R version 2.15.2 (2012-10-26) -- "Trick or Treat" Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i686-pc-linux-gnu (32-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 <- array(list(4 + ,1 + ,1 + ,0 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,1 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,1 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,1 + ,0 + ,0 + ,0 + ,4 + ,1 + ,1 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,1 + ,0 + ,4 + ,1 + ,1 + ,0 + ,0 + ,4 + ,0 + ,0 + ,1 + ,1 + ,4 + ,0 + ,1 + ,1 + ,1 + ,4 + ,1 + ,1 + ,2 + ,0 + ,4 + ,1 + ,1 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,1 + ,2 + ,1 + ,4 + ,1 + ,0 + ,0 + ,0 + ,4 + ,1 + ,0 + ,1 + ,1 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,1 + ,0 + ,0 + ,1 + ,4 + ,0 + ,1 + ,1 + ,1 + ,4 + ,0 + ,0 + ,1 + ,0 + ,4 + ,1 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,1 + ,0 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,1 + ,0 + ,0 + ,0 + ,4 + ,1 + ,0 + ,0 + ,0 + ,4 + ,0 + ,1 + ,0 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,1 + ,1 + ,1 + ,0 + ,4 + ,0 + ,0 + ,1 + ,1 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,1 + ,0 + ,0 + ,4 + ,0 + ,0 + ,2 + ,1 + ,4 + ,0 + ,0 + ,1 + ,1 + ,4 + ,1 + ,0 + ,0 + ,1 + ,4 + ,1 + ,1 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,1 + ,1 + ,0 + ,4 + ,1 + ,1 + ,2 + ,0 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,2 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,1 + ,1 + ,1 + ,4 + ,0 + ,0 + ,1 + ,1 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,1 + ,1 + ,2 + ,1 + ,4 + ,1 + ,1 + ,0 + ,1 + ,4 + ,0 + ,0 + ,1 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,1 + ,1 + ,0 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,1 + ,2 + ,0 + ,4 + ,1 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,1 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,1 + ,1 + ,4 + ,1 + ,0 + ,1 + ,0 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,1 + ,0 + ,1 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,1 + ,1 + ,4 + ,0 + ,1 + ,2 + ,1 + ,4 + ,0 + ,1 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,1 + ,0 + ,1 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,2 + ,0 + ,4 + ,0 + ,0 + ,0 + ,1 + ,4 + ,1 + ,0 + ,0 + ,0 + ,2 + ,1 + ,0 + ,0 + ,1 + ,2 + ,1 + ,1 + ,1 + ,1 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,1 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,1 + ,1 + ,0 + ,0 + ,2 + ,1 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,1 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,1 + ,2 + ,1 + ,1 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,1 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,1 + ,2 + ,1 + ,0 + ,0 + ,1 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,1 + ,1 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,1 + ,1 + ,1 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,1 + ,0 + ,0 + ,0 + ,2 + ,1 + ,1 + ,1 + ,0 + ,2 + ,0 + ,1 + ,0 + ,0 + ,2 + ,0 + ,0 + ,1 + ,0 + ,2 + ,1 + ,1 + ,1 + ,0 + ,2 + ,1 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,1 + ,0 + ,0 + ,1 + ,2 + ,1 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,1 + ,2 + ,1 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,1 + ,1 + ,1 + ,0 + ,2 + ,0 + ,0 + ,1 + ,1 + ,2 + ,0 + ,0 + ,0 + ,1 + ,2 + ,0 + ,1 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,1 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,1 + ,2 + ,1 + ,0 + ,0 + ,0 + ,2 + ,1 + ,0 + ,0 + ,1 + ,2 + ,1 + ,0 + ,1 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,1 + ,0 + ,1 + ,1 + ,2 + ,1 + ,1 + ,1 + ,1 + ,2 + ,0 + ,1 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,2 + ,1 + ,2 + ,0 + ,1 + ,1 + ,1 + ,2 + ,1 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,1 + ,2 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,1 + ,0 + ,1 + ,2 + ,0 + ,1 + ,1 + ,0 + ,2 + ,0 + ,1 + ,0 + ,0 + ,2 + ,1 + ,0 + ,0 + ,0 + ,2 + ,0 + ,0 + ,0 + ,1 + ,2 + ,0 + ,0 + ,0 + ,1 + ,2 + ,1 + ,0 + ,2 + ,0 + ,2 + ,1 + ,0 + ,2 + ,0 + ,2 + ,1 + ,0 + ,1 + ,0) + ,dim=c(5 + ,154) + ,dimnames=list(c('Weken' + ,'GebruikLimieten' + ,'Review' + ,'GebruikStatistiek' + ,'Uitkomst') + ,1:154)) > y <- array(NA,dim=c(5,154),dimnames=list(c('Weken','GebruikLimieten','Review','GebruikStatistiek','Uitkomst'),1:154)) > 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 = '5' > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from 'package:base': as.Date, as.Date.numeric > 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 Uitkomst Weken GebruikLimieten Review GebruikStatistiek 1 1 4 1 1 0 2 0 4 0 0 0 3 0 4 0 0 0 4 0 4 0 0 0 5 0 4 0 0 0 6 1 4 1 0 0 7 0 4 0 0 0 8 0 4 0 1 0 9 1 4 0 0 0 10 0 4 1 0 0 11 0 4 1 1 0 12 0 4 0 0 0 13 0 4 0 0 1 14 0 4 1 1 0 15 1 4 0 0 1 16 1 4 0 1 1 17 0 4 1 1 2 18 0 4 1 1 0 19 1 4 0 0 0 20 1 4 0 1 2 21 0 4 1 0 0 22 1 4 1 0 1 23 1 4 0 0 0 24 1 4 1 0 0 25 1 4 0 1 1 26 0 4 0 0 1 27 1 4 1 0 0 28 0 4 0 0 1 29 1 4 0 0 0 30 0 4 0 0 0 31 0 4 0 0 0 32 0 4 1 0 0 33 0 4 1 0 0 34 1 4 0 1 0 35 0 4 0 0 0 36 0 4 0 0 0 37 0 4 1 1 1 38 1 4 0 0 1 39 1 4 0 0 0 40 0 4 0 1 0 41 1 4 0 0 2 42 1 4 0 0 1 43 1 4 1 0 0 44 0 4 1 1 0 45 0 4 0 0 0 46 1 4 0 0 0 47 0 4 0 0 0 48 1 4 0 0 0 49 1 4 0 0 0 50 0 4 0 0 0 51 0 4 0 1 1 52 0 4 1 1 2 53 1 4 0 0 0 54 0 4 0 0 2 55 0 4 0 0 0 56 1 4 0 1 1 57 1 4 0 0 1 58 1 4 0 0 0 59 1 4 0 0 0 60 1 4 1 1 2 61 1 4 1 1 0 62 0 4 0 0 1 63 0 4 0 0 0 64 1 4 1 1 0 65 0 4 0 0 0 66 0 4 0 0 0 67 0 4 0 1 2 68 0 4 1 0 0 69 1 4 0 0 0 70 0 4 0 0 1 71 0 4 0 0 0 72 1 4 0 0 0 73 1 4 0 0 1 74 0 4 1 0 1 75 1 4 0 0 0 76 1 4 0 1 0 77 1 4 0 0 0 78 1 4 0 0 1 79 1 4 0 1 2 80 0 4 0 1 0 81 0 4 0 0 0 82 1 4 1 0 1 83 0 4 0 0 0 84 0 4 0 0 2 85 1 4 0 0 0 86 0 4 1 0 0 87 1 2 1 0 0 88 1 2 1 1 1 89 0 2 0 0 0 90 1 2 0 0 0 91 0 2 0 0 0 92 0 2 1 1 0 93 0 2 1 0 0 94 0 2 0 0 0 95 0 2 0 1 0 96 1 2 0 0 0 97 0 2 1 1 0 98 0 2 0 0 0 99 0 2 1 0 0 100 1 2 0 0 0 101 1 2 1 0 0 102 0 2 0 0 0 103 0 2 0 0 0 104 0 2 0 0 0 105 0 2 0 1 1 106 0 2 0 0 0 107 0 2 0 0 0 108 0 2 1 1 1 109 0 2 0 0 0 110 0 2 1 0 0 111 0 2 1 1 1 112 0 2 0 1 0 113 0 2 0 0 1 114 0 2 1 1 1 115 0 2 1 0 0 116 0 2 0 0 0 117 1 2 1 0 0 118 0 2 1 0 0 119 0 2 0 0 0 120 1 2 0 0 0 121 0 2 1 0 0 122 0 2 0 0 0 123 0 2 1 1 1 124 1 2 0 0 1 125 1 2 0 0 0 126 0 2 0 1 0 127 0 2 0 0 0 128 1 2 0 0 0 129 0 2 0 0 0 130 1 2 0 0 0 131 0 2 1 0 0 132 1 2 1 0 0 133 0 2 1 0 1 134 0 2 0 0 0 135 0 2 0 0 0 136 0 2 0 0 0 137 1 2 1 0 1 138 1 2 1 1 1 139 0 2 0 1 0 140 0 2 0 0 0 141 1 2 0 0 2 142 1 2 0 1 1 143 0 2 1 0 0 144 1 2 0 0 0 145 0 2 0 0 0 146 1 2 0 1 0 147 0 2 0 1 1 148 0 2 0 1 0 149 0 2 1 0 0 150 1 2 0 0 0 151 1 2 0 0 0 152 0 2 1 0 2 153 0 2 1 0 2 154 0 2 1 0 1 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Weken GebruikLimieten Review 0.18530 0.07113 -0.06711 -0.03973 GebruikStatistiek 0.05731 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.5844 -0.4027 -0.2878 0.5302 0.7396 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.18530 0.13670 1.356 0.1773 Weken 0.07113 0.04018 1.770 0.0788 . GebruikLimieten -0.06711 0.08641 -0.777 0.4386 Review -0.03973 0.09454 -0.420 0.6749 GebruikStatistiek 0.05731 0.06601 0.868 0.3867 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.4886 on 149 degrees of freedom Multiple R-squared: 0.03426, Adjusted R-squared: 0.008338 F-statistic: 1.322 on 4 and 149 DF, p-value: 0.2646 > 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,] 1.073815e-48 2.147629e-48 1.000000e+00 [2,] 5.276447e-01 9.447106e-01 4.723553e-01 [3,] 7.169056e-01 5.661888e-01 2.830944e-01 [4,] 7.350746e-01 5.298507e-01 2.649254e-01 [5,] 6.461915e-01 7.076169e-01 3.538085e-01 [6,] 5.478674e-01 9.042653e-01 4.521326e-01 [7,] 5.111124e-01 9.777753e-01 4.888876e-01 [8,] 6.013017e-01 7.973965e-01 3.986983e-01 [9,] 5.892102e-01 8.215795e-01 4.107898e-01 [10,] 7.179950e-01 5.640099e-01 2.820050e-01 [11,] 6.677760e-01 6.644479e-01 3.322240e-01 [12,] 7.246925e-01 5.506150e-01 2.753075e-01 [13,] 7.050893e-01 5.898214e-01 2.949107e-01 [14,] 6.538724e-01 6.922552e-01 3.461276e-01 [15,] 6.618534e-01 6.762932e-01 3.381466e-01 [16,] 6.984919e-01 6.030163e-01 3.015081e-01 [17,] 7.261349e-01 5.477302e-01 2.738651e-01 [18,] 7.254304e-01 5.491392e-01 2.745696e-01 [19,] 7.405708e-01 5.188584e-01 2.594292e-01 [20,] 7.565944e-01 4.868112e-01 2.434056e-01 [21,] 7.596272e-01 4.807456e-01 2.403728e-01 [22,] 7.762319e-01 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5.410529e-01 2.705264e-01 [67,] 7.289676e-01 5.420647e-01 2.710324e-01 [68,] 7.286737e-01 5.426526e-01 2.713263e-01 [69,] 7.380883e-01 5.238234e-01 2.619117e-01 [70,] 7.454659e-01 5.090682e-01 2.545341e-01 [71,] 7.467599e-01 5.064802e-01 2.532401e-01 [72,] 7.530687e-01 4.938627e-01 2.469313e-01 [73,] 7.354708e-01 5.290584e-01 2.645292e-01 [74,] 7.227326e-01 5.545348e-01 2.772674e-01 [75,] 7.472352e-01 5.055296e-01 2.527648e-01 [76,] 7.301087e-01 5.397826e-01 2.698913e-01 [77,] 7.413688e-01 5.172624e-01 2.586312e-01 [78,] 7.593843e-01 4.812314e-01 2.406157e-01 [79,] 7.311438e-01 5.377123e-01 2.688562e-01 [80,] 7.480706e-01 5.038589e-01 2.519294e-01 [81,] 7.745791e-01 4.508417e-01 2.254209e-01 [82,] 7.897708e-01 4.204584e-01 2.102292e-01 [83,] 7.987402e-01 4.025196e-01 2.012598e-01 [84,] 7.988739e-01 4.022522e-01 2.011261e-01 [85,] 7.787224e-01 4.425551e-01 2.212776e-01 [86,] 7.561659e-01 4.876681e-01 2.438341e-01 [87,] 7.401913e-01 5.196174e-01 2.598087e-01 [88,] 7.126355e-01 5.747290e-01 2.873645e-01 [89,] 7.405972e-01 5.188056e-01 2.594028e-01 [90,] 7.069983e-01 5.860033e-01 2.930017e-01 [91,] 6.861099e-01 6.277801e-01 3.138901e-01 [92,] 6.529953e-01 6.940095e-01 3.470047e-01 [93,] 6.865549e-01 6.268902e-01 3.134451e-01 [94,] 7.441818e-01 5.116365e-01 2.558182e-01 [95,] 7.244945e-01 5.510110e-01 2.755055e-01 [96,] 7.038091e-01 5.923818e-01 2.961909e-01 [97,] 6.825749e-01 6.348501e-01 3.174251e-01 [98,] 6.602927e-01 6.794145e-01 3.397073e-01 [99,] 6.378688e-01 7.242625e-01 3.621312e-01 [100,] 6.161033e-01 7.677934e-01 3.838967e-01 [101,] 5.747672e-01 8.504657e-01 4.252328e-01 [102,] 5.525904e-01 8.948192e-01 4.474096e-01 [103,] 5.096329e-01 9.807342e-01 4.903671e-01 [104,] 4.656819e-01 9.313638e-01 5.343181e-01 [105,] 4.326803e-01 8.653606e-01 5.673197e-01 [106,] 4.266333e-01 8.532667e-01 5.733667e-01 [107,] 3.853105e-01 7.706211e-01 6.146895e-01 [108,] 3.430241e-01 6.860482e-01 6.569759e-01 [109,] 3.244805e-01 6.489610e-01 6.755195e-01 [110,] 4.078241e-01 8.156481e-01 5.921759e-01 [111,] 3.600895e-01 7.201790e-01 6.399105e-01 [112,] 3.439534e-01 6.879067e-01 6.560466e-01 [113,] 3.673987e-01 7.347974e-01 6.326013e-01 [114,] 3.207378e-01 6.414755e-01 6.792622e-01 [115,] 3.048455e-01 6.096910e-01 6.951545e-01 [116,] 2.652780e-01 5.305559e-01 7.347220e-01 [117,] 2.669047e-01 5.338093e-01 7.330953e-01 [118,] 2.903362e-01 5.806725e-01 7.096638e-01 [119,] 2.726369e-01 5.452739e-01 7.273631e-01 [120,] 2.516769e-01 5.033537e-01 7.483231e-01 [121,] 2.746773e-01 5.493546e-01 7.253227e-01 [122,] 2.511348e-01 5.022696e-01 7.488652e-01 [123,] 2.770412e-01 5.540824e-01 7.229588e-01 [124,] 2.339999e-01 4.679997e-01 7.660001e-01 [125,] 3.179885e-01 6.359771e-01 6.820115e-01 [126,] 2.709108e-01 5.418216e-01 7.290892e-01 [127,] 2.391673e-01 4.783347e-01 7.608327e-01 [128,] 2.150894e-01 4.301788e-01 7.849106e-01 [129,] 2.012433e-01 4.024866e-01 7.987567e-01 [130,] 2.726117e-01 5.452235e-01 7.273883e-01 [131,] 5.137320e-01 9.725360e-01 4.862680e-01 [132,] 4.813606e-01 9.627213e-01 5.186394e-01 [133,] 5.832877e-01 8.334245e-01 4.167123e-01 [134,] 4.988745e-01 9.977491e-01 5.011255e-01 [135,] 5.606693e-01 8.786614e-01 4.393307e-01 [136,] 4.467562e-01 8.935125e-01 5.532438e-01 [137,] 3.698769e-01 7.397537e-01 6.301231e-01 [138,] 6.168055e-01 7.663890e-01 3.831945e-01 [139,] 1.000000e+00 1.864434e-46 9.322169e-47 > postscript(file="/var/fisher/rcomp/tmp/1ijwc1355751562.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/fisher/rcomp/tmp/2t5691355751562.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/3jrol1355751562.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/4eff41355751562.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/5h2no1355751562.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 = 154 Frequency = 1 1 2 3 4 5 6 7 0.6370248 -0.4698118 -0.4698118 -0.4698118 -0.4698118 0.5972933 -0.4698118 8 9 10 11 12 13 14 -0.4300803 0.5301882 -0.4027067 -0.3629752 -0.4698118 -0.5271235 -0.3629752 15 16 17 18 19 20 21 0.4728765 0.5126081 -0.4775984 -0.3629752 0.5301882 0.4552964 -0.4027067 22 23 24 25 26 27 28 0.5399817 0.5301882 0.5972933 0.5126081 -0.5271235 0.5972933 -0.5271235 29 30 31 32 33 34 35 0.5301882 -0.4698118 -0.4698118 -0.4027067 -0.4027067 0.5699197 -0.4698118 36 37 38 39 40 41 42 -0.4698118 -0.4202868 0.4728765 0.5301882 -0.4300803 0.4155649 0.4728765 43 44 45 46 47 48 49 0.5972933 -0.3629752 -0.4698118 0.5301882 -0.4698118 0.5301882 0.5301882 50 51 52 53 54 55 56 -0.4698118 -0.4873919 -0.4775984 0.5301882 -0.5844351 -0.4698118 0.5126081 57 58 59 60 61 62 63 0.4728765 0.5301882 0.5301882 0.5224016 0.6370248 -0.5271235 -0.4698118 64 65 66 67 68 69 70 0.6370248 -0.4698118 -0.4698118 -0.5447036 -0.4027067 0.5301882 -0.5271235 71 72 73 74 75 76 77 -0.4698118 0.5301882 0.4728765 -0.4600183 0.5301882 0.5699197 0.5301882 78 79 80 81 82 83 84 0.4728765 0.4552964 -0.4300803 -0.4698118 0.5399817 -0.4698118 -0.5844351 85 86 87 88 89 90 91 0.5301882 -0.4027067 0.7395473 0.7219672 -0.3275579 0.6724421 -0.3275579 92 93 94 95 96 97 98 -0.2207212 -0.2604527 -0.3275579 -0.2878264 0.6724421 -0.2207212 -0.3275579 99 100 101 102 103 104 105 -0.2604527 0.6724421 0.7395473 -0.3275579 -0.3275579 -0.3275579 -0.3451380 106 107 108 109 110 111 112 -0.3275579 -0.3275579 -0.2780328 -0.3275579 -0.2604527 -0.2780328 -0.2878264 113 114 115 116 117 118 119 -0.3848695 -0.2780328 -0.2604527 -0.3275579 0.7395473 -0.2604527 -0.3275579 120 121 122 123 124 125 126 0.6724421 -0.2604527 -0.3275579 -0.2780328 0.6151305 0.6724421 -0.2878264 127 128 129 130 131 132 133 -0.3275579 0.6724421 -0.3275579 0.6724421 -0.2604527 0.7395473 -0.3177644 134 135 136 137 138 139 140 -0.3275579 -0.3275579 -0.3275579 0.6822356 0.7219672 -0.2878264 -0.3275579 141 142 143 144 145 146 147 0.5578188 0.6548620 -0.2604527 0.6724421 -0.3275579 0.7121736 -0.3451380 148 149 150 151 152 153 154 -0.2878264 -0.2604527 0.6724421 0.6724421 -0.3750760 -0.3750760 -0.3177644 > postscript(file="/var/fisher/rcomp/tmp/63uvs1355751562.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 = 154 Frequency = 1 lag(myerror, k = 1) myerror 0 0.6370248 NA 1 -0.4698118 0.6370248 2 -0.4698118 -0.4698118 3 -0.4698118 -0.4698118 4 -0.4698118 -0.4698118 5 0.5972933 -0.4698118 6 -0.4698118 0.5972933 7 -0.4300803 -0.4698118 8 0.5301882 -0.4300803 9 -0.4027067 0.5301882 10 -0.3629752 -0.4027067 11 -0.4698118 -0.3629752 12 -0.5271235 -0.4698118 13 -0.3629752 -0.5271235 14 0.4728765 -0.3629752 15 0.5126081 0.4728765 16 -0.4775984 0.5126081 17 -0.3629752 -0.4775984 18 0.5301882 -0.3629752 19 0.4552964 0.5301882 20 -0.4027067 0.4552964 21 0.5399817 -0.4027067 22 0.5301882 0.5399817 23 0.5972933 0.5301882 24 0.5126081 0.5972933 25 -0.5271235 0.5126081 26 0.5972933 -0.5271235 27 -0.5271235 0.5972933 28 0.5301882 -0.5271235 29 -0.4698118 0.5301882 30 -0.4698118 -0.4698118 31 -0.4027067 -0.4698118 32 -0.4027067 -0.4027067 33 0.5699197 -0.4027067 34 -0.4698118 0.5699197 35 -0.4698118 -0.4698118 36 -0.4202868 -0.4698118 37 0.4728765 -0.4202868 38 0.5301882 0.4728765 39 -0.4300803 0.5301882 40 0.4155649 -0.4300803 41 0.4728765 0.4155649 42 0.5972933 0.4728765 43 -0.3629752 0.5972933 44 -0.4698118 -0.3629752 45 0.5301882 -0.4698118 46 -0.4698118 0.5301882 47 0.5301882 -0.4698118 48 0.5301882 0.5301882 49 -0.4698118 0.5301882 50 -0.4873919 -0.4698118 51 -0.4775984 -0.4873919 52 0.5301882 -0.4775984 53 -0.5844351 0.5301882 54 -0.4698118 -0.5844351 55 0.5126081 -0.4698118 56 0.4728765 0.5126081 57 0.5301882 0.4728765 58 0.5301882 0.5301882 59 0.5224016 0.5301882 60 0.6370248 0.5224016 61 -0.5271235 0.6370248 62 -0.4698118 -0.5271235 63 0.6370248 -0.4698118 64 -0.4698118 0.6370248 65 -0.4698118 -0.4698118 66 -0.5447036 -0.4698118 67 -0.4027067 -0.5447036 68 0.5301882 -0.4027067 69 -0.5271235 0.5301882 70 -0.4698118 -0.5271235 71 0.5301882 -0.4698118 72 0.4728765 0.5301882 73 -0.4600183 0.4728765 74 0.5301882 -0.4600183 75 0.5699197 0.5301882 76 0.5301882 0.5699197 77 0.4728765 0.5301882 78 0.4552964 0.4728765 79 -0.4300803 0.4552964 80 -0.4698118 -0.4300803 81 0.5399817 -0.4698118 82 -0.4698118 0.5399817 83 -0.5844351 -0.4698118 84 0.5301882 -0.5844351 85 -0.4027067 0.5301882 86 0.7395473 -0.4027067 87 0.7219672 0.7395473 88 -0.3275579 0.7219672 89 0.6724421 -0.3275579 90 -0.3275579 0.6724421 91 -0.2207212 -0.3275579 92 -0.2604527 -0.2207212 93 -0.3275579 -0.2604527 94 -0.2878264 -0.3275579 95 0.6724421 -0.2878264 96 -0.2207212 0.6724421 97 -0.3275579 -0.2207212 98 -0.2604527 -0.3275579 99 0.6724421 -0.2604527 100 0.7395473 0.6724421 101 -0.3275579 0.7395473 102 -0.3275579 -0.3275579 103 -0.3275579 -0.3275579 104 -0.3451380 -0.3275579 105 -0.3275579 -0.3451380 106 -0.3275579 -0.3275579 107 -0.2780328 -0.3275579 108 -0.3275579 -0.2780328 109 -0.2604527 -0.3275579 110 -0.2780328 -0.2604527 111 -0.2878264 -0.2780328 112 -0.3848695 -0.2878264 113 -0.2780328 -0.3848695 114 -0.2604527 -0.2780328 115 -0.3275579 -0.2604527 116 0.7395473 -0.3275579 117 -0.2604527 0.7395473 118 -0.3275579 -0.2604527 119 0.6724421 -0.3275579 120 -0.2604527 0.6724421 121 -0.3275579 -0.2604527 122 -0.2780328 -0.3275579 123 0.6151305 -0.2780328 124 0.6724421 0.6151305 125 -0.2878264 0.6724421 126 -0.3275579 -0.2878264 127 0.6724421 -0.3275579 128 -0.3275579 0.6724421 129 0.6724421 -0.3275579 130 -0.2604527 0.6724421 131 0.7395473 -0.2604527 132 -0.3177644 0.7395473 133 -0.3275579 -0.3177644 134 -0.3275579 -0.3275579 135 -0.3275579 -0.3275579 136 0.6822356 -0.3275579 137 0.7219672 0.6822356 138 -0.2878264 0.7219672 139 -0.3275579 -0.2878264 140 0.5578188 -0.3275579 141 0.6548620 0.5578188 142 -0.2604527 0.6548620 143 0.6724421 -0.2604527 144 -0.3275579 0.6724421 145 0.7121736 -0.3275579 146 -0.3451380 0.7121736 147 -0.2878264 -0.3451380 148 -0.2604527 -0.2878264 149 0.6724421 -0.2604527 150 0.6724421 0.6724421 151 -0.3750760 0.6724421 152 -0.3750760 -0.3750760 153 -0.3177644 -0.3750760 154 NA -0.3177644 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -0.4698118 0.6370248 [2,] -0.4698118 -0.4698118 [3,] -0.4698118 -0.4698118 [4,] -0.4698118 -0.4698118 [5,] 0.5972933 -0.4698118 [6,] -0.4698118 0.5972933 [7,] -0.4300803 -0.4698118 [8,] 0.5301882 -0.4300803 [9,] -0.4027067 0.5301882 [10,] -0.3629752 -0.4027067 [11,] -0.4698118 -0.3629752 [12,] -0.5271235 -0.4698118 [13,] -0.3629752 -0.5271235 [14,] 0.4728765 -0.3629752 [15,] 0.5126081 0.4728765 [16,] -0.4775984 0.5126081 [17,] -0.3629752 -0.4775984 [18,] 0.5301882 -0.3629752 [19,] 0.4552964 0.5301882 [20,] -0.4027067 0.4552964 [21,] 0.5399817 -0.4027067 [22,] 0.5301882 0.5399817 [23,] 0.5972933 0.5301882 [24,] 0.5126081 0.5972933 [25,] -0.5271235 0.5126081 [26,] 0.5972933 -0.5271235 [27,] -0.5271235 0.5972933 [28,] 0.5301882 -0.5271235 [29,] -0.4698118 0.5301882 [30,] -0.4698118 -0.4698118 [31,] -0.4027067 -0.4698118 [32,] -0.4027067 -0.4027067 [33,] 0.5699197 -0.4027067 [34,] -0.4698118 0.5699197 [35,] -0.4698118 -0.4698118 [36,] -0.4202868 -0.4698118 [37,] 0.4728765 -0.4202868 [38,] 0.5301882 0.4728765 [39,] -0.4300803 0.5301882 [40,] 0.4155649 -0.4300803 [41,] 0.4728765 0.4155649 [42,] 0.5972933 0.4728765 [43,] -0.3629752 0.5972933 [44,] -0.4698118 -0.3629752 [45,] 0.5301882 -0.4698118 [46,] -0.4698118 0.5301882 [47,] 0.5301882 -0.4698118 [48,] 0.5301882 0.5301882 [49,] -0.4698118 0.5301882 [50,] -0.4873919 -0.4698118 [51,] -0.4775984 -0.4873919 [52,] 0.5301882 -0.4775984 [53,] -0.5844351 0.5301882 [54,] -0.4698118 -0.5844351 [55,] 0.5126081 -0.4698118 [56,] 0.4728765 0.5126081 [57,] 0.5301882 0.4728765 [58,] 0.5301882 0.5301882 [59,] 0.5224016 0.5301882 [60,] 0.6370248 0.5224016 [61,] -0.5271235 0.6370248 [62,] -0.4698118 -0.5271235 [63,] 0.6370248 -0.4698118 [64,] -0.4698118 0.6370248 [65,] -0.4698118 -0.4698118 [66,] -0.5447036 -0.4698118 [67,] -0.4027067 -0.5447036 [68,] 0.5301882 -0.4027067 [69,] -0.5271235 0.5301882 [70,] -0.4698118 -0.5271235 [71,] 0.5301882 -0.4698118 [72,] 0.4728765 0.5301882 [73,] -0.4600183 0.4728765 [74,] 0.5301882 -0.4600183 [75,] 0.5699197 0.5301882 [76,] 0.5301882 0.5699197 [77,] 0.4728765 0.5301882 [78,] 0.4552964 0.4728765 [79,] -0.4300803 0.4552964 [80,] -0.4698118 -0.4300803 [81,] 0.5399817 -0.4698118 [82,] -0.4698118 0.5399817 [83,] -0.5844351 -0.4698118 [84,] 0.5301882 -0.5844351 [85,] -0.4027067 0.5301882 [86,] 0.7395473 -0.4027067 [87,] 0.7219672 0.7395473 [88,] -0.3275579 0.7219672 [89,] 0.6724421 -0.3275579 [90,] -0.3275579 0.6724421 [91,] -0.2207212 -0.3275579 [92,] -0.2604527 -0.2207212 [93,] -0.3275579 -0.2604527 [94,] -0.2878264 -0.3275579 [95,] 0.6724421 -0.2878264 [96,] -0.2207212 0.6724421 [97,] -0.3275579 -0.2207212 [98,] -0.2604527 -0.3275579 [99,] 0.6724421 -0.2604527 [100,] 0.7395473 0.6724421 [101,] -0.3275579 0.7395473 [102,] -0.3275579 -0.3275579 [103,] -0.3275579 -0.3275579 [104,] -0.3451380 -0.3275579 [105,] -0.3275579 -0.3451380 [106,] -0.3275579 -0.3275579 [107,] -0.2780328 -0.3275579 [108,] -0.3275579 -0.2780328 [109,] -0.2604527 -0.3275579 [110,] -0.2780328 -0.2604527 [111,] -0.2878264 -0.2780328 [112,] -0.3848695 -0.2878264 [113,] -0.2780328 -0.3848695 [114,] -0.2604527 -0.2780328 [115,] -0.3275579 -0.2604527 [116,] 0.7395473 -0.3275579 [117,] -0.2604527 0.7395473 [118,] -0.3275579 -0.2604527 [119,] 0.6724421 -0.3275579 [120,] -0.2604527 0.6724421 [121,] -0.3275579 -0.2604527 [122,] -0.2780328 -0.3275579 [123,] 0.6151305 -0.2780328 [124,] 0.6724421 0.6151305 [125,] -0.2878264 0.6724421 [126,] -0.3275579 -0.2878264 [127,] 0.6724421 -0.3275579 [128,] -0.3275579 0.6724421 [129,] 0.6724421 -0.3275579 [130,] -0.2604527 0.6724421 [131,] 0.7395473 -0.2604527 [132,] -0.3177644 0.7395473 [133,] -0.3275579 -0.3177644 [134,] -0.3275579 -0.3275579 [135,] -0.3275579 -0.3275579 [136,] 0.6822356 -0.3275579 [137,] 0.7219672 0.6822356 [138,] -0.2878264 0.7219672 [139,] -0.3275579 -0.2878264 [140,] 0.5578188 -0.3275579 [141,] 0.6548620 0.5578188 [142,] -0.2604527 0.6548620 [143,] 0.6724421 -0.2604527 [144,] -0.3275579 0.6724421 [145,] 0.7121736 -0.3275579 [146,] -0.3451380 0.7121736 [147,] -0.2878264 -0.3451380 [148,] -0.2604527 -0.2878264 [149,] 0.6724421 -0.2604527 [150,] 0.6724421 0.6724421 [151,] -0.3750760 0.6724421 [152,] -0.3750760 -0.3750760 [153,] -0.3177644 -0.3750760 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -0.4698118 0.6370248 2 -0.4698118 -0.4698118 3 -0.4698118 -0.4698118 4 -0.4698118 -0.4698118 5 0.5972933 -0.4698118 6 -0.4698118 0.5972933 7 -0.4300803 -0.4698118 8 0.5301882 -0.4300803 9 -0.4027067 0.5301882 10 -0.3629752 -0.4027067 11 -0.4698118 -0.3629752 12 -0.5271235 -0.4698118 13 -0.3629752 -0.5271235 14 0.4728765 -0.3629752 15 0.5126081 0.4728765 16 -0.4775984 0.5126081 17 -0.3629752 -0.4775984 18 0.5301882 -0.3629752 19 0.4552964 0.5301882 20 -0.4027067 0.4552964 21 0.5399817 -0.4027067 22 0.5301882 0.5399817 23 0.5972933 0.5301882 24 0.5126081 0.5972933 25 -0.5271235 0.5126081 26 0.5972933 -0.5271235 27 -0.5271235 0.5972933 28 0.5301882 -0.5271235 29 -0.4698118 0.5301882 30 -0.4698118 -0.4698118 31 -0.4027067 -0.4698118 32 -0.4027067 -0.4027067 33 0.5699197 -0.4027067 34 -0.4698118 0.5699197 35 -0.4698118 -0.4698118 36 -0.4202868 -0.4698118 37 0.4728765 -0.4202868 38 0.5301882 0.4728765 39 -0.4300803 0.5301882 40 0.4155649 -0.4300803 41 0.4728765 0.4155649 42 0.5972933 0.4728765 43 -0.3629752 0.5972933 44 -0.4698118 -0.3629752 45 0.5301882 -0.4698118 46 -0.4698118 0.5301882 47 0.5301882 -0.4698118 48 0.5301882 0.5301882 49 -0.4698118 0.5301882 50 -0.4873919 -0.4698118 51 -0.4775984 -0.4873919 52 0.5301882 -0.4775984 53 -0.5844351 0.5301882 54 -0.4698118 -0.5844351 55 0.5126081 -0.4698118 56 0.4728765 0.5126081 57 0.5301882 0.4728765 58 0.5301882 0.5301882 59 0.5224016 0.5301882 60 0.6370248 0.5224016 61 -0.5271235 0.6370248 62 -0.4698118 -0.5271235 63 0.6370248 -0.4698118 64 -0.4698118 0.6370248 65 -0.4698118 -0.4698118 66 -0.5447036 -0.4698118 67 -0.4027067 -0.5447036 68 0.5301882 -0.4027067 69 -0.5271235 0.5301882 70 -0.4698118 -0.5271235 71 0.5301882 -0.4698118 72 0.4728765 0.5301882 73 -0.4600183 0.4728765 74 0.5301882 -0.4600183 75 0.5699197 0.5301882 76 0.5301882 0.5699197 77 0.4728765 0.5301882 78 0.4552964 0.4728765 79 -0.4300803 0.4552964 80 -0.4698118 -0.4300803 81 0.5399817 -0.4698118 82 -0.4698118 0.5399817 83 -0.5844351 -0.4698118 84 0.5301882 -0.5844351 85 -0.4027067 0.5301882 86 0.7395473 -0.4027067 87 0.7219672 0.7395473 88 -0.3275579 0.7219672 89 0.6724421 -0.3275579 90 -0.3275579 0.6724421 91 -0.2207212 -0.3275579 92 -0.2604527 -0.2207212 93 -0.3275579 -0.2604527 94 -0.2878264 -0.3275579 95 0.6724421 -0.2878264 96 -0.2207212 0.6724421 97 -0.3275579 -0.2207212 98 -0.2604527 -0.3275579 99 0.6724421 -0.2604527 100 0.7395473 0.6724421 101 -0.3275579 0.7395473 102 -0.3275579 -0.3275579 103 -0.3275579 -0.3275579 104 -0.3451380 -0.3275579 105 -0.3275579 -0.3451380 106 -0.3275579 -0.3275579 107 -0.2780328 -0.3275579 108 -0.3275579 -0.2780328 109 -0.2604527 -0.3275579 110 -0.2780328 -0.2604527 111 -0.2878264 -0.2780328 112 -0.3848695 -0.2878264 113 -0.2780328 -0.3848695 114 -0.2604527 -0.2780328 115 -0.3275579 -0.2604527 116 0.7395473 -0.3275579 117 -0.2604527 0.7395473 118 -0.3275579 -0.2604527 119 0.6724421 -0.3275579 120 -0.2604527 0.6724421 121 -0.3275579 -0.2604527 122 -0.2780328 -0.3275579 123 0.6151305 -0.2780328 124 0.6724421 0.6151305 125 -0.2878264 0.6724421 126 -0.3275579 -0.2878264 127 0.6724421 -0.3275579 128 -0.3275579 0.6724421 129 0.6724421 -0.3275579 130 -0.2604527 0.6724421 131 0.7395473 -0.2604527 132 -0.3177644 0.7395473 133 -0.3275579 -0.3177644 134 -0.3275579 -0.3275579 135 -0.3275579 -0.3275579 136 0.6822356 -0.3275579 137 0.7219672 0.6822356 138 -0.2878264 0.7219672 139 -0.3275579 -0.2878264 140 0.5578188 -0.3275579 141 0.6548620 0.5578188 142 -0.2604527 0.6548620 143 0.6724421 -0.2604527 144 -0.3275579 0.6724421 145 0.7121736 -0.3275579 146 -0.3451380 0.7121736 147 -0.2878264 -0.3451380 148 -0.2604527 -0.2878264 149 0.6724421 -0.2604527 150 0.6724421 0.6724421 151 -0.3750760 0.6724421 152 -0.3750760 -0.3750760 153 -0.3177644 -0.3750760 > 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/fisher/rcomp/tmp/78ucg1355751562.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/fisher/rcomp/tmp/8x72d1355751562.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/fisher/rcomp/tmp/9gs2q1355751562.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/fisher/rcomp/tmp/10toa91355751562.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/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/11qfi21355751562.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/12e2ui1355751562.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$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$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/13g8mt1355751563.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/14e8z11355751563.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/fisher/rcomp/tmp/15w0ps1355751563.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/fisher/rcomp/tmp/16mnww1355751563.tab") + } > > try(system("convert tmp/1ijwc1355751562.ps tmp/1ijwc1355751562.png",intern=TRUE)) character(0) > try(system("convert tmp/2t5691355751562.ps tmp/2t5691355751562.png",intern=TRUE)) character(0) > try(system("convert tmp/3jrol1355751562.ps tmp/3jrol1355751562.png",intern=TRUE)) character(0) > try(system("convert tmp/4eff41355751562.ps tmp/4eff41355751562.png",intern=TRUE)) character(0) > try(system("convert tmp/5h2no1355751562.ps tmp/5h2no1355751562.png",intern=TRUE)) character(0) > try(system("convert tmp/63uvs1355751562.ps tmp/63uvs1355751562.png",intern=TRUE)) character(0) > try(system("convert tmp/78ucg1355751562.ps tmp/78ucg1355751562.png",intern=TRUE)) character(0) > try(system("convert tmp/8x72d1355751562.ps tmp/8x72d1355751562.png",intern=TRUE)) character(0) > try(system("convert tmp/9gs2q1355751562.ps tmp/9gs2q1355751562.png",intern=TRUE)) character(0) > try(system("convert tmp/10toa91355751562.ps tmp/10toa91355751562.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 8.266 1.805 10.137