 -0.10492344 74 0.76166722 0.04324563 75 0.49162762 0.76166722 76 -0.23879811 0.49162762 77 -0.38452762 -0.23879811 78 -1.23910305 -0.38452762 79 -1.36122336 -1.23910305 80 0.23462462 -1.36122336 81 0.40989362 0.23462462 82 -0.07130310 0.40989362 83 0.31514776 -0.07130310 84 -1.48530197 0.31514776 85 0.96397365 -1.48530197 86 0.09098885 0.96397365 87 -0.49463476 0.09098885 88 1.65973790 -0.49463476 89 -0.46004047 1.65973790 90 0.23552727 -0.46004047 91 0.68698081 0.23552727 92 0.32532555 0.68698081 93 -0.12442052 0.32532555 94 0.02200843 -0.12442052 95 -0.19289595 0.02200843 96 2.13456315 -0.19289595 97 -0.61543160 2.13456315 98 -0.63592801 -0.61543160 99 0.74006743 -0.63592801 100 0.19728312 0.74006743 101 0.57043005 0.19728312 102 -0.72537705 0.57043005 103 -1.37322872 -0.72537705 104 -0.75310970 -1.37322872 105 2.26940234 -0.75310970 106 -1.68774649 2.26940234 107 1.85530822 -1.68774649 108 -1.57686311 1.85530822 109 -0.68142829 -1.57686311 110 -0.24754438 -0.68142829 111 1.39180475 -0.24754438 112 1.45641674 1.39180475 113 0.08011999 1.45641674 114 0.88311329 0.08011999 115 -0.20747736 0.88311329 116 -0.18738115 -0.20747736 117 0.91269813 -0.18738115 118 0.01645032 0.91269813 119 -1.40208902 0.01645032 120 -1.21952217 -1.40208902 121 -0.81735155 -1.21952217 122 -0.16770080 -0.81735155 123 0.18879075 -0.16770080 124 -0.29484141 0.18879075 125 0.25357863 -0.29484141 126 1.51594855 0.25357863 127 0.46635820 1.51594855 128 -0.09031049 0.46635820 129 1.86186428 -0.09031049 130 1.51400475 1.86186428 131 0.29198616 1.51400475 132 -0.94040310 0.29198616 133 0.45231648 -0.94040310 134 0.06163242 0.45231648 135 -0.91609346 0.06163242 136 -0.01287895 -0.91609346 137 -1.41451051 -0.01287895 138 -0.91011417 -1.41451051 139 -0.62297027 -0.91011417 140 -1.66411398 -0.62297027 141 0.26303414 -1.66411398 142 -2.33763864 0.26303414 143 0.57337181 -2.33763864 144 -1.02403967 0.57337181 145 1.92586853 -1.02403967 146 0.65298042 1.92586853 147 0.53495092 0.65298042 148 -0.27647103 0.53495092 149 1.85782240 -0.27647103 150 1.59112913 1.85782240 151 0.40022713 1.59112913 152 -0.33646733 0.40022713 153 0.12309031 -0.33646733 154 0.37375740 0.12309031 155 -3.29944534 0.37375740 156 NA -3.29944534 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 0.25259656 -2.50195929 [2,] -0.10362459 0.25259656 [3,] 1.43935622 -0.10362459 [4,] 0.60301589 1.43935622 [5,] -1.49986919 0.60301589 [6,] 1.25007667 -1.49986919 [7,] -0.30666227 1.25007667 [8,] -1.51814644 -0.30666227 [9,] 0.07017090 -1.51814644 [10,] 0.28384922 0.07017090 [11,] 1.23711250 0.28384922 [12,] -0.77266558 1.23711250 [13,] -0.20951567 -0.77266558 [14,] 1.54520421 -0.20951567 [15,] -0.82607122 1.54520421 [16,] 1.38887076 -0.82607122 [17,] -0.24686164 1.38887076 [18,] 0.21932352 -0.24686164 [19,] 0.25430487 0.21932352 [20,] -2.56062231 0.25430487 [21,] 0.84648459 -2.56062231 [22,] 0.08870504 0.84648459 [23,] -0.36271090 0.08870504 [24,] 0.20803506 -0.36271090 [25,] -0.61208258 0.20803506 [26,] 1.66561029 -0.61208258 [27,] -0.76389617 1.66561029 [28,] 0.25620005 -0.76389617 [29,] -1.52366752 0.25620005 [30,] -0.22732136 -1.52366752 [31,] 1.57541777 -0.22732136 [32,] 1.01590932 1.57541777 [33,] -0.69109449 1.01590932 [34,] -0.31978293 -0.69109449 [35,] -0.52165204 -0.31978293 [36,] 0.73663218 -0.52165204 [37,] 1.02418915 0.73663218 [38,] 0.43841027 1.02418915 [39,] 0.33049876 0.43841027 [40,] 0.40740517 0.33049876 [41,] -1.68862323 0.40740517 [42,] -0.48035940 -1.68862323 [43,] -0.23288337 -0.48035940 [44,] 1.51121194 -0.23288337 [45,] 0.93011182 1.51121194 [46,] -1.43170746 0.93011182 [47,] 0.69122568 -1.43170746 [48,] 0.25744814 0.69122568 [49,] -0.19121453 0.25744814 [50,] 1.84787900 -0.19121453 [51,] 1.65848284 1.84787900 [52,] -0.33238294 1.65848284 [53,] -0.15592080 -0.33238294 [54,] -0.57881597 -0.15592080 [55,] -0.41566287 -0.57881597 [56,] -0.95007442 -0.41566287 [57,] -0.71941268 -0.95007442 [58,] -2.67788882 -0.71941268 [59,] 1.72444582 -2.67788882 [60,] -0.85922903 1.72444582 [61,] -0.36779919 -0.85922903 [62,] -0.14056278 -0.36779919 [63,] -0.32811334 -0.14056278 [64,] 0.97584996 -0.32811334 [65,] -0.60474359 0.97584996 [66,] 0.79609459 -0.60474359 [67,] 0.31581387 0.79609459 [68,] 0.23961054 0.31581387 [69,] -0.07843381 0.23961054 [70,] -0.88551618 -0.07843381 [71,] -0.45347128 -0.88551618 [72,] -0.10492344 -0.45347128 [73,] 0.04324563 -0.10492344 [74,] 0.76166722 0.04324563 [75,] 0.49162762 0.76166722 [76,] -0.23879811 0.49162762 [77,] -0.38452762 -0.23879811 [78,] -1.23910305 -0.38452762 [79,] -1.36122336 -1.23910305 [80,] 0.23462462 -1.36122336 [81,] 0.40989362 0.23462462 [82,] -0.07130310 0.40989362 [83,] 0.31514776 -0.07130310 [84,] -1.48530197 0.31514776 [85,] 0.96397365 -1.48530197 [86,] 0.09098885 0.96397365 [87,] -0.49463476 0.09098885 [88,] 1.65973790 -0.49463476 [89,] -0.46004047 1.65973790 [90,] 0.23552727 -0.46004047 [91,] 0.68698081 0.23552727 [92,] 0.32532555 0.68698081 [93,] -0.12442052 0.32532555 [94,] 0.02200843 -0.12442052 [95,] -0.19289595 0.02200843 [96,] 2.13456315 -0.19289595 [97,] -0.61543160 2.13456315 [98,] -0.63592801 -0.61543160 [99,] 0.74006743 -0.63592801 [100,] 0.19728312 0.74006743 [101,] 0.57043005 0.19728312 [102,] -0.72537705 0.57043005 [103,] -1.37322872 -0.72537705 [104,] -0.75310970 -1.37322872 [105,] 2.26940234 -0.75310970 [106,] -1.68774649 2.26940234 [107,] 1.85530822 -1.68774649 [108,] -1.57686311 1.85530822 [109,] -0.68142829 -1.57686311 [110,] -0.24754438 -0.68142829 [111,] 1.39180475 -0.24754438 [112,] 1.45641674 1.39180475 [113,] 0.08011999 1.45641674 [114,] 0.88311329 0.08011999 [115,] -0.20747736 0.88311329 [116,] -0.18738115 -0.20747736 [117,] 0.91269813 -0.18738115 [118,] 0.01645032 0.91269813 [119,] -1.40208902 0.01645032 [120,] -1.21952217 -1.40208902 [121,] -0.81735155 -1.21952217 [122,] -0.16770080 -0.81735155 [123,] 0.18879075 -0.16770080 [124,] -0.29484141 0.18879075 [125,] 0.25357863 -0.29484141 [126,] 1.51594855 0.25357863 [127,] 0.46635820 1.51594855 [128,] -0.09031049 0.46635820 [129,] 1.86186428 -0.09031049 [130,] 1.51400475 1.86186428 [131,] 0.29198616 1.51400475 [132,] -0.94040310 0.29198616 [133,] 0.45231648 -0.94040310 [134,] 0.06163242 0.45231648 [135,] -0.91609346 0.06163242 [136,] -0.01287895 -0.91609346 [137,] -1.41451051 -0.01287895 [138,] -0.91011417 -1.41451051 [139,] -0.62297027 -0.91011417 [140,] -1.66411398 -0.62297027 [141,] 0.26303414 -1.66411398 [142,] -2.33763864 0.26303414 [143,] 0.57337181 -2.33763864 [144,] -1.02403967 0.57337181 [145,] 1.92586853 -1.02403967 [146,] 0.65298042 1.92586853 [147,] 0.53495092 0.65298042 [148,] -0.27647103 0.53495092 [149,] 1.85782240 -0.27647103 [150,] 1.59112913 1.85782240 [151,] 0.40022713 1.59112913 [152,] -0.33646733 0.40022713 [153,] 0.12309031 -0.33646733 [154,] 0.37375740 0.12309031 [155,] -3.29944534 0.37375740 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 0.25259656 -2.50195929 2 -0.10362459 0.25259656 3 1.43935622 -0.10362459 4 0.60301589 1.43935622 5 -1.49986919 0.60301589 6 1.25007667 -1.49986919 7 -0.30666227 1.25007667 8 -1.51814644 -0.30666227 9 0.07017090 -1.51814644 10 0.28384922 0.07017090 11 1.23711250 0.28384922 12 -0.77266558 1.23711250 13 -0.20951567 -0.77266558 14 1.54520421 -0.20951567 15 -0.82607122 1.54520421 16 1.38887076 -0.82607122 17 -0.24686164 1.38887076 18 0.21932352 -0.24686164 19 0.25430487 0.21932352 20 -2.56062231 0.25430487 21 0.84648459 -2.56062231 22 0.08870504 0.84648459 23 -0.36271090 0.08870504 24 0.20803506 -0.36271090 25 -0.61208258 0.20803506 26 1.66561029 -0.61208258 27 -0.76389617 1.66561029 28 0.25620005 -0.76389617 29 -1.52366752 0.25620005 30 -0.22732136 -1.52366752 31 1.57541777 -0.22732136 32 1.01590932 1.57541777 33 -0.69109449 1.01590932 34 -0.31978293 -0.69109449 35 -0.52165204 -0.31978293 36 0.73663218 -0.52165204 37 1.02418915 0.73663218 38 0.43841027 1.02418915 39 0.33049876 0.43841027 40 0.40740517 0.33049876 41 -1.68862323 0.40740517 42 -0.48035940 -1.68862323 43 -0.23288337 -0.48035940 44 1.51121194 -0.23288337 45 0.93011182 1.51121194 46 -1.43170746 0.93011182 47 0.69122568 -1.43170746 48 0.25744814 0.69122568 49 -0.19121453 0.25744814 50 1.84787900 -0.19121453 51 1.65848284 1.84787900 52 -0.33238294 1.65848284 53 -0.15592080 -0.33238294 54 -0.57881597 -0.15592080 55 -0.41566287 -0.57881597 56 -0.95007442 -0.41566287 57 -0.71941268 -0.95007442 58 -2.67788882 -0.71941268 59 1.72444582 -2.67788882 60 -0.85922903 1.72444582 61 -0.36779919 -0.85922903 62 -0.14056278 -0.36779919 63 -0.32811334 -0.14056278 64 0.97584996 -0.32811334 65 -0.60474359 0.97584996 66 0.79609459 -0.60474359 67 0.31581387 0.79609459 68 0.23961054 0.31581387 69 -0.07843381 0.23961054 70 -0.88551618 -0.07843381 71 -0.45347128 -0.88551618 72 -0.10492344 -0.45347128 73 0.04324563 -0.10492344 74 0.76166722 0.04324563 75 0.49162762 0.76166722 76 -0.23879811 0.49162762 77 -0.38452762 -0.23879811 78 -1.23910305 -0.38452762 79 -1.36122336 -1.23910305 80 0.23462462 -1.36122336 81 0.40989362 0.23462462 82 -0.07130310 0.40989362 83 0.31514776 -0.07130310 84 -1.48530197 0.31514776 85 0.96397365 -1.48530197 86 0.09098885 0.96397365 87 -0.49463476 0.09098885 88 1.65973790 -0.49463476 89 -0.46004047 1.65973790 90 0.23552727 -0.46004047 91 0.68698081 0.23552727 92 0.32532555 0.68698081 93 -0.12442052 0.32532555 94 0.02200843 -0.12442052 95 -0.19289595 0.02200843 96 2.13456315 -0.19289595 97 -0.61543160 2.13456315 98 -0.63592801 -0.61543160 99 0.74006743 -0.63592801 100 0.19728312 0.74006743 101 0.57043005 0.19728312 102 -0.72537705 0.57043005 103 -1.37322872 -0.72537705 104 -0.75310970 -1.37322872 105 2.26940234 -0.75310970 106 -1.68774649 2.26940234 107 1.85530822 -1.68774649 108 -1.57686311 1.85530822 109 -0.68142829 -1.57686311 110 -0.24754438 -0.68142829 111 1.39180475 -0.24754438 112 1.45641674 1.39180475 113 0.08011999 1.45641674 114 0.88311329 0.08011999 115 -0.20747736 0.88311329 116 -0.18738115 -0.20747736 117 0.91269813 -0.18738115 118 0.01645032 0.91269813 119 -1.40208902 0.01645032 120 -1.21952217 -1.40208902 121 -0.81735155 -1.21952217 122 -0.16770080 -0.81735155 123 0.18879075 -0.16770080 124 -0.29484141 0.18879075 125 0.25357863 -0.29484141 126 1.51594855 0.25357863 127 0.46635820 1.51594855 128 -0.09031049 0.46635820 129 1.86186428 -0.09031049 130 1.51400475 1.86186428 131 0.29198616 1.51400475 132 -0.94040310 0.29198616 133 0.45231648 -0.94040310 134 0.06163242 0.45231648 135 -0.91609346 0.06163242 136 -0.01287895 -0.91609346 137 -1.41451051 -0.01287895 138 -0.91011417 -1.41451051 139 -0.62297027 -0.91011417 140 -1.66411398 -0.62297027 141 0.26303414 -1.66411398 142 -2.33763864 0.26303414 143 0.57337181 -2.33763864 144 -1.02403967 0.57337181 145 1.92586853 -1.02403967 146 0.65298042 1.92586853 147 0.53495092 0.65298042 148 -0.27647103 0.53495092 149 1.85782240 -0.27647103 150 1.59112913 1.85782240 151 0.40022713 1.59112913 152 -0.33646733 0.40022713 153 0.12309031 -0.33646733 154 0.37375740 0.12309031 155 -3.29944534 0.37375740 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/7a0iu1290533427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/8a0iu1290533427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/93r0x1290533427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/rcomp/tmp/103r0x1290533427.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } Error: subscript out of bounds Execution halted