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Type 'q()' to quit R. > x <- array(list(13 + ,1 + ,0 + ,12 + ,1 + ,0 + ,11 + ,1 + ,0 + ,10 + ,1 + ,1 + ,8 + ,1 + ,1 + ,7 + ,1 + ,0 + ,10 + ,1 + ,1 + ,8 + ,1 + ,1 + ,13 + ,1 + ,1 + ,11 + ,1 + ,1 + ,8 + ,1 + ,1 + ,9 + ,1 + ,0 + ,12 + ,1 + ,0 + ,11 + ,0 + ,1 + ,9 + ,1 + ,0 + ,8 + ,1 + ,1 + ,9 + ,1 + ,1 + ,8 + ,1 + ,0 + ,11 + ,1 + ,1 + ,10 + ,1 + ,0 + ,15 + ,1 + ,0 + ,11 + ,1 + ,1 + ,16 + ,1 + ,1 + ,12 + ,1 + ,1 + ,11 + ,1 + ,1 + ,11 + ,1 + ,0 + ,10 + ,0 + ,1 + ,8 + ,1 + ,1 + ,11 + ,1 + ,1 + ,11 + ,1 + ,1 + ,13 + ,1 + ,1 + ,15 + ,0 + ,1 + ,12 + ,1 + ,0 + ,14 + ,0 + ,1 + ,12 + ,1 + ,1 + ,7 + ,1 + ,1 + ,8 + ,1 + ,1 + ,12 + ,1 + ,0 + ,10 + ,0 + ,1 + ,9 + ,1 + ,1 + ,12 + ,0 + ,1 + ,10 + ,1 + ,0 + ,9 + ,0 + ,1 + ,10 + ,1 + ,1 + ,13 + ,0 + ,1 + ,8 + ,1 + ,0 + ,11 + ,0 + ,0 + ,11 + ,0 + ,1 + ,9 + ,1 + ,1 + ,9 + ,1 + ,1 + ,12 + ,0 + ,0 + ,10 + ,0 + ,0 + ,9 + ,0 + ,0 + ,14 + ,0 + ,1 + ,8 + ,0 + ,1 + ,9 + ,0 + ,0 + ,14 + ,0 + ,0 + ,8 + ,0 + ,1 + ,16 + ,0 + ,1 + ,14 + ,0 + ,1 + ,14 + ,0 + ,0 + ,8 + ,0 + ,1 + ,11 + ,0 + ,1 + ,11 + ,0 + ,0 + ,13 + ,0 + ,1 + ,12 + ,0 + ,1 + ,9 + ,0 + ,1 + ,10 + ,0 + ,0 + ,12 + ,0 + ,1 + ,11 + ,0 + ,1 + ,15 + ,0 + ,0 + ,14 + ,0 + ,1 + ,16 + ,1 + ,1 + ,16 + ,1 + ,1 + ,9 + ,1 + ,1 + ,10 + ,1 + ,1 + ,14 + ,1 + ,1 + ,14 + ,0 + ,1 + ,21 + ,0 + ,0 + ,14 + ,1 + ,0 + ,17 + ,1 + ,1 + ,18 + ,1 + ,0 + ,16 + ,1 + ,1 + ,14 + ,0 + ,1 + ,13 + ,0 + ,0 + ,17 + ,1 + ,1 + ,10 + ,1 + ,1 + ,17 + ,1 + ,0 + ,13 + ,1 + ,1 + ,18 + ,1 + ,1 + ,14 + ,1 + ,0 + ,14 + ,1 + ,1 + ,15 + ,1 + ,0 + ,12 + ,0 + ,1 + ,17 + ,0 + ,1 + ,15 + ,0 + ,1 + ,12 + ,0 + ,0 + ,13 + ,0 + ,1 + ,14 + ,0 + ,0 + ,18 + ,0 + ,1 + ,16 + ,1 + ,1 + ,21 + ,1 + ,0 + ,20 + ,1 + ,1 + ,10 + ,0 + ,0 + ,16 + ,0 + ,0 + ,19 + ,1 + ,0 + ,12 + ,1 + ,1 + ,13 + ,0 + ,1 + ,20 + ,0 + ,0 + ,14 + ,0 + ,0 + ,10 + ,0 + ,1 + ,13 + ,0 + ,0 + ,11 + ,0 + ,0 + ,13 + ,0 + ,1 + ,13 + ,0 + ,1 + ,11 + ,0 + ,1 + ,15 + ,0 + ,0 + ,14 + ,0 + ,0 + ,10 + ,0 + ,0 + ,24 + ,1 + ,0 + ,23 + ,1 + ,1 + ,19 + ,1 + ,0 + ,19 + ,1 + ,0 + ,22 + ,1 + ,1 + ,16 + ,1 + ,1 + ,16 + ,0 + ,0 + ,20 + ,1 + ,1 + ,11 + ,1 + ,0 + ,20 + ,1 + ,1 + ,15 + ,1 + ,0 + ,21 + ,1 + ,0 + ,17 + ,1 + ,0 + ,25 + ,0 + ,0 + ,17 + ,0 + ,1 + ,16 + ,0 + ,0 + ,17 + ,0 + ,0 + ,15 + ,0 + ,0 + ,15 + ,0 + ,0 + ,26 + ,1 + ,0 + ,25 + ,1 + ,0 + ,20 + ,1 + ,0 + ,20 + ,1 + ,1 + ,26 + ,1 + ,0) + ,dim=c(3 + ,143) + ,dimnames=list(c('depression' + ,'course' + ,'gender') + ,1:143)) > y <- array(NA,dim=c(3,143),dimnames=list(c('depression','course','gender'),1:143)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '1' > #'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 depression course gender 1 13 1 0 2 12 1 0 3 11 1 0 4 10 1 1 5 8 1 1 6 7 1 0 7 10 1 1 8 8 1 1 9 13 1 1 10 11 1 1 11 8 1 1 12 9 1 0 13 12 1 0 14 11 0 1 15 9 1 0 16 8 1 1 17 9 1 1 18 8 1 0 19 11 1 1 20 10 1 0 21 15 1 0 22 11 1 1 23 16 1 1 24 12 1 1 25 11 1 1 26 11 1 0 27 10 0 1 28 8 1 1 29 11 1 1 30 11 1 1 31 13 1 1 32 15 0 1 33 12 1 0 34 14 0 1 35 12 1 1 36 7 1 1 37 8 1 1 38 12 1 0 39 10 0 1 40 9 1 1 41 12 0 1 42 10 1 0 43 9 0 1 44 10 1 1 45 13 0 1 46 8 1 0 47 11 0 0 48 11 0 1 49 9 1 1 50 9 1 1 51 12 0 0 52 10 0 0 53 9 0 0 54 14 0 1 55 8 0 1 56 9 0 0 57 14 0 0 58 8 0 1 59 16 0 1 60 14 0 1 61 14 0 0 62 8 0 1 63 11 0 1 64 11 0 0 65 13 0 1 66 12 0 1 67 9 0 1 68 10 0 0 69 12 0 1 70 11 0 1 71 15 0 0 72 14 0 1 73 16 1 1 74 16 1 1 75 9 1 1 76 10 1 1 77 14 1 1 78 14 0 1 79 21 0 0 80 14 1 0 81 17 1 1 82 18 1 0 83 16 1 1 84 14 0 1 85 13 0 0 86 17 1 1 87 10 1 1 88 17 1 0 89 13 1 1 90 18 1 1 91 14 1 0 92 14 1 1 93 15 1 0 94 12 0 1 95 17 0 1 96 15 0 1 97 12 0 0 98 13 0 1 99 14 0 0 100 18 0 1 101 16 1 1 102 21 1 0 103 20 1 1 104 10 0 0 105 16 0 0 106 19 1 0 107 12 1 1 108 13 0 1 109 20 0 0 110 14 0 0 111 10 0 1 112 13 0 0 113 11 0 0 114 13 0 1 115 13 0 1 116 11 0 1 117 15 0 0 118 14 0 0 119 10 0 0 120 24 1 0 121 23 1 1 122 19 1 0 123 19 1 0 124 22 1 1 125 16 1 1 126 16 0 0 127 20 1 1 128 11 1 0 129 20 1 1 130 15 1 0 131 21 1 0 132 17 1 0 133 25 0 0 134 17 0 1 135 16 0 0 136 17 0 0 137 15 0 0 138 15 0 0 139 26 1 0 140 25 1 0 141 20 1 0 142 20 1 1 143 26 1 0 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) course gender 14.1163 0.8119 -1.8983 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -7.928 -3.073 -0.218 2.427 11.072 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 14.1163 0.6434 21.940 < 2e-16 *** course 0.8119 0.6967 1.165 0.24589 gender -1.8983 0.6991 -2.715 0.00745 ** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 4.14 on 140 degrees of freedom Multiple R-squared: 0.05735, Adjusted R-squared: 0.04388 F-statistic: 4.259 on 2 and 140 DF, p-value: 0.01601 > 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,] 2.813502e-01 5.627004e-01 0.71864982 [2,] 1.531991e-01 3.063983e-01 0.84680087 [3,] 8.428228e-02 1.685646e-01 0.91571772 [4,] 1.022293e-01 2.044586e-01 0.89777070 [5,] 5.822263e-02 1.164453e-01 0.94177737 [6,] 3.924035e-02 7.848071e-02 0.96075965 [7,] 2.526460e-02 5.052920e-02 0.97473540 [8,] 1.513956e-02 3.027912e-02 0.98486044 [9,] 7.265325e-03 1.453065e-02 0.99273468 [10,] 4.685513e-03 9.371026e-03 0.99531449 [11,] 3.020391e-03 6.040783e-03 0.99697961 [12,] 1.501034e-03 3.002068e-03 0.99849897 [13,] 1.416292e-03 2.832584e-03 0.99858371 [14,] 8.395328e-04 1.679066e-03 0.99916047 [15,] 4.351213e-04 8.702425e-04 0.99956488 [16,] 1.625496e-03 3.250991e-03 0.99837450 [17,] 9.781207e-04 1.956241e-03 0.99902188 [18,] 6.079646e-03 1.215929e-02 0.99392035 [19,] 4.134130e-03 8.268260e-03 0.99586587 [20,] 2.469882e-03 4.939763e-03 0.99753012 [21,] 1.564175e-03 3.128350e-03 0.99843583 [22,] 8.922606e-04 1.784521e-03 0.99910774 [23,] 8.386671e-04 1.677334e-03 0.99916133 [24,] 4.965326e-04 9.930652e-04 0.99950347 [25,] 2.905340e-04 5.810679e-04 0.99970947 [26,] 2.486254e-04 4.972508e-04 0.99975137 [27,] 3.442410e-04 6.884820e-04 0.99965576 [28,] 2.384314e-04 4.768627e-04 0.99976157 [29,] 1.592426e-04 3.184851e-04 0.99984076 [30,] 1.025263e-04 2.050525e-04 0.99989747 [31,] 1.850566e-04 3.701133e-04 0.99981494 [32,] 2.028198e-04 4.056396e-04 0.99979718 [33,] 1.496874e-04 2.993747e-04 0.99985031 [34,] 1.168350e-04 2.336699e-04 0.99988317 [35,] 9.752613e-05 1.950523e-04 0.99990247 [36,] 5.304057e-05 1.060811e-04 0.99994696 [37,] 4.861986e-05 9.723971e-05 0.99995138 [38,] 4.841618e-05 9.683235e-05 0.99995158 [39,] 3.574923e-05 7.149847e-05 0.99996425 [40,] 2.188569e-05 4.377138e-05 0.99997811 [41,] 5.155299e-05 1.031060e-04 0.99994845 [42,] 3.423128e-05 6.846256e-05 0.99996577 [43,] 1.947873e-05 3.895746e-05 0.99998052 [44,] 2.067581e-05 4.135162e-05 0.99997932 [45,] 2.354769e-05 4.709539e-05 0.99997645 [46,] 1.376676e-05 2.753351e-05 0.99998623 [47,] 1.209295e-05 2.418590e-05 0.99998791 [48,] 1.547327e-05 3.094653e-05 0.99998453 [49,] 1.415674e-05 2.831347e-05 0.99998584 [50,] 2.180664e-05 4.361328e-05 0.99997819 [51,] 2.650847e-05 5.301693e-05 0.99997349 [52,] 2.445913e-05 4.891825e-05 0.99997554 [53,] 3.469747e-05 6.939493e-05 0.99996530 [54,] 8.595260e-05 1.719052e-04 0.99991405 [55,] 7.449438e-05 1.489888e-04 0.99992551 [56,] 5.994294e-05 1.198859e-04 0.99994006 [57,] 9.025071e-05 1.805014e-04 0.99990975 [58,] 5.702642e-05 1.140528e-04 0.99994297 [59,] 4.400666e-05 8.801331e-05 0.99995599 [60,] 2.962328e-05 5.924656e-05 0.99997038 [61,] 1.774358e-05 3.548717e-05 0.99998226 [62,] 1.816812e-05 3.633623e-05 0.99998183 [63,] 1.899167e-05 3.798334e-05 0.99998101 [64,] 1.152055e-05 2.304111e-05 0.99998848 [65,] 7.261019e-06 1.452204e-05 0.99999274 [66,] 7.855570e-06 1.571114e-05 0.99999214 [67,] 6.380373e-06 1.276075e-05 0.99999362 [68,] 1.856869e-05 3.713739e-05 0.99998143 [69,] 4.207366e-05 8.414732e-05 0.99995793 [70,] 7.755698e-05 1.551140e-04 0.99992244 [71,] 1.152573e-04 2.305147e-04 0.99988474 [72,] 1.362585e-04 2.725170e-04 0.99986374 [73,] 1.050078e-04 2.100156e-04 0.99989499 [74,] 1.793988e-03 3.587977e-03 0.99820601 [75,] 2.301682e-03 4.603365e-03 0.99769832 [76,] 4.152620e-03 8.305240e-03 0.99584738 [77,] 7.782448e-03 1.556490e-02 0.99221755 [78,] 9.386234e-03 1.877247e-02 0.99061377 [79,] 7.359256e-03 1.471851e-02 0.99264074 [80,] 5.607744e-03 1.121549e-02 0.99439226 [81,] 7.600506e-03 1.520101e-02 0.99239949 [82,] 1.335018e-02 2.670036e-02 0.98664982 [83,] 1.675693e-02 3.351386e-02 0.98324307 [84,] 1.907253e-02 3.814507e-02 0.98092747 [85,] 2.644063e-02 5.288125e-02 0.97355937 [86,] 3.276860e-02 6.553720e-02 0.96723140 [87,] 3.638802e-02 7.277605e-02 0.96361198 [88,] 4.421104e-02 8.842207e-02 0.95578896 [89,] 3.525106e-02 7.050212e-02 0.96474894 [90,] 4.188072e-02 8.376144e-02 0.95811928 [91,] 3.610483e-02 7.220967e-02 0.96389517 [92,] 3.113294e-02 6.226588e-02 0.96886706 [93,] 2.350064e-02 4.700129e-02 0.97649936 [94,] 1.806258e-02 3.612516e-02 0.98193742 [95,] 2.771233e-02 5.542466e-02 0.97228767 [96,] 2.857005e-02 5.714009e-02 0.97142995 [97,] 4.689254e-02 9.378509e-02 0.95310746 [98,] 6.371559e-02 1.274312e-01 0.93628441 [99,] 7.401558e-02 1.480312e-01 0.92598442 [100,] 6.247412e-02 1.249482e-01 0.93752588 [101,] 6.771347e-02 1.354269e-01 0.93228653 [102,] 1.023669e-01 2.047338e-01 0.89763308 [103,] 8.056074e-02 1.611215e-01 0.91943926 [104,] 1.209998e-01 2.419995e-01 0.87900023 [105,] 9.598937e-02 1.919787e-01 0.90401063 [106,] 9.544370e-02 1.908874e-01 0.90455630 [107,] 7.792012e-02 1.558402e-01 0.92207988 [108,] 8.109531e-02 1.621906e-01 0.91890469 [109,] 6.373760e-02 1.274752e-01 0.93626240 [110,] 5.014800e-02 1.002960e-01 0.94985200 [111,] 5.371342e-02 1.074268e-01 0.94628658 [112,] 4.070936e-02 8.141872e-02 0.95929064 [113,] 3.205759e-02 6.411518e-02 0.96794241 [114,] 6.115730e-02 1.223146e-01 0.93884270 [115,] 1.112842e-01 2.225685e-01 0.88871577 [116,] 1.568140e-01 3.136280e-01 0.84318602 [117,] 1.366816e-01 2.733632e-01 0.86331838 [118,] 1.167541e-01 2.335083e-01 0.88324587 [119,] 1.309448e-01 2.618897e-01 0.86905517 [120,] 1.226190e-01 2.452380e-01 0.87738099 [121,] 9.392793e-02 1.878559e-01 0.90607207 [122,] 7.868966e-02 1.573793e-01 0.92131034 [123,] 2.899529e-01 5.799057e-01 0.71004713 [124,] 2.448599e-01 4.897198e-01 0.75514010 [125,] 3.955029e-01 7.910057e-01 0.60449713 [126,] 3.425627e-01 6.851254e-01 0.65743731 [127,] 4.967909e-01 9.935817e-01 0.50320913 [128,] 9.084758e-01 1.830484e-01 0.09152421 [129,] 9.294813e-01 1.410374e-01 0.07051871 [130,] 8.646208e-01 2.707584e-01 0.13537922 [131,] 7.905478e-01 4.189045e-01 0.20945223 [132,] 6.356147e-01 7.287706e-01 0.36438528 > postscript(file="/var/wessaorg/rcomp/tmp/1zr6u1324134258.ps",horizontal=F,onefile=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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/24sf21324134258.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3s2e21324134258.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4u6541324134258.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5m14f1324134258.ps",horizontal=F,onefile=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 = 143 Frequency = 1 1 2 3 4 5 6 -1.92813119 -2.92813119 -3.92813119 -3.02981893 -5.02981893 -7.92813119 7 8 9 10 11 12 -3.02981893 -5.02981893 -0.02981893 -2.02981893 -5.02981893 -5.92813119 13 14 15 16 17 18 -2.92813119 -1.21795226 -5.92813119 -5.02981893 -4.02981893 -6.92813119 19 20 21 22 23 24 -2.02981893 -4.92813119 0.07186881 -2.02981893 2.97018107 -1.02981893 25 26 27 28 29 30 -2.02981893 -3.92813119 -2.21795226 -5.02981893 -2.02981893 -2.02981893 31 32 33 34 35 36 -0.02981893 2.78204774 -2.92813119 1.78204774 -1.02981893 -6.02981893 37 38 39 40 41 42 -5.02981893 -2.92813119 -2.21795226 -4.02981893 -0.21795226 -4.92813119 43 44 45 46 47 48 -3.21795226 -3.02981893 0.78204774 -6.92813119 -3.11626451 -1.21795226 49 50 51 52 53 54 -4.02981893 -4.02981893 -2.11626451 -4.11626451 -5.11626451 1.78204774 55 56 57 58 59 60 -4.21795226 -5.11626451 -0.11626451 -4.21795226 3.78204774 1.78204774 61 62 63 64 65 66 -0.11626451 -4.21795226 -1.21795226 -3.11626451 0.78204774 -0.21795226 67 68 69 70 71 72 -3.21795226 -4.11626451 -0.21795226 -1.21795226 0.88373549 1.78204774 73 74 75 76 77 78 2.97018107 2.97018107 -4.02981893 -3.02981893 0.97018107 1.78204774 79 80 81 82 83 84 6.88373549 -0.92813119 3.97018107 3.07186881 2.97018107 1.78204774 85 86 87 88 89 90 -1.11626451 3.97018107 -3.02981893 2.07186881 -0.02981893 4.97018107 91 92 93 94 95 96 -0.92813119 0.97018107 0.07186881 -0.21795226 4.78204774 2.78204774 97 98 99 100 101 102 -2.11626451 0.78204774 -0.11626451 5.78204774 2.97018107 6.07186881 103 104 105 106 107 108 6.97018107 -4.11626451 1.88373549 4.07186881 -1.02981893 0.78204774 109 110 111 112 113 114 5.88373549 -0.11626451 -2.21795226 -1.11626451 -3.11626451 0.78204774 115 116 117 118 119 120 0.78204774 -1.21795226 0.88373549 -0.11626451 -4.11626451 9.07186881 121 122 123 124 125 126 9.97018107 4.07186881 4.07186881 8.97018107 2.97018107 1.88373549 127 128 129 130 131 132 6.97018107 -3.92813119 6.97018107 0.07186881 6.07186881 2.07186881 133 134 135 136 137 138 10.88373549 4.78204774 1.88373549 2.88373549 0.88373549 0.88373549 139 140 141 142 143 11.07186881 10.07186881 5.07186881 6.97018107 11.07186881 > postscript(file="/var/wessaorg/rcomp/tmp/6o21y1324134258.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 143 Frequency = 1 lag(myerror, k = 1) myerror 0 -1.92813119 NA 1 -2.92813119 -1.92813119 2 -3.92813119 -2.92813119 3 -3.02981893 -3.92813119 4 -5.02981893 -3.02981893 5 -7.92813119 -5.02981893 6 -3.02981893 -7.92813119 7 -5.02981893 -3.02981893 8 -0.02981893 -5.02981893 9 -2.02981893 -0.02981893 10 -5.02981893 -2.02981893 11 -5.92813119 -5.02981893 12 -2.92813119 -5.92813119 13 -1.21795226 -2.92813119 14 -5.92813119 -1.21795226 15 -5.02981893 -5.92813119 16 -4.02981893 -5.02981893 17 -6.92813119 -4.02981893 18 -2.02981893 -6.92813119 19 -4.92813119 -2.02981893 20 0.07186881 -4.92813119 21 -2.02981893 0.07186881 22 2.97018107 -2.02981893 23 -1.02981893 2.97018107 24 -2.02981893 -1.02981893 25 -3.92813119 -2.02981893 26 -2.21795226 -3.92813119 27 -5.02981893 -2.21795226 28 -2.02981893 -5.02981893 29 -2.02981893 -2.02981893 30 -0.02981893 -2.02981893 31 2.78204774 -0.02981893 32 -2.92813119 2.78204774 33 1.78204774 -2.92813119 34 -1.02981893 1.78204774 35 -6.02981893 -1.02981893 36 -5.02981893 -6.02981893 37 -2.92813119 -5.02981893 38 -2.21795226 -2.92813119 39 -4.02981893 -2.21795226 40 -0.21795226 -4.02981893 41 -4.92813119 -0.21795226 42 -3.21795226 -4.92813119 43 -3.02981893 -3.21795226 44 0.78204774 -3.02981893 45 -6.92813119 0.78204774 46 -3.11626451 -6.92813119 47 -1.21795226 -3.11626451 48 -4.02981893 -1.21795226 49 -4.02981893 -4.02981893 50 -2.11626451 -4.02981893 51 -4.11626451 -2.11626451 52 -5.11626451 -4.11626451 53 1.78204774 -5.11626451 54 -4.21795226 1.78204774 55 -5.11626451 -4.21795226 56 -0.11626451 -5.11626451 57 -4.21795226 -0.11626451 58 3.78204774 -4.21795226 59 1.78204774 3.78204774 60 -0.11626451 1.78204774 61 -4.21795226 -0.11626451 62 -1.21795226 -4.21795226 63 -3.11626451 -1.21795226 64 0.78204774 -3.11626451 65 -0.21795226 0.78204774 66 -3.21795226 -0.21795226 67 -4.11626451 -3.21795226 68 -0.21795226 -4.11626451 69 -1.21795226 -0.21795226 70 0.88373549 -1.21795226 71 1.78204774 0.88373549 72 2.97018107 1.78204774 73 2.97018107 2.97018107 74 -4.02981893 2.97018107 75 -3.02981893 -4.02981893 76 0.97018107 -3.02981893 77 1.78204774 0.97018107 78 6.88373549 1.78204774 79 -0.92813119 6.88373549 80 3.97018107 -0.92813119 81 3.07186881 3.97018107 82 2.97018107 3.07186881 83 1.78204774 2.97018107 84 -1.11626451 1.78204774 85 3.97018107 -1.11626451 86 -3.02981893 3.97018107 87 2.07186881 -3.02981893 88 -0.02981893 2.07186881 89 4.97018107 -0.02981893 90 -0.92813119 4.97018107 91 0.97018107 -0.92813119 92 0.07186881 0.97018107 93 -0.21795226 0.07186881 94 4.78204774 -0.21795226 95 2.78204774 4.78204774 96 -2.11626451 2.78204774 97 0.78204774 -2.11626451 98 -0.11626451 0.78204774 99 5.78204774 -0.11626451 100 2.97018107 5.78204774 101 6.07186881 2.97018107 102 6.97018107 6.07186881 103 -4.11626451 6.97018107 104 1.88373549 -4.11626451 105 4.07186881 1.88373549 106 -1.02981893 4.07186881 107 0.78204774 -1.02981893 108 5.88373549 0.78204774 109 -0.11626451 5.88373549 110 -2.21795226 -0.11626451 111 -1.11626451 -2.21795226 112 -3.11626451 -1.11626451 113 0.78204774 -3.11626451 114 0.78204774 0.78204774 115 -1.21795226 0.78204774 116 0.88373549 -1.21795226 117 -0.11626451 0.88373549 118 -4.11626451 -0.11626451 119 9.07186881 -4.11626451 120 9.97018107 9.07186881 121 4.07186881 9.97018107 122 4.07186881 4.07186881 123 8.97018107 4.07186881 124 2.97018107 8.97018107 125 1.88373549 2.97018107 126 6.97018107 1.88373549 127 -3.92813119 6.97018107 128 6.97018107 -3.92813119 129 0.07186881 6.97018107 130 6.07186881 0.07186881 131 2.07186881 6.07186881 132 10.88373549 2.07186881 133 4.78204774 10.88373549 134 1.88373549 4.78204774 135 2.88373549 1.88373549 136 0.88373549 2.88373549 137 0.88373549 0.88373549 138 11.07186881 0.88373549 139 10.07186881 11.07186881 140 5.07186881 10.07186881 141 6.97018107 5.07186881 142 11.07186881 6.97018107 143 NA 11.07186881 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -2.92813119 -1.92813119 [2,] -3.92813119 -2.92813119 [3,] -3.02981893 -3.92813119 [4,] -5.02981893 -3.02981893 [5,] -7.92813119 -5.02981893 [6,] -3.02981893 -7.92813119 [7,] -5.02981893 -3.02981893 [8,] -0.02981893 -5.02981893 [9,] -2.02981893 -0.02981893 [10,] -5.02981893 -2.02981893 [11,] -5.92813119 -5.02981893 [12,] -2.92813119 -5.92813119 [13,] -1.21795226 -2.92813119 [14,] -5.92813119 -1.21795226 [15,] -5.02981893 -5.92813119 [16,] -4.02981893 -5.02981893 [17,] -6.92813119 -4.02981893 [18,] -2.02981893 -6.92813119 [19,] -4.92813119 -2.02981893 [20,] 0.07186881 -4.92813119 [21,] -2.02981893 0.07186881 [22,] 2.97018107 -2.02981893 [23,] -1.02981893 2.97018107 [24,] -2.02981893 -1.02981893 [25,] -3.92813119 -2.02981893 [26,] -2.21795226 -3.92813119 [27,] -5.02981893 -2.21795226 [28,] -2.02981893 -5.02981893 [29,] -2.02981893 -2.02981893 [30,] -0.02981893 -2.02981893 [31,] 2.78204774 -0.02981893 [32,] -2.92813119 2.78204774 [33,] 1.78204774 -2.92813119 [34,] -1.02981893 1.78204774 [35,] -6.02981893 -1.02981893 [36,] -5.02981893 -6.02981893 [37,] -2.92813119 -5.02981893 [38,] -2.21795226 -2.92813119 [39,] -4.02981893 -2.21795226 [40,] -0.21795226 -4.02981893 [41,] -4.92813119 -0.21795226 [42,] -3.21795226 -4.92813119 [43,] -3.02981893 -3.21795226 [44,] 0.78204774 -3.02981893 [45,] -6.92813119 0.78204774 [46,] -3.11626451 -6.92813119 [47,] -1.21795226 -3.11626451 [48,] -4.02981893 -1.21795226 [49,] -4.02981893 -4.02981893 [50,] -2.11626451 -4.02981893 [51,] -4.11626451 -2.11626451 [52,] -5.11626451 -4.11626451 [53,] 1.78204774 -5.11626451 [54,] -4.21795226 1.78204774 [55,] -5.11626451 -4.21795226 [56,] -0.11626451 -5.11626451 [57,] -4.21795226 -0.11626451 [58,] 3.78204774 -4.21795226 [59,] 1.78204774 3.78204774 [60,] -0.11626451 1.78204774 [61,] -4.21795226 -0.11626451 [62,] -1.21795226 -4.21795226 [63,] -3.11626451 -1.21795226 [64,] 0.78204774 -3.11626451 [65,] -0.21795226 0.78204774 [66,] -3.21795226 -0.21795226 [67,] -4.11626451 -3.21795226 [68,] -0.21795226 -4.11626451 [69,] -1.21795226 -0.21795226 [70,] 0.88373549 -1.21795226 [71,] 1.78204774 0.88373549 [72,] 2.97018107 1.78204774 [73,] 2.97018107 2.97018107 [74,] -4.02981893 2.97018107 [75,] -3.02981893 -4.02981893 [76,] 0.97018107 -3.02981893 [77,] 1.78204774 0.97018107 [78,] 6.88373549 1.78204774 [79,] -0.92813119 6.88373549 [80,] 3.97018107 -0.92813119 [81,] 3.07186881 3.97018107 [82,] 2.97018107 3.07186881 [83,] 1.78204774 2.97018107 [84,] -1.11626451 1.78204774 [85,] 3.97018107 -1.11626451 [86,] -3.02981893 3.97018107 [87,] 2.07186881 -3.02981893 [88,] -0.02981893 2.07186881 [89,] 4.97018107 -0.02981893 [90,] -0.92813119 4.97018107 [91,] 0.97018107 -0.92813119 [92,] 0.07186881 0.97018107 [93,] -0.21795226 0.07186881 [94,] 4.78204774 -0.21795226 [95,] 2.78204774 4.78204774 [96,] -2.11626451 2.78204774 [97,] 0.78204774 -2.11626451 [98,] -0.11626451 0.78204774 [99,] 5.78204774 -0.11626451 [100,] 2.97018107 5.78204774 [101,] 6.07186881 2.97018107 [102,] 6.97018107 6.07186881 [103,] -4.11626451 6.97018107 [104,] 1.88373549 -4.11626451 [105,] 4.07186881 1.88373549 [106,] -1.02981893 4.07186881 [107,] 0.78204774 -1.02981893 [108,] 5.88373549 0.78204774 [109,] -0.11626451 5.88373549 [110,] -2.21795226 -0.11626451 [111,] -1.11626451 -2.21795226 [112,] -3.11626451 -1.11626451 [113,] 0.78204774 -3.11626451 [114,] 0.78204774 0.78204774 [115,] -1.21795226 0.78204774 [116,] 0.88373549 -1.21795226 [117,] -0.11626451 0.88373549 [118,] -4.11626451 -0.11626451 [119,] 9.07186881 -4.11626451 [120,] 9.97018107 9.07186881 [121,] 4.07186881 9.97018107 [122,] 4.07186881 4.07186881 [123,] 8.97018107 4.07186881 [124,] 2.97018107 8.97018107 [125,] 1.88373549 2.97018107 [126,] 6.97018107 1.88373549 [127,] -3.92813119 6.97018107 [128,] 6.97018107 -3.92813119 [129,] 0.07186881 6.97018107 [130,] 6.07186881 0.07186881 [131,] 2.07186881 6.07186881 [132,] 10.88373549 2.07186881 [133,] 4.78204774 10.88373549 [134,] 1.88373549 4.78204774 [135,] 2.88373549 1.88373549 [136,] 0.88373549 2.88373549 [137,] 0.88373549 0.88373549 [138,] 11.07186881 0.88373549 [139,] 10.07186881 11.07186881 [140,] 5.07186881 10.07186881 [141,] 6.97018107 5.07186881 [142,] 11.07186881 6.97018107 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -2.92813119 -1.92813119 2 -3.92813119 -2.92813119 3 -3.02981893 -3.92813119 4 -5.02981893 -3.02981893 5 -7.92813119 -5.02981893 6 -3.02981893 -7.92813119 7 -5.02981893 -3.02981893 8 -0.02981893 -5.02981893 9 -2.02981893 -0.02981893 10 -5.02981893 -2.02981893 11 -5.92813119 -5.02981893 12 -2.92813119 -5.92813119 13 -1.21795226 -2.92813119 14 -5.92813119 -1.21795226 15 -5.02981893 -5.92813119 16 -4.02981893 -5.02981893 17 -6.92813119 -4.02981893 18 -2.02981893 -6.92813119 19 -4.92813119 -2.02981893 20 0.07186881 -4.92813119 21 -2.02981893 0.07186881 22 2.97018107 -2.02981893 23 -1.02981893 2.97018107 24 -2.02981893 -1.02981893 25 -3.92813119 -2.02981893 26 -2.21795226 -3.92813119 27 -5.02981893 -2.21795226 28 -2.02981893 -5.02981893 29 -2.02981893 -2.02981893 30 -0.02981893 -2.02981893 31 2.78204774 -0.02981893 32 -2.92813119 2.78204774 33 1.78204774 -2.92813119 34 -1.02981893 1.78204774 35 -6.02981893 -1.02981893 36 -5.02981893 -6.02981893 37 -2.92813119 -5.02981893 38 -2.21795226 -2.92813119 39 -4.02981893 -2.21795226 40 -0.21795226 -4.02981893 41 -4.92813119 -0.21795226 42 -3.21795226 -4.92813119 43 -3.02981893 -3.21795226 44 0.78204774 -3.02981893 45 -6.92813119 0.78204774 46 -3.11626451 -6.92813119 47 -1.21795226 -3.11626451 48 -4.02981893 -1.21795226 49 -4.02981893 -4.02981893 50 -2.11626451 -4.02981893 51 -4.11626451 -2.11626451 52 -5.11626451 -4.11626451 53 1.78204774 -5.11626451 54 -4.21795226 1.78204774 55 -5.11626451 -4.21795226 56 -0.11626451 -5.11626451 57 -4.21795226 -0.11626451 58 3.78204774 -4.21795226 59 1.78204774 3.78204774 60 -0.11626451 1.78204774 61 -4.21795226 -0.11626451 62 -1.21795226 -4.21795226 63 -3.11626451 -1.21795226 64 0.78204774 -3.11626451 65 -0.21795226 0.78204774 66 -3.21795226 -0.21795226 67 -4.11626451 -3.21795226 68 -0.21795226 -4.11626451 69 -1.21795226 -0.21795226 70 0.88373549 -1.21795226 71 1.78204774 0.88373549 72 2.97018107 1.78204774 73 2.97018107 2.97018107 74 -4.02981893 2.97018107 75 -3.02981893 -4.02981893 76 0.97018107 -3.02981893 77 1.78204774 0.97018107 78 6.88373549 1.78204774 79 -0.92813119 6.88373549 80 3.97018107 -0.92813119 81 3.07186881 3.97018107 82 2.97018107 3.07186881 83 1.78204774 2.97018107 84 -1.11626451 1.78204774 85 3.97018107 -1.11626451 86 -3.02981893 3.97018107 87 2.07186881 -3.02981893 88 -0.02981893 2.07186881 89 4.97018107 -0.02981893 90 -0.92813119 4.97018107 91 0.97018107 -0.92813119 92 0.07186881 0.97018107 93 -0.21795226 0.07186881 94 4.78204774 -0.21795226 95 2.78204774 4.78204774 96 -2.11626451 2.78204774 97 0.78204774 -2.11626451 98 -0.11626451 0.78204774 99 5.78204774 -0.11626451 100 2.97018107 5.78204774 101 6.07186881 2.97018107 102 6.97018107 6.07186881 103 -4.11626451 6.97018107 104 1.88373549 -4.11626451 105 4.07186881 1.88373549 106 -1.02981893 4.07186881 107 0.78204774 -1.02981893 108 5.88373549 0.78204774 109 -0.11626451 5.88373549 110 -2.21795226 -0.11626451 111 -1.11626451 -2.21795226 112 -3.11626451 -1.11626451 113 0.78204774 -3.11626451 114 0.78204774 0.78204774 115 -1.21795226 0.78204774 116 0.88373549 -1.21795226 117 -0.11626451 0.88373549 118 -4.11626451 -0.11626451 119 9.07186881 -4.11626451 120 9.97018107 9.07186881 121 4.07186881 9.97018107 122 4.07186881 4.07186881 123 8.97018107 4.07186881 124 2.97018107 8.97018107 125 1.88373549 2.97018107 126 6.97018107 1.88373549 127 -3.92813119 6.97018107 128 6.97018107 -3.92813119 129 0.07186881 6.97018107 130 6.07186881 0.07186881 131 2.07186881 6.07186881 132 10.88373549 2.07186881 133 4.78204774 10.88373549 134 1.88373549 4.78204774 135 2.88373549 1.88373549 136 0.88373549 2.88373549 137 0.88373549 0.88373549 138 11.07186881 0.88373549 139 10.07186881 11.07186881 140 5.07186881 10.07186881 141 6.97018107 5.07186881 142 11.07186881 6.97018107 > 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/wessaorg/rcomp/tmp/79ve91324134258.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8vy8u1324134258.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9peot1324134258.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/1073w01324134258.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/116b201324134258.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/12h8531324134258.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/139ajy1324134258.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/14ckwl1324134258.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/15gbuc1324134258.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/16936y1324134258.tab") + } > > try(system("convert tmp/1zr6u1324134258.ps tmp/1zr6u1324134258.png",intern=TRUE)) character(0) > try(system("convert tmp/24sf21324134258.ps tmp/24sf21324134258.png",intern=TRUE)) character(0) > try(system("convert tmp/3s2e21324134258.ps tmp/3s2e21324134258.png",intern=TRUE)) character(0) > try(system("convert tmp/4u6541324134258.ps tmp/4u6541324134258.png",intern=TRUE)) character(0) > try(system("convert tmp/5m14f1324134258.ps tmp/5m14f1324134258.png",intern=TRUE)) character(0) > try(system("convert tmp/6o21y1324134258.ps tmp/6o21y1324134258.png",intern=TRUE)) character(0) > try(system("convert tmp/79ve91324134258.ps tmp/79ve91324134258.png",intern=TRUE)) character(0) > try(system("convert tmp/8vy8u1324134258.ps tmp/8vy8u1324134258.png",intern=TRUE)) character(0) > try(system("convert tmp/9peot1324134258.ps tmp/9peot1324134258.png",intern=TRUE)) character(0) > try(system("convert tmp/1073w01324134258.ps tmp/1073w01324134258.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.373 0.640 5.056