R version 2.9.0 (2009-04-17) Copyright (C) 2009 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 + ,1 + ,3 + ,4 + ,2 + ,1 + ,1 + ,1 + ,3 + ,3 + ,3 + ,1 + ,2 + ,2 + ,3 + ,3 + ,4 + ,2 + ,4 + ,1 + ,3 + ,5 + ,3 + ,2 + ,1 + ,1 + ,3 + ,4 + ,2 + ,2 + ,4 + ,1 + ,3 + ,1 + ,2 + ,3 + ,1 + ,3 + ,5 + ,3 + ,1 + ,1 + ,1 + ,1 + ,5 + ,2 + ,1 + ,1 + ,1 + ,3 + ,2 + ,3 + ,1 + ,2 + ,4 + ,2 + ,2 + ,5 + ,2 + ,3 + ,5 + ,3 + ,1 + ,3 + ,1 + ,3 + ,3 + ,2 + ,1 + ,1 + ,1 + ,2 + ,4 + ,4 + ,1 + ,2 + ,1 + ,3 + ,4 + ,1 + ,1 + ,2 + ,1 + ,3 + ,4 + ,2 + ,2 + ,5 + ,2 + ,3 + ,4 + ,4 + ,2 + ,2 + ,1 + ,3 + ,5 + ,2 + ,1 + ,2 + ,1 + ,3 + ,3 + ,3 + ,2 + ,2 + ,1 + ,3 + ,5 + ,3 + ,1 + ,2 + ,1 + ,3 + ,3 + ,3 + ,2 + ,3 + ,1 + ,3 + ,4 + ,1 + ,1 + ,3 + ,1 + ,3 + ,4 + ,3 + ,2 + ,3 + ,2 + ,3 + ,4 + ,3 + ,2 + ,1 + ,1 + ,3 + ,3 + ,2 + ,1 + ,1 + ,2 + ,3 + ,5 + ,2 + ,2 + ,4 + ,1 + ,2 + ,4 + ,2 + ,1 + ,1 + ,4 + ,3 + ,5 + ,2 + ,1 + ,3 + ,1 + ,3 + ,2 + ,4 + ,1 + ,2 + ,1 + ,2 + ,5 + ,3 + ,2 + ,1 + ,1 + ,3 + ,4 + ,1 + ,2 + ,2 + ,1 + ,3 + ,5 + ,2 + ,2 + ,1 + ,1 + ,3 + ,4 + ,1 + ,1 + ,2 + ,1 + 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,5 + ,2 + ,1 + ,1 + ,1 + ,3 + ,3 + ,2 + ,1 + ,3 + ,3 + ,2 + ,4 + ,4 + ,2 + ,3 + ,1 + ,3 + ,4 + ,2 + ,1 + ,2 + ,2 + ,2 + ,4 + ,4 + ,1 + ,1 + ,1 + ,3 + ,4 + ,3 + ,1 + ,1 + ,1 + ,2 + ,4 + ,2 + ,2 + ,4 + ,1 + ,3 + ,5 + ,4 + ,1 + ,3 + ,1 + ,3 + ,5 + ,1 + ,1 + ,3 + ,1 + ,3 + ,5 + ,3 + ,2 + ,3 + ,1 + ,3 + ,5 + ,1 + ,2 + ,3 + ,1 + ,3 + ,5 + ,2 + ,1 + ,3 + ,1 + ,3 + ,4 + ,4 + ,1 + ,2 + ,3 + ,3 + ,4 + ,3 + ,1 + ,1 + ,2 + ,3 + ,4 + ,2 + ,2 + ,2 + ,1 + ,3 + ,4 + ,1 + ,2 + ,1 + ,1 + ,3 + ,5 + ,2 + ,2 + ,2 + ,1 + ,3 + ,4 + ,3 + ,1 + ,1 + ,1 + ,2 + ,5 + ,2 + ,1 + ,4 + ,1 + ,3 + ,4 + ,3 + ,1 + ,1 + ,2 + ,2 + ,5 + ,3 + ,1 + ,1 + ,1 + ,2 + ,5 + ,3 + ,1 + ,1 + ,1 + ,3 + ,5 + ,3 + ,2 + ,3 + ,1 + ,3 + ,4 + ,3 + ,2 + ,2 + ,1 + ,3 + ,4 + ,3 + ,1 + ,1 + ,1 + ,3 + ,4 + ,1 + ,1 + ,1 + ,2 + ,3 + ,5 + ,3 + ,1 + ,3 + ,1 + ,2 + ,4 + ,4) + ,dim=c(6 + ,160) + ,dimnames=list(c('Gender' + ,'Weight' + ,'Drugs' + ,'Sports' + ,'Vegetables' + ,'Alcohol ') + ,1:160)) > y <- array(NA,dim=c(6,160),dimnames=list(c('Gender','Weight','Drugs','Sports','Vegetables','Alcohol '),1:160)) > 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 Attaching package: 'zoo' The following object(s) are masked from package:base : 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 Gender Weight Drugs Sports Vegetables Alcohol\r\r 1 1 3 1 3 4 2 2 1 1 1 3 3 3 3 1 2 2 3 3 4 4 2 4 1 3 5 3 5 2 1 1 3 4 2 6 2 4 1 3 1 2 7 3 1 3 5 3 1 8 1 1 1 5 2 1 9 1 1 3 2 3 1 10 2 4 2 2 5 2 11 3 5 3 1 3 1 12 3 3 2 1 1 1 13 2 4 4 1 2 1 14 3 4 1 1 2 1 15 3 4 2 2 5 2 16 3 4 4 2 2 1 17 3 5 2 1 2 1 18 3 3 3 2 2 1 19 3 5 3 1 2 1 20 3 3 3 2 3 1 21 3 4 1 1 3 1 22 3 4 3 2 3 2 23 3 4 3 2 1 1 24 3 3 2 1 1 2 25 3 5 2 2 4 1 26 2 4 2 1 1 4 27 3 5 2 1 3 1 28 3 2 4 1 2 1 29 2 5 3 2 1 1 30 3 4 1 2 2 1 31 3 5 2 2 1 1 32 3 4 1 1 2 1 33 3 5 3 2 1 1 34 2 3 2 1 1 1 35 3 3 1 1 1 1 36 3 4 3 2 1 1 37 3 4 2 1 3 1 38 3 5 3 2 3 1 39 1 5 1 1 1 1 40 3 3 3 2 3 1 41 2 5 3 1 1 1 42 3 5 2 2 2 1 43 3 4 3 1 3 1 44 3 5 3 1 2 1 45 2 3 3 2 1 3 46 2 4 3 1 1 2 47 3 5 3 1 1 1 48 3 3 3 1 1 1 49 3 5 2 2 1 1 50 3 4 2 1 3 2 51 2 3 3 2 2 1 52 2 5 1 2 2 1 53 3 4 3 1 2 1 54 2 5 3 1 4 1 55 3 3 1 1 3 1 56 3 5 1 2 3 1 57 3 4 1 1 3 1 58 2 5 4 2 1 1 59 3 4 3 2 3 1 60 3 5 1 1 1 1 61 3 5 2 1 1 2 62 3 5 4 2 1 1 63 3 4 3 1 1 1 64 2 5 3 2 3 1 65 3 4 2 2 3 1 66 3 5 3 1 1 1 67 2 4 3 1 1 1 68 3 3 3 1 2 1 69 3 4 2 1 2 2 70 3 3 3 2 1 1 71 2 5 2 1 4 1 72 2 4 3 2 3 1 73 3 4 1 1 2 1 74 2 4 3 1 1 1 75 3 4 2 1 1 1 76 3 4 2 2 3 1 77 3 3 4 2 2 1 78 3 4 2 1 1 1 79 3 3 3 1 3 1 80 3 4 2 1 3 1 81 3 5 4 1 1 1 82 3 4 2 1 2 1 83 3 3 3 1 1 2 84 2 4 3 2 2 1 85 3 4 1 1 2 1 86 3 4 2 1 2 1 87 3 5 2 1 1 1 88 3 4 3 2 2 1 89 3 5 1 1 1 3 90 2 4 2 1 1 1 91 3 2 3 2 3 1 92 3 5 3 2 2 1 93 3 5 3 2 3 2 94 3 5 2 1 3 1 95 3 4 3 1 4 1 96 1 5 4 2 1 1 97 3 5 3 1 4 1 98 1 4 3 1 1 1 99 3 4 3 1 1 1 100 3 5 2 2 3 1 101 3 4 3 1 3 1 102 3 5 3 1 3 2 103 2 5 3 1 4 3 104 3 4 3 2 2 1 105 3 4 3 2 1 1 106 2 5 2 1 2 1 107 3 4 2 1 1 1 108 3 4 4 1 2 1 109 3 2 2 1 3 1 110 2 3 2 5 1 3 111 4 1 1 2 1 2 112 4 3 2 1 1 2 113 2 3 1 1 1 3 114 5 2 2 2 1 3 115 4 1 1 3 1 3 116 4 3 1 1 1 3 117 4 2 1 3 3 2 118 4 2 1 1 1 3 119 5 3 1 1 1 2 120 3 3 1 1 1 3 121 1 1 1 1 1 3 122 5 2 1 3 3 3 123 3 3 1 3 2 3 124 5 1 1 1 1 3 125 3 3 2 3 1 3 126 4 2 1 2 1 1 127 4 4 2 3 1 3 128 4 3 2 2 1 2 129 4 3 2 2 2 3 130 4 2 2 5 3 3 131 5 2 2 4 1 3 132 4 3 1 1 1 2 133 5 2 1 1 1 3 134 3 2 1 3 3 2 135 4 4 2 3 1 3 136 4 2 1 2 2 2 137 4 4 1 1 1 3 138 4 3 1 1 1 2 139 4 2 2 4 1 3 140 5 4 1 3 1 3 141 5 1 1 3 1 3 142 5 3 2 3 1 3 143 5 1 2 3 1 3 144 5 2 1 3 1 3 145 4 4 1 2 3 3 146 4 3 1 1 2 3 147 4 2 2 2 1 3 148 4 1 2 1 1 3 149 5 2 2 2 1 3 150 4 3 1 1 1 2 151 5 2 1 4 1 3 152 4 3 1 1 2 2 153 5 3 1 1 1 2 154 5 3 1 1 1 3 155 5 3 2 3 1 3 156 4 3 2 2 1 3 157 4 3 1 1 1 3 158 4 1 1 1 2 3 159 5 3 1 3 1 2 160 4 4 1 3 1 3 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Weight Drugs Sports Vegetables 3.78656 -0.10205 -0.17466 -0.02077 -0.20747 `Alcohol\r\r` 0.27079 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -3.0940 -0.2891 0.2043 0.4389 1.4645 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 3.78656 0.44159 8.575 9.87e-15 *** Weight -0.10205 0.06926 -1.473 0.14271 Drugs -0.17466 0.08556 -2.041 0.04292 * Sports -0.02077 0.08179 -0.254 0.79992 Vegetables -0.20747 0.06821 -3.042 0.00277 ** `Alcohol\r\r` 0.27079 0.09870 2.743 0.00680 ** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.8616 on 154 degrees of freedom Multiple R-squared: 0.2633, Adjusted R-squared: 0.2394 F-statistic: 11.01 on 5 and 154 DF, p-value: 4.475e-09 > 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,] 8.168729e-01 3.662542e-01 0.1831270837 [2,] 7.040719e-01 5.918562e-01 0.2959281153 [3,] 6.521301e-01 6.957399e-01 0.3478699312 [4,] 7.515858e-01 4.968283e-01 0.2484141667 [5,] 7.518959e-01 4.962082e-01 0.2481041009 [6,] 7.177982e-01 5.644036e-01 0.2822018103 [7,] 7.109814e-01 5.780371e-01 0.2890185614 [8,] 6.393890e-01 7.212221e-01 0.3606110390 [9,] 5.530653e-01 8.938694e-01 0.4469346907 [10,] 5.115302e-01 9.769396e-01 0.4884697895 [11,] 4.306619e-01 8.613238e-01 0.5693381202 [12,] 3.823221e-01 7.646443e-01 0.6176778632 [13,] 3.218816e-01 6.437632e-01 0.6781184083 [14,] 2.929849e-01 5.859699e-01 0.7070150610 [15,] 2.337483e-01 4.674967e-01 0.7662516682 [16,] 2.553166e-01 5.106332e-01 0.7446834015 [17,] 2.003299e-01 4.006598e-01 0.7996700827 [18,] 1.814145e-01 3.628290e-01 0.8185855247 [19,] 1.400154e-01 2.800308e-01 0.8599846183 [20,] 1.158855e-01 2.317709e-01 0.8841145488 [21,] 1.616567e-01 3.233134e-01 0.8383432897 [22,] 1.353030e-01 2.706059e-01 0.8646970251 [23,] 1.036511e-01 2.073021e-01 0.8963489258 [24,] 7.876020e-02 1.575204e-01 0.9212398022 [25,] 5.856028e-02 1.171206e-01 0.9414397218 [26,] 6.356506e-02 1.271301e-01 0.9364349395 [27,] 5.258826e-02 1.051765e-01 0.9474117436 [28,] 3.935670e-02 7.871340e-02 0.9606432978 [29,] 2.830197e-02 5.660394e-02 0.9716980300 [30,] 2.041349e-02 4.082697e-02 0.9795865138 [31,] 1.621569e-01 3.243138e-01 0.8378430820 [32,] 1.348773e-01 2.697546e-01 0.8651226965 [33,] 1.607756e-01 3.215513e-01 0.8392243686 [34,] 1.324936e-01 2.649872e-01 0.8675064224 [35,] 1.071437e-01 2.142875e-01 0.8928562721 [36,] 8.672651e-02 1.734530e-01 0.9132734916 [37,] 8.835278e-02 1.767056e-01 0.9116472200 [38,] 8.604094e-02 1.720819e-01 0.9139590604 [39,] 6.854730e-02 1.370946e-01 0.9314527035 [40,] 5.551038e-02 1.110208e-01 0.9444896193 [41,] 4.431286e-02 8.862571e-02 0.9556871436 [42,] 3.812155e-02 7.624311e-02 0.9618784456 [43,] 3.972605e-02 7.945211e-02 0.9602739466 [44,] 4.291538e-02 8.583075e-02 0.9570846238 [45,] 3.314457e-02 6.628914e-02 0.9668554275 [46,] 4.672942e-02 9.345885e-02 0.9532705766 [47,] 3.951124e-02 7.902249e-02 0.9604887571 [48,] 3.161008e-02 6.322017e-02 0.9683899152 [49,] 2.458489e-02 4.916979e-02 0.9754151058 [50,] 2.585387e-02 5.170774e-02 0.9741461302 [51,] 2.028861e-02 4.057721e-02 0.9797113926 [52,] 1.542581e-02 3.085163e-02 0.9845741860 [53,] 1.286342e-02 2.572684e-02 0.9871365781 [54,] 1.023075e-02 2.046150e-02 0.9897692520 [55,] 7.589352e-03 1.517870e-02 0.9924106484 [56,] 8.279392e-03 1.655878e-02 0.9917206077 [57,] 6.323258e-03 1.264652e-02 0.9936767424 [58,] 4.700425e-03 9.400851e-03 0.9952995746 [59,] 5.379375e-03 1.075875e-02 0.9946206255 [60,] 3.947627e-03 7.895255e-03 0.9960523726 [61,] 3.242394e-03 6.484788e-03 0.9967576060 [62,] 2.574849e-03 5.149697e-03 0.9974251513 [63,] 3.285627e-03 6.571255e-03 0.9967143726 [64,] 3.337768e-03 6.675537e-03 0.9966622315 [65,] 2.438592e-03 4.877185e-03 0.9975614076 [66,] 2.812229e-03 5.624459e-03 0.9971877706 [67,] 2.004905e-03 4.009809e-03 0.9979950953 [68,] 1.491224e-03 2.982448e-03 0.9985087759 [69,] 1.137251e-03 2.274502e-03 0.9988627491 [70,] 7.865712e-04 1.573142e-03 0.9992134288 [71,] 5.422515e-04 1.084503e-03 0.9994577485 [72,] 3.625497e-04 7.250994e-04 0.9996374503 [73,] 2.802744e-04 5.605489e-04 0.9997197256 [74,] 1.844159e-04 3.688318e-04 0.9998155841 [75,] 1.433767e-04 2.867535e-04 0.9998566233 [76,] 1.487440e-04 2.974880e-04 0.9998512560 [77,] 1.005737e-04 2.011474e-04 0.9998994263 [78,] 6.412775e-05 1.282555e-04 0.9999358723 [79,] 4.014554e-05 8.029108e-05 0.9999598545 [80,] 2.721197e-05 5.442393e-05 0.9999727880 [81,] 2.861788e-05 5.723575e-05 0.9999713821 [82,] 4.510705e-05 9.021410e-05 0.9999548929 [83,] 3.246126e-05 6.492253e-05 0.9999675387 [84,] 2.165433e-05 4.330866e-05 0.9999783457 [85,] 1.600081e-05 3.200162e-05 0.9999839992 [86,] 9.659549e-06 1.931910e-05 0.9999903405 [87,] 6.384512e-06 1.276902e-05 0.9999936155 [88,] 6.652213e-05 1.330443e-04 0.9999334779 [89,] 5.039578e-05 1.007916e-04 0.9999496042 [90,] 8.994367e-04 1.798873e-03 0.9991005633 [91,] 6.259942e-04 1.251988e-03 0.9993740058 [92,] 4.302893e-04 8.605786e-04 0.9995697107 [93,] 2.934871e-04 5.869741e-04 0.9997065129 [94,] 2.095811e-04 4.191623e-04 0.9997904189 [95,] 1.695853e-04 3.391707e-04 0.9998304147 [96,] 1.162465e-04 2.324929e-04 0.9998837535 [97,] 8.426852e-05 1.685370e-04 0.9999157315 [98,] 1.484984e-04 2.969968e-04 0.9998515016 [99,] 1.209106e-04 2.418212e-04 0.9998790894 [100,] 8.006869e-05 1.601374e-04 0.9999199313 [101,] 6.329445e-05 1.265889e-04 0.9999367056 [102,] 1.064140e-03 2.128279e-03 0.9989358604 [103,] 2.374888e-03 4.749777e-03 0.9976251117 [104,] 3.147094e-03 6.294188e-03 0.9968529062 [105,] 1.354430e-02 2.708860e-02 0.9864557022 [106,] 6.219397e-02 1.243879e-01 0.9378060267 [107,] 8.164209e-02 1.632842e-01 0.9183579120 [108,] 7.975010e-02 1.595002e-01 0.9202499035 [109,] 8.651860e-02 1.730372e-01 0.9134813953 [110,] 7.791918e-02 1.558384e-01 0.9220808248 [111,] 1.217152e-01 2.434304e-01 0.8782848036 [112,] 1.402607e-01 2.805215e-01 0.8597392610 [113,] 9.668933e-01 6.621344e-02 0.0331067201 [114,] 9.906081e-01 1.878376e-02 0.0093918803 [115,] 9.969541e-01 6.091735e-03 0.0030458674 [116,] 9.968506e-01 6.298812e-03 0.0031494061 [117,] 9.996778e-01 6.443895e-04 0.0003221947 [118,] 9.995077e-01 9.845221e-04 0.0004922610 [119,] 9.994515e-01 1.096988e-03 0.0005484941 [120,] 9.991486e-01 1.702834e-03 0.0008514170 [121,] 9.987190e-01 2.562061e-03 0.0012810303 [122,] 9.982638e-01 3.472420e-03 0.0017362101 [123,] 9.982024e-01 3.595197e-03 0.0017975987 [124,] 9.973748e-01 5.250377e-03 0.0026251886 [125,] 9.969938e-01 6.012488e-03 0.0030062439 [126,] 9.980992e-01 3.801693e-03 0.0019008467 [127,] 9.975986e-01 4.802818e-03 0.0024014088 [128,] 9.963420e-01 7.316096e-03 0.0036580482 [129,] 9.941833e-01 1.163336e-02 0.0058166812 [130,] 9.922663e-01 1.546733e-02 0.0077336637 [131,] 9.966602e-01 6.679536e-03 0.0033397678 [132,] 9.952197e-01 9.560653e-03 0.0047803267 [133,] 9.915826e-01 1.683488e-02 0.0084174404 [134,] 9.883942e-01 2.321167e-02 0.0116058354 [135,] 9.810956e-01 3.780871e-02 0.0189043563 [136,] 9.691486e-01 6.170280e-02 0.0308514019 [137,] 9.491990e-01 1.016020e-01 0.0508010002 [138,] 9.146510e-01 1.706979e-01 0.0853489639 [139,] 8.862601e-01 2.274799e-01 0.1137399497 [140,] 8.903859e-01 2.192282e-01 0.1096140774 [141,] 8.196794e-01 3.606412e-01 0.1803205852 [142,] 8.455365e-01 3.089270e-01 0.1544634762 [143,] 7.115095e-01 5.769810e-01 0.2884904754 > postscript(file="/var/www/html/rcomp/tmp/1z78h1290558334.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2z78h1290558334.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/html/rcomp/tmp/3z78h1290558334.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4k9sx1290558335.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5k9sx1290558335.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 = 160 Frequency = 1 1 2 3 4 5 6 -1.955167675 -2.637522611 -2.631610493 -0.916444287 -1.159258297 -1.475535952 7 8 9 10 11 12 0.294914318 -2.261876730 -1.767381941 -0.491756662 0.620033883 -0.173659057 13 14 15 16 17 18 -0.514822697 -0.038802477 0.508243338 0.505942723 0.237902761 0.229237485 19 20 21 22 23 24 0.412562687 0.436708681 0.168668719 0.267960873 0.123811600 -0.444452175 25 26 27 28 29 30 0.673610572 -1.883993102 0.445373957 0.281086681 -0.774143089 -0.018037057 31 32 33 34 35 36 0.051196985 -0.038802477 0.225856911 -1.173659057 -0.348318983 0.123811600 37 38 39 40 41 42 0.343328646 0.640799303 -2.144228361 0.436708681 -0.794908509 0.258668181 43 44 45 46 47 48 0.517988572 0.412562687 -1.519819948 -1.167746938 0.205091491 0.001000870 49 50 51 52 53 54 0.051196985 0.072535527 -0.770762515 -0.915991746 0.310517376 -0.172494921 55 56 57 58 59 60 0.066623408 0.291479450 0.168668719 -0.599483162 0.538753992 -0.144228361 61 62 63 64 65 66 -0.240361554 0.400516838 0.103046181 -0.359200697 0.364094065 0.205091491 67 68 69 70 71 72 -0.896953819 0.208472065 -0.134935669 0.021766289 -0.347154848 -0.461246008 73 74 75 76 77 78 -0.038802477 -0.896953819 -0.071613746 0.364094065 0.403897412 -0.071613746 79 80 81 82 83 84 0.415943261 0.343328646 0.379751418 0.135857450 -0.269792249 -0.668717204 85 86 87 88 89 90 -0.038802477 0.135857450 0.030431565 0.331282796 -0.685814599 -1.071613746 91 92 93 94 95 96 0.334663370 0.433328107 0.370006184 0.445373957 0.725459768 -1.599483162 97 98 99 100 101 102 0.827505079 -1.896953819 0.103046181 0.466139376 0.517988572 0.349240764 103 104 105 106 107 108 -0.714081159 0.331282796 0.123811600 -0.762097239 -0.071613746 0.485177303 109 110 111 112 113 114 0.139238024 -1.632183615 0.197562696 0.555547825 -1.889905221 1.203474815 115 116 117 118 119 120 -0.052465003 0.110094779 0.735315818 0.008049468 1.380887898 -0.889905221 121 122 123 124 125 126 -3.093995842 1.464522699 -0.640903185 0.906004158 -0.673714455 0.570401126 127 128 129 130 131 132 0.428330856 0.576313244 0.512991321 0.680713465 1.245005654 0.380887898 133 134 135 136 137 138 1.008049468 -0.264684182 0.428330856 0.507079203 0.212140090 0.380887898 139 140 141 142 143 144 0.245005654 1.253670930 0.947534997 1.326285545 1.122194923 1.049580308 145 146 147 148 149 150 0.647847901 0.317565975 0.203474815 0.080664084 1.203474815 0.380887898 151 152 153 154 155 156 1.070345728 0.588359094 1.380887898 1.110094779 1.326285545 0.305520126 157 158 159 160 0.110094779 0.113475353 1.422418738 0.253670930 > postscript(file="/var/www/html/rcomp/tmp/6k9sx1290558335.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 = 160 Frequency = 1 lag(myerror, k = 1) myerror 0 -1.955167675 NA 1 -2.637522611 -1.955167675 2 -2.631610493 -2.637522611 3 -0.916444287 -2.631610493 4 -1.159258297 -0.916444287 5 -1.475535952 -1.159258297 6 0.294914318 -1.475535952 7 -2.261876730 0.294914318 8 -1.767381941 -2.261876730 9 -0.491756662 -1.767381941 10 0.620033883 -0.491756662 11 -0.173659057 0.620033883 12 -0.514822697 -0.173659057 13 -0.038802477 -0.514822697 14 0.508243338 -0.038802477 15 0.505942723 0.508243338 16 0.237902761 0.505942723 17 0.229237485 0.237902761 18 0.412562687 0.229237485 19 0.436708681 0.412562687 20 0.168668719 0.436708681 21 0.267960873 0.168668719 22 0.123811600 0.267960873 23 -0.444452175 0.123811600 24 0.673610572 -0.444452175 25 -1.883993102 0.673610572 26 0.445373957 -1.883993102 27 0.281086681 0.445373957 28 -0.774143089 0.281086681 29 -0.018037057 -0.774143089 30 0.051196985 -0.018037057 31 -0.038802477 0.051196985 32 0.225856911 -0.038802477 33 -1.173659057 0.225856911 34 -0.348318983 -1.173659057 35 0.123811600 -0.348318983 36 0.343328646 0.123811600 37 0.640799303 0.343328646 38 -2.144228361 0.640799303 39 0.436708681 -2.144228361 40 -0.794908509 0.436708681 41 0.258668181 -0.794908509 42 0.517988572 0.258668181 43 0.412562687 0.517988572 44 -1.519819948 0.412562687 45 -1.167746938 -1.519819948 46 0.205091491 -1.167746938 47 0.001000870 0.205091491 48 0.051196985 0.001000870 49 0.072535527 0.051196985 50 -0.770762515 0.072535527 51 -0.915991746 -0.770762515 52 0.310517376 -0.915991746 53 -0.172494921 0.310517376 54 0.066623408 -0.172494921 55 0.291479450 0.066623408 56 0.168668719 0.291479450 57 -0.599483162 0.168668719 58 0.538753992 -0.599483162 59 -0.144228361 0.538753992 60 -0.240361554 -0.144228361 61 0.400516838 -0.240361554 62 0.103046181 0.400516838 63 -0.359200697 0.103046181 64 0.364094065 -0.359200697 65 0.205091491 0.364094065 66 -0.896953819 0.205091491 67 0.208472065 -0.896953819 68 -0.134935669 0.208472065 69 0.021766289 -0.134935669 70 -0.347154848 0.021766289 71 -0.461246008 -0.347154848 72 -0.038802477 -0.461246008 73 -0.896953819 -0.038802477 74 -0.071613746 -0.896953819 75 0.364094065 -0.071613746 76 0.403897412 0.364094065 77 -0.071613746 0.403897412 78 0.415943261 -0.071613746 79 0.343328646 0.415943261 80 0.379751418 0.343328646 81 0.135857450 0.379751418 82 -0.269792249 0.135857450 83 -0.668717204 -0.269792249 84 -0.038802477 -0.668717204 85 0.135857450 -0.038802477 86 0.030431565 0.135857450 87 0.331282796 0.030431565 88 -0.685814599 0.331282796 89 -1.071613746 -0.685814599 90 0.334663370 -1.071613746 91 0.433328107 0.334663370 92 0.370006184 0.433328107 93 0.445373957 0.370006184 94 0.725459768 0.445373957 95 -1.599483162 0.725459768 96 0.827505079 -1.599483162 97 -1.896953819 0.827505079 98 0.103046181 -1.896953819 99 0.466139376 0.103046181 100 0.517988572 0.466139376 101 0.349240764 0.517988572 102 -0.714081159 0.349240764 103 0.331282796 -0.714081159 104 0.123811600 0.331282796 105 -0.762097239 0.123811600 106 -0.071613746 -0.762097239 107 0.485177303 -0.071613746 108 0.139238024 0.485177303 109 -1.632183615 0.139238024 110 0.197562696 -1.632183615 111 0.555547825 0.197562696 112 -1.889905221 0.555547825 113 1.203474815 -1.889905221 114 -0.052465003 1.203474815 115 0.110094779 -0.052465003 116 0.735315818 0.110094779 117 0.008049468 0.735315818 118 1.380887898 0.008049468 119 -0.889905221 1.380887898 120 -3.093995842 -0.889905221 121 1.464522699 -3.093995842 122 -0.640903185 1.464522699 123 0.906004158 -0.640903185 124 -0.673714455 0.906004158 125 0.570401126 -0.673714455 126 0.428330856 0.570401126 127 0.576313244 0.428330856 128 0.512991321 0.576313244 129 0.680713465 0.512991321 130 1.245005654 0.680713465 131 0.380887898 1.245005654 132 1.008049468 0.380887898 133 -0.264684182 1.008049468 134 0.428330856 -0.264684182 135 0.507079203 0.428330856 136 0.212140090 0.507079203 137 0.380887898 0.212140090 138 0.245005654 0.380887898 139 1.253670930 0.245005654 140 0.947534997 1.253670930 141 1.326285545 0.947534997 142 1.122194923 1.326285545 143 1.049580308 1.122194923 144 0.647847901 1.049580308 145 0.317565975 0.647847901 146 0.203474815 0.317565975 147 0.080664084 0.203474815 148 1.203474815 0.080664084 149 0.380887898 1.203474815 150 1.070345728 0.380887898 151 0.588359094 1.070345728 152 1.380887898 0.588359094 153 1.110094779 1.380887898 154 1.326285545 1.110094779 155 0.305520126 1.326285545 156 0.110094779 0.305520126 157 0.113475353 0.110094779 158 1.422418738 0.113475353 159 0.253670930 1.422418738 160 NA 0.253670930 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -2.637522611 -1.955167675 [2,] -2.631610493 -2.637522611 [3,] -0.916444287 -2.631610493 [4,] -1.159258297 -0.916444287 [5,] -1.475535952 -1.159258297 [6,] 0.294914318 -1.475535952 [7,] -2.261876730 0.294914318 [8,] -1.767381941 -2.261876730 [9,] -0.491756662 -1.767381941 [10,] 0.620033883 -0.491756662 [11,] -0.173659057 0.620033883 [12,] -0.514822697 -0.173659057 [13,] -0.038802477 -0.514822697 [14,] 0.508243338 -0.038802477 [15,] 0.505942723 0.508243338 [16,] 0.237902761 0.505942723 [17,] 0.229237485 0.237902761 [18,] 0.412562687 0.229237485 [19,] 0.436708681 0.412562687 [20,] 0.168668719 0.436708681 [21,] 0.267960873 0.168668719 [22,] 0.123811600 0.267960873 [23,] -0.444452175 0.123811600 [24,] 0.673610572 -0.444452175 [25,] -1.883993102 0.673610572 [26,] 0.445373957 -1.883993102 [27,] 0.281086681 0.445373957 [28,] -0.774143089 0.281086681 [29,] -0.018037057 -0.774143089 [30,] 0.051196985 -0.018037057 [31,] -0.038802477 0.051196985 [32,] 0.225856911 -0.038802477 [33,] -1.173659057 0.225856911 [34,] -0.348318983 -1.173659057 [35,] 0.123811600 -0.348318983 [36,] 0.343328646 0.123811600 [37,] 0.640799303 0.343328646 [38,] -2.144228361 0.640799303 [39,] 0.436708681 -2.144228361 [40,] -0.794908509 0.436708681 [41,] 0.258668181 -0.794908509 [42,] 0.517988572 0.258668181 [43,] 0.412562687 0.517988572 [44,] -1.519819948 0.412562687 [45,] -1.167746938 -1.519819948 [46,] 0.205091491 -1.167746938 [47,] 0.001000870 0.205091491 [48,] 0.051196985 0.001000870 [49,] 0.072535527 0.051196985 [50,] -0.770762515 0.072535527 [51,] -0.915991746 -0.770762515 [52,] 0.310517376 -0.915991746 [53,] -0.172494921 0.310517376 [54,] 0.066623408 -0.172494921 [55,] 0.291479450 0.066623408 [56,] 0.168668719 0.291479450 [57,] -0.599483162 0.168668719 [58,] 0.538753992 -0.599483162 [59,] -0.144228361 0.538753992 [60,] -0.240361554 -0.144228361 [61,] 0.400516838 -0.240361554 [62,] 0.103046181 0.400516838 [63,] -0.359200697 0.103046181 [64,] 0.364094065 -0.359200697 [65,] 0.205091491 0.364094065 [66,] -0.896953819 0.205091491 [67,] 0.208472065 -0.896953819 [68,] -0.134935669 0.208472065 [69,] 0.021766289 -0.134935669 [70,] -0.347154848 0.021766289 [71,] -0.461246008 -0.347154848 [72,] -0.038802477 -0.461246008 [73,] -0.896953819 -0.038802477 [74,] -0.071613746 -0.896953819 [75,] 0.364094065 -0.071613746 [76,] 0.403897412 0.364094065 [77,] -0.071613746 0.403897412 [78,] 0.415943261 -0.071613746 [79,] 0.343328646 0.415943261 [80,] 0.379751418 0.343328646 [81,] 0.135857450 0.379751418 [82,] -0.269792249 0.135857450 [83,] -0.668717204 -0.269792249 [84,] -0.038802477 -0.668717204 [85,] 0.135857450 -0.038802477 [86,] 0.030431565 0.135857450 [87,] 0.331282796 0.030431565 [88,] -0.685814599 0.331282796 [89,] -1.071613746 -0.685814599 [90,] 0.334663370 -1.071613746 [91,] 0.433328107 0.334663370 [92,] 0.370006184 0.433328107 [93,] 0.445373957 0.370006184 [94,] 0.725459768 0.445373957 [95,] -1.599483162 0.725459768 [96,] 0.827505079 -1.599483162 [97,] -1.896953819 0.827505079 [98,] 0.103046181 -1.896953819 [99,] 0.466139376 0.103046181 [100,] 0.517988572 0.466139376 [101,] 0.349240764 0.517988572 [102,] -0.714081159 0.349240764 [103,] 0.331282796 -0.714081159 [104,] 0.123811600 0.331282796 [105,] -0.762097239 0.123811600 [106,] -0.071613746 -0.762097239 [107,] 0.485177303 -0.071613746 [108,] 0.139238024 0.485177303 [109,] -1.632183615 0.139238024 [110,] 0.197562696 -1.632183615 [111,] 0.555547825 0.197562696 [112,] -1.889905221 0.555547825 [113,] 1.203474815 -1.889905221 [114,] -0.052465003 1.203474815 [115,] 0.110094779 -0.052465003 [116,] 0.735315818 0.110094779 [117,] 0.008049468 0.735315818 [118,] 1.380887898 0.008049468 [119,] -0.889905221 1.380887898 [120,] -3.093995842 -0.889905221 [121,] 1.464522699 -3.093995842 [122,] -0.640903185 1.464522699 [123,] 0.906004158 -0.640903185 [124,] -0.673714455 0.906004158 [125,] 0.570401126 -0.673714455 [126,] 0.428330856 0.570401126 [127,] 0.576313244 0.428330856 [128,] 0.512991321 0.576313244 [129,] 0.680713465 0.512991321 [130,] 1.245005654 0.680713465 [131,] 0.380887898 1.245005654 [132,] 1.008049468 0.380887898 [133,] -0.264684182 1.008049468 [134,] 0.428330856 -0.264684182 [135,] 0.507079203 0.428330856 [136,] 0.212140090 0.507079203 [137,] 0.380887898 0.212140090 [138,] 0.245005654 0.380887898 [139,] 1.253670930 0.245005654 [140,] 0.947534997 1.253670930 [141,] 1.326285545 0.947534997 [142,] 1.122194923 1.326285545 [143,] 1.049580308 1.122194923 [144,] 0.647847901 1.049580308 [145,] 0.317565975 0.647847901 [146,] 0.203474815 0.317565975 [147,] 0.080664084 0.203474815 [148,] 1.203474815 0.080664084 [149,] 0.380887898 1.203474815 [150,] 1.070345728 0.380887898 [151,] 0.588359094 1.070345728 [152,] 1.380887898 0.588359094 [153,] 1.110094779 1.380887898 [154,] 1.326285545 1.110094779 [155,] 0.305520126 1.326285545 [156,] 0.110094779 0.305520126 [157,] 0.113475353 0.110094779 [158,] 1.422418738 0.113475353 [159,] 0.253670930 1.422418738 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -2.637522611 -1.955167675 2 -2.631610493 -2.637522611 3 -0.916444287 -2.631610493 4 -1.159258297 -0.916444287 5 -1.475535952 -1.159258297 6 0.294914318 -1.475535952 7 -2.261876730 0.294914318 8 -1.767381941 -2.261876730 9 -0.491756662 -1.767381941 10 0.620033883 -0.491756662 11 -0.173659057 0.620033883 12 -0.514822697 -0.173659057 13 -0.038802477 -0.514822697 14 0.508243338 -0.038802477 15 0.505942723 0.508243338 16 0.237902761 0.505942723 17 0.229237485 0.237902761 18 0.412562687 0.229237485 19 0.436708681 0.412562687 20 0.168668719 0.436708681 21 0.267960873 0.168668719 22 0.123811600 0.267960873 23 -0.444452175 0.123811600 24 0.673610572 -0.444452175 25 -1.883993102 0.673610572 26 0.445373957 -1.883993102 27 0.281086681 0.445373957 28 -0.774143089 0.281086681 29 -0.018037057 -0.774143089 30 0.051196985 -0.018037057 31 -0.038802477 0.051196985 32 0.225856911 -0.038802477 33 -1.173659057 0.225856911 34 -0.348318983 -1.173659057 35 0.123811600 -0.348318983 36 0.343328646 0.123811600 37 0.640799303 0.343328646 38 -2.144228361 0.640799303 39 0.436708681 -2.144228361 40 -0.794908509 0.436708681 41 0.258668181 -0.794908509 42 0.517988572 0.258668181 43 0.412562687 0.517988572 44 -1.519819948 0.412562687 45 -1.167746938 -1.519819948 46 0.205091491 -1.167746938 47 0.001000870 0.205091491 48 0.051196985 0.001000870 49 0.072535527 0.051196985 50 -0.770762515 0.072535527 51 -0.915991746 -0.770762515 52 0.310517376 -0.915991746 53 -0.172494921 0.310517376 54 0.066623408 -0.172494921 55 0.291479450 0.066623408 56 0.168668719 0.291479450 57 -0.599483162 0.168668719 58 0.538753992 -0.599483162 59 -0.144228361 0.538753992 60 -0.240361554 -0.144228361 61 0.400516838 -0.240361554 62 0.103046181 0.400516838 63 -0.359200697 0.103046181 64 0.364094065 -0.359200697 65 0.205091491 0.364094065 66 -0.896953819 0.205091491 67 0.208472065 -0.896953819 68 -0.134935669 0.208472065 69 0.021766289 -0.134935669 70 -0.347154848 0.021766289 71 -0.461246008 -0.347154848 72 -0.038802477 -0.461246008 73 -0.896953819 -0.038802477 74 -0.071613746 -0.896953819 75 0.364094065 -0.071613746 76 0.403897412 0.364094065 77 -0.071613746 0.403897412 78 0.415943261 -0.071613746 79 0.343328646 0.415943261 80 0.379751418 0.343328646 81 0.135857450 0.379751418 82 -0.269792249 0.135857450 83 -0.668717204 -0.269792249 84 -0.038802477 -0.668717204 85 0.135857450 -0.038802477 86 0.030431565 0.135857450 87 0.331282796 0.030431565 88 -0.685814599 0.331282796 89 -1.071613746 -0.685814599 90 0.334663370 -1.071613746 91 0.433328107 0.334663370 92 0.370006184 0.433328107 93 0.445373957 0.370006184 94 0.725459768 0.445373957 95 -1.599483162 0.725459768 96 0.827505079 -1.599483162 97 -1.896953819 0.827505079 98 0.103046181 -1.896953819 99 0.466139376 0.103046181 100 0.517988572 0.466139376 101 0.349240764 0.517988572 102 -0.714081159 0.349240764 103 0.331282796 -0.714081159 104 0.123811600 0.331282796 105 -0.762097239 0.123811600 106 -0.071613746 -0.762097239 107 0.485177303 -0.071613746 108 0.139238024 0.485177303 109 -1.632183615 0.139238024 110 0.197562696 -1.632183615 111 0.555547825 0.197562696 112 -1.889905221 0.555547825 113 1.203474815 -1.889905221 114 -0.052465003 1.203474815 115 0.110094779 -0.052465003 116 0.735315818 0.110094779 117 0.008049468 0.735315818 118 1.380887898 0.008049468 119 -0.889905221 1.380887898 120 -3.093995842 -0.889905221 121 1.464522699 -3.093995842 122 -0.640903185 1.464522699 123 0.906004158 -0.640903185 124 -0.673714455 0.906004158 125 0.570401126 -0.673714455 126 0.428330856 0.570401126 127 0.576313244 0.428330856 128 0.512991321 0.576313244 129 0.680713465 0.512991321 130 1.245005654 0.680713465 131 0.380887898 1.245005654 132 1.008049468 0.380887898 133 -0.264684182 1.008049468 134 0.428330856 -0.264684182 135 0.507079203 0.428330856 136 0.212140090 0.507079203 137 0.380887898 0.212140090 138 0.245005654 0.380887898 139 1.253670930 0.245005654 140 0.947534997 1.253670930 141 1.326285545 0.947534997 142 1.122194923 1.326285545 143 1.049580308 1.122194923 144 0.647847901 1.049580308 145 0.317565975 0.647847901 146 0.203474815 0.317565975 147 0.080664084 0.203474815 148 1.203474815 0.080664084 149 0.380887898 1.203474815 150 1.070345728 0.380887898 151 0.588359094 1.070345728 152 1.380887898 0.588359094 153 1.110094779 1.380887898 154 1.326285545 1.110094779 155 0.305520126 1.326285545 156 0.110094779 0.305520126 157 0.113475353 0.110094779 158 1.422418738 0.113475353 159 0.253670930 1.422418738 > 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/html/rcomp/tmp/7visi1290558335.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8n9r31290558335.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9n9r31290558335.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10n9r31290558335.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/www/html/rcomp/tmp/11jj6b1290558335.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/www/html/rcomp/tmp/12uaof1290558335.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/www/html/rcomp/tmp/131t3q1290558335.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/www/html/rcomp/tmp/144uje1290558335.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/www/html/rcomp/tmp/15qu021290558335.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/www/html/rcomp/tmp/16bvgq1290558335.tab") + } > > try(system("convert tmp/1z78h1290558334.ps tmp/1z78h1290558334.png",intern=TRUE)) character(0) > try(system("convert tmp/2z78h1290558334.ps tmp/2z78h1290558334.png",intern=TRUE)) character(0) > try(system("convert tmp/3z78h1290558334.ps tmp/3z78h1290558334.png",intern=TRUE)) character(0) > try(system("convert tmp/4k9sx1290558335.ps tmp/4k9sx1290558335.png",intern=TRUE)) character(0) > try(system("convert tmp/5k9sx1290558335.ps tmp/5k9sx1290558335.png",intern=TRUE)) character(0) > try(system("convert tmp/6k9sx1290558335.ps tmp/6k9sx1290558335.png",intern=TRUE)) character(0) > try(system("convert tmp/7visi1290558335.ps tmp/7visi1290558335.png",intern=TRUE)) character(0) > try(system("convert tmp/8n9r31290558335.ps tmp/8n9r31290558335.png",intern=TRUE)) character(0) > try(system("convert tmp/9n9r31290558335.ps tmp/9n9r31290558335.png",intern=TRUE)) character(0) > try(system("convert tmp/10n9r31290558335.ps tmp/10n9r31290558335.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.045 1.731 10.642