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(100.21 + ,0 + ,100.36 + ,0 + ,100.62 + ,0 + ,100.78 + ,0 + ,100.93 + ,0 + ,100.70 + ,0 + ,100.00 + ,0 + ,100.20 + ,0 + ,99.68 + ,0 + ,99.56 + ,0 + ,100.06 + ,0 + ,100.50 + ,0 + ,99.30 + ,0 + ,99.37 + ,0 + ,99.20 + ,0 + ,98.11 + ,0 + ,97.60 + ,0 + ,97.76 + ,0 + ,98.06 + ,0 + ,98.25 + ,0 + ,98.50 + ,0 + ,97.39 + ,0 + ,98.09 + ,0 + ,97.78 + ,0 + ,98.12 + ,0 + ,97.50 + ,0 + ,97.30 + ,0 + ,97.64 + ,0 + ,96.88 + ,0 + ,97.40 + ,0 + ,98.27 + ,0 + ,97.94 + ,0 + ,98.61 + ,0 + ,98.72 + ,0 + ,98.62 + ,0 + ,98.56 + ,0 + ,98.06 + ,0 + ,97.40 + ,0 + ,97.76 + ,0 + ,97.05 + ,0 + ,97.85 + ,0 + ,97.40 + ,0 + ,97.27 + ,0 + ,97.93 + ,0 + ,98.60 + ,0 + ,98.70 + ,0 + ,98.88 + ,0 + ,98.27 + ,0 + ,97.85 + ,0 + ,97.70 + ,0 + ,96.97 + ,0 + ,97.72 + ,0 + ,97.66 + ,0 + ,99.00 + ,0 + ,98.86 + ,0 + ,99.56 + ,0 + ,100.19 + ,0 + ,100.37 + ,0 + ,100.01 + ,0 + ,99.68 + ,0 + ,99.78 + ,0 + ,99.36 + ,0 + ,99.21 + ,0 + ,99.26 + ,0 + ,99.26 + ,0 + ,100.43 + ,0 + ,101.50 + ,0 + ,102.27 + ,0 + ,102.69 + ,0 + ,103.47 + ,0 + ,104.02 + ,0 + ,103.55 + ,0 + ,103.77 + ,0 + ,104.19 + ,0 + ,103.64 + ,0 + ,103.68 + ,0 + ,105.39 + ,0 + ,106.61 + ,0 + ,108.12 + ,0 + ,109.22 + ,0 + ,110.17 + ,0 + ,110.31 + ,0 + ,111.06 + ,0 + ,111.14 + ,0 + ,111.39 + ,0 + ,112.51 + ,0 + ,111.28 + ,0 + ,112.22 + ,0 + ,113.19 + ,0 + ,114.32 + ,0 + ,115.34 + ,0 + ,116.61 + ,0 + ,117.83 + ,0 + ,117.70 + ,0 + ,118.51 + ,0 + ,118.82 + ,0 + ,119.49 + ,0 + ,119.57 + ,0 + ,120.00 + ,0 + ,121.96 + ,0 + ,121.45 + ,0 + ,123.41 + ,0 + ,124.44 + ,0 + ,126.25 + ,0 + ,127.41 + ,0 + ,127.63 + ,0 + ,129.19 + ,0 + ,129.82 + ,0 + ,130.45 + ,0 + ,132.02 + ,0 + ,132.72 + ,0 + ,132.96 + ,0 + ,135.06 + ,0 + ,137.04 + ,0 + ,137.83 + ,0 + ,139.17 + ,0 + ,140.35 + ,0 + ,141.01 + ,0 + ,141.89 + ,0 + ,143.28 + ,0 + ,142.90 + ,0 + ,143.37 + ,0 + ,145.03 + ,0 + ,146.05 + ,0 + ,147.39 + ,0 + ,149.58 + ,0 + ,151.02 + ,0 + ,153.57 + ,0 + ,155.60 + ,0 + ,157.18 + ,0 + ,158.77 + ,0 + ,159.95 + ,0 + ,161.34 + ,0 + ,161.95 + ,0 + ,163.36 + ,0 + ,165.00 + ,0 + ,166.65 + ,0 + ,168.65 + ,0 + ,170.29 + ,0 + ,172.70 + ,0 + ,173.79 + ,0 + ,176.45 + ,0 + ,177.58 + ,0 + ,179.19 + ,0 + ,181.01 + ,0 + ,184.08 + ,0 + ,185.63 + ,0 + ,188.51 + ,0 + ,190.18 + ,0 + ,192.19 + ,0 + ,193.47 + ,0 + ,196.73 + ,0 + ,200.39 + ,0 + ,203.24 + ,0 + ,205.53 + ,0 + ,208.21 + ,0 + ,208.88 + ,0 + ,212.85 + ,0 + ,216.41 + ,0 + ,216.23 + ,0 + ,219.27 + ,0 + ,222.02 + ,0 + ,224.89 + ,0 + ,230.37 + ,0 + ,232.29 + ,0 + ,235.53 + ,0 + ,236.92 + ,0 + ,242.37 + ,0 + ,242.75 + ,0 + ,244.19 + ,0 + ,247.94 + ,0 + ,248.80 + ,0 + ,250.18 + ,0 + ,251.55 + ,0 + ,254.40 + ,0 + ,255.72 + ,0 + ,257.69 + ,0 + ,258.37 + ,0 + ,258.22 + ,0 + ,258.59 + ,0 + ,257.45 + ,0 + ,257.45 + ,0 + ,256.73 + ,0 + ,258.82 + ,0 + ,257.99 + ,0 + ,262.85 + ,0 + ,262.58 + ,0 + ,261.55 + ,0 + ,261.25 + ,0 + ,259.78 + ,1 + ,256.26 + ,1 + ,254.29 + ,1 + ,248.50 + ,1 + ,241.88 + ,1 + ,238.53 + ,1 + ,232.24 + ,1 + ,232.46 + ,1 + ,225.79 + ,1 + ,221.63 + ,1 + ,219.62 + ,1 + ,215.94 + ,1 + ,211.81 + ,1 + ,205.57 + ,1 + ,201.25 + ,1 + ,194.70 + ,1 + ,187.94 + ,1 + ,185.61 + ,1 + ,181.15 + ,1 + ,186.50 + ,1 + ,183.21 + ,1 + ,182.61 + ,1 + ,187.09 + ,1 + ,189.10 + ,1 + ,191.25 + ,1 + ,190.74 + ,1 + ,190.79 + ,1) + ,dim=c(2 + ,216) + ,dimnames=list(c('Huizenprijs_Pacific' + ,'Dummy_Crisis') + ,1:216)) > y <- array(NA,dim=c(2,216),dimnames=list(c('Huizenprijs_Pacific','Dummy_Crisis'),1:216)) > 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 Huizenprijs_Pacific Dummy_Crisis 1 100.21 0 2 100.36 0 3 100.62 0 4 100.78 0 5 100.93 0 6 100.70 0 7 100.00 0 8 100.20 0 9 99.68 0 10 99.56 0 11 100.06 0 12 100.50 0 13 99.30 0 14 99.37 0 15 99.20 0 16 98.11 0 17 97.60 0 18 97.76 0 19 98.06 0 20 98.25 0 21 98.50 0 22 97.39 0 23 98.09 0 24 97.78 0 25 98.12 0 26 97.50 0 27 97.30 0 28 97.64 0 29 96.88 0 30 97.40 0 31 98.27 0 32 97.94 0 33 98.61 0 34 98.72 0 35 98.62 0 36 98.56 0 37 98.06 0 38 97.40 0 39 97.76 0 40 97.05 0 41 97.85 0 42 97.40 0 43 97.27 0 44 97.93 0 45 98.60 0 46 98.70 0 47 98.88 0 48 98.27 0 49 97.85 0 50 97.70 0 51 96.97 0 52 97.72 0 53 97.66 0 54 99.00 0 55 98.86 0 56 99.56 0 57 100.19 0 58 100.37 0 59 100.01 0 60 99.68 0 61 99.78 0 62 99.36 0 63 99.21 0 64 99.26 0 65 99.26 0 66 100.43 0 67 101.50 0 68 102.27 0 69 102.69 0 70 103.47 0 71 104.02 0 72 103.55 0 73 103.77 0 74 104.19 0 75 103.64 0 76 103.68 0 77 105.39 0 78 106.61 0 79 108.12 0 80 109.22 0 81 110.17 0 82 110.31 0 83 111.06 0 84 111.14 0 85 111.39 0 86 112.51 0 87 111.28 0 88 112.22 0 89 113.19 0 90 114.32 0 91 115.34 0 92 116.61 0 93 117.83 0 94 117.70 0 95 118.51 0 96 118.82 0 97 119.49 0 98 119.57 0 99 120.00 0 100 121.96 0 101 121.45 0 102 123.41 0 103 124.44 0 104 126.25 0 105 127.41 0 106 127.63 0 107 129.19 0 108 129.82 0 109 130.45 0 110 132.02 0 111 132.72 0 112 132.96 0 113 135.06 0 114 137.04 0 115 137.83 0 116 139.17 0 117 140.35 0 118 141.01 0 119 141.89 0 120 143.28 0 121 142.90 0 122 143.37 0 123 145.03 0 124 146.05 0 125 147.39 0 126 149.58 0 127 151.02 0 128 153.57 0 129 155.60 0 130 157.18 0 131 158.77 0 132 159.95 0 133 161.34 0 134 161.95 0 135 163.36 0 136 165.00 0 137 166.65 0 138 168.65 0 139 170.29 0 140 172.70 0 141 173.79 0 142 176.45 0 143 177.58 0 144 179.19 0 145 181.01 0 146 184.08 0 147 185.63 0 148 188.51 0 149 190.18 0 150 192.19 0 151 193.47 0 152 196.73 0 153 200.39 0 154 203.24 0 155 205.53 0 156 208.21 0 157 208.88 0 158 212.85 0 159 216.41 0 160 216.23 0 161 219.27 0 162 222.02 0 163 224.89 0 164 230.37 0 165 232.29 0 166 235.53 0 167 236.92 0 168 242.37 0 169 242.75 0 170 244.19 0 171 247.94 0 172 248.80 0 173 250.18 0 174 251.55 0 175 254.40 0 176 255.72 0 177 257.69 0 178 258.37 0 179 258.22 0 180 258.59 0 181 257.45 0 182 257.45 0 183 256.73 0 184 258.82 0 185 257.99 0 186 262.85 0 187 262.58 0 188 261.55 0 189 261.25 0 190 259.78 1 191 256.26 1 192 254.29 1 193 248.50 1 194 241.88 1 195 238.53 1 196 232.24 1 197 232.46 1 198 225.79 1 199 221.63 1 200 219.62 1 201 215.94 1 202 211.81 1 203 205.57 1 204 201.25 1 205 194.70 1 206 187.94 1 207 185.61 1 208 181.15 1 209 186.50 1 210 183.21 1 211 182.61 1 212 187.09 1 213 189.10 1 214 191.25 1 215 190.74 1 216 190.79 1 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Dummy_Crisis 143.78 67.93 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -46.90 -43.74 -22.08 29.19 119.07 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 143.784 3.776 38.07 < 2e-16 *** Dummy_Crisis 67.929 10.681 6.36 1.21e-09 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 51.92 on 214 degrees of freedom Multiple R-squared: 0.1589, Adjusted R-squared: 0.155 F-statistic: 40.44 on 1 and 214 DF, p-value: 1.206e-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,] 3.898640e-07 7.797280e-07 9.999996e-01 [2,] 2.231734e-09 4.463468e-09 1.000000e+00 [3,] 5.152440e-11 1.030488e-10 1.000000e+00 [4,] 4.590615e-13 9.181229e-13 1.000000e+00 [5,] 1.968296e-14 3.936592e-14 1.000000e+00 [6,] 6.941926e-16 1.388385e-15 1.000000e+00 [7,] 6.875268e-18 1.375054e-17 1.000000e+00 [8,] 6.474164e-20 1.294833e-19 1.000000e+00 [9,] 4.158994e-21 8.317987e-21 1.000000e+00 [10,] 1.357678e-22 2.715355e-22 1.000000e+00 [11,] 5.515390e-24 1.103078e-23 1.000000e+00 [12,] 4.053316e-24 8.106633e-24 1.000000e+00 [13,] 2.444983e-24 4.889966e-24 1.000000e+00 [14,] 3.579450e-25 7.158900e-25 1.000000e+00 [15,] 2.299987e-26 4.599974e-26 1.000000e+00 [16,] 1.033675e-27 2.067349e-27 1.000000e+00 [17,] 3.435506e-29 6.871011e-29 1.000000e+00 [18,] 4.021023e-30 8.042046e-30 1.000000e+00 [19,] 1.698822e-31 3.397643e-31 1.000000e+00 [20,] 9.249669e-33 1.849934e-32 1.000000e+00 [21,] 3.461422e-34 6.922843e-34 1.000000e+00 [22,] 2.267335e-35 4.534669e-35 1.000000e+00 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9.441695e-62 1.888339e-61 1.000000e+00 [90,] 1.940499e-60 3.880998e-60 1.000000e+00 [91,] 4.081493e-59 8.162987e-59 1.000000e+00 [92,] 7.009877e-58 1.401975e-57 1.000000e+00 [93,] 1.183693e-56 2.367386e-56 1.000000e+00 [94,] 1.574850e-55 3.149700e-55 1.000000e+00 [95,] 1.961084e-54 3.922168e-54 1.000000e+00 [96,] 3.938624e-53 7.877248e-53 1.000000e+00 [97,] 5.181364e-52 1.036273e-51 1.000000e+00 [98,] 1.050134e-50 2.100268e-50 1.000000e+00 [99,] 2.306798e-49 4.613595e-49 1.000000e+00 [100,] 6.858863e-48 1.371773e-47 1.000000e+00 [101,] 2.156701e-46 4.313402e-46 1.000000e+00 [102,] 5.448576e-45 1.089715e-44 1.000000e+00 [103,] 1.627854e-43 3.255708e-43 1.000000e+00 [104,] 4.411562e-42 8.823123e-42 1.000000e+00 [105,] 1.102162e-40 2.204324e-40 1.000000e+00 [106,] 3.153796e-39 6.307593e-39 1.000000e+00 [107,] 8.373302e-38 1.674660e-37 1.000000e+00 [108,] 1.912222e-36 3.824443e-36 1.000000e+00 [109,] 5.401142e-35 1.080228e-34 1.000000e+00 [110,] 1.770879e-33 3.541758e-33 1.000000e+00 [111,] 5.301338e-32 1.060268e-31 1.000000e+00 [112,] 1.594224e-30 3.188448e-30 1.000000e+00 [113,] 4.645592e-29 9.291184e-29 1.000000e+00 [114,] 1.216471e-27 2.432942e-27 1.000000e+00 [115,] 2.982424e-26 5.964848e-26 1.000000e+00 [116,] 7.283847e-25 1.456769e-24 1.000000e+00 [117,] 1.459451e-23 2.918903e-23 1.000000e+00 [118,] 2.714046e-22 5.428092e-22 1.000000e+00 [119,] 5.226979e-21 1.045396e-20 1.000000e+00 [120,] 9.734211e-20 1.946842e-19 1.000000e+00 [121,] 1.786452e-18 3.572904e-18 1.000000e+00 [122,] 3.373530e-17 6.747060e-17 1.000000e+00 [123,] 6.086155e-16 1.217231e-15 1.000000e+00 [124,] 1.100695e-14 2.201390e-14 1.000000e+00 [125,] 1.877958e-13 3.755916e-13 1.000000e+00 [126,] 2.898965e-12 5.797931e-12 1.000000e+00 [127,] 4.009818e-11 8.019635e-11 1.000000e+00 [128,] 4.860220e-10 9.720441e-10 1.000000e+00 [129,] 5.190763e-09 1.038153e-08 1.000000e+00 [130,] 4.789612e-08 9.579223e-08 1.000000e+00 [131,] 3.900959e-07 7.801918e-07 9.999996e-01 [132,] 2.797345e-06 5.594691e-06 9.999972e-01 [133,] 1.753117e-05 3.506234e-05 9.999825e-01 [134,] 9.557282e-05 1.911456e-04 9.999044e-01 [135,] 4.490933e-04 8.981866e-04 9.995509e-01 [136,] 1.814329e-03 3.628658e-03 9.981857e-01 [137,] 6.270856e-03 1.254171e-02 9.937291e-01 [138,] 1.855053e-02 3.710107e-02 9.814495e-01 [139,] 4.712214e-02 9.424428e-02 9.528779e-01 [140,] 1.033098e-01 2.066197e-01 8.966902e-01 [141,] 1.965918e-01 3.931837e-01 8.034082e-01 [142,] 3.259870e-01 6.519740e-01 6.740130e-01 [143,] 4.793281e-01 9.586562e-01 5.206719e-01 [144,] 6.324056e-01 7.351888e-01 3.675944e-01 [145,] 7.649377e-01 4.701247e-01 2.350623e-01 [146,] 8.640417e-01 2.719166e-01 1.359583e-01 [147,] 9.293709e-01 1.412581e-01 7.062907e-02 [148,] 9.662514e-01 6.749715e-02 3.374858e-02 [149,] 9.848272e-01 3.034557e-02 1.517278e-02 [150,] 9.935226e-01 1.295476e-02 6.477379e-03 [151,] 9.973546e-01 5.290804e-03 2.645402e-03 [152,] 9.989437e-01 2.112659e-03 1.056330e-03 [153,] 9.996000e-01 8.000864e-04 4.000432e-04 [154,] 9.998438e-01 3.124772e-04 1.562386e-04 [155,] 9.999363e-01 1.274926e-04 6.374628e-05 [156,] 9.999749e-01 5.017202e-05 2.508601e-05 [157,] 9.999896e-01 2.075608e-05 1.037804e-05 [158,] 9.999955e-01 9.079796e-06 4.539898e-06 [159,] 9.999979e-01 4.261340e-06 2.130670e-06 [160,] 9.999988e-01 2.308704e-06 1.154352e-06 [161,] 9.999993e-01 1.341446e-06 6.707229e-07 [162,] 9.999996e-01 8.590677e-07 4.295339e-07 [163,] 9.999997e-01 5.872757e-07 2.936379e-07 [164,] 9.999998e-01 4.524133e-07 2.262066e-07 [165,] 9.999998e-01 3.696022e-07 1.848011e-07 [166,] 9.999998e-01 3.221496e-07 1.610748e-07 [167,] 9.999998e-01 3.032331e-07 1.516166e-07 [168,] 9.999998e-01 3.021814e-07 1.510907e-07 [169,] 9.999998e-01 3.181131e-07 1.590566e-07 [170,] 9.999998e-01 3.523953e-07 1.761976e-07 [171,] 9.999998e-01 4.086570e-07 2.043285e-07 [172,] 9.999998e-01 4.946316e-07 2.473158e-07 [173,] 9.999997e-01 6.199419e-07 3.099709e-07 [174,] 9.999996e-01 8.073505e-07 4.036753e-07 [175,] 9.999995e-01 1.094395e-06 5.471974e-07 [176,] 9.999992e-01 1.533279e-06 7.666397e-07 [177,] 9.999989e-01 2.228343e-06 1.114171e-06 [178,] 9.999983e-01 3.326440e-06 1.663220e-06 [179,] 9.999975e-01 5.086415e-06 2.543208e-06 [180,] 9.999960e-01 7.907379e-06 3.953690e-06 [181,] 9.999937e-01 1.253439e-05 6.267193e-06 [182,] 9.999901e-01 1.989134e-05 9.945671e-06 [183,] 9.999839e-01 3.217676e-05 1.608838e-05 [184,] 9.999734e-01 5.311033e-05 2.655516e-05 [185,] 9.999556e-01 8.883748e-05 4.441874e-05 [186,] 9.999758e-01 4.834100e-05 2.417050e-05 [187,] 9.999875e-01 2.504462e-05 1.252231e-05 [188,] 9.999946e-01 1.073622e-05 5.368110e-06 [189,] 9.999975e-01 4.929895e-06 2.464948e-06 [190,] 9.999986e-01 2.739787e-06 1.369894e-06 [191,] 9.999993e-01 1.437410e-06 7.187052e-07 [192,] 9.999995e-01 9.669727e-07 4.834863e-07 [193,] 9.999998e-01 4.103718e-07 2.051859e-07 [194,] 9.999999e-01 2.360777e-07 1.180389e-07 [195,] 9.999999e-01 1.444237e-07 7.221186e-08 [196,] 1.000000e+00 6.284771e-08 3.142386e-08 [197,] 1.000000e+00 2.144815e-08 1.072408e-08 [198,] 1.000000e+00 5.109167e-09 2.554583e-09 [199,] 1.000000e+00 1.773766e-09 8.868829e-10 [200,] 1.000000e+00 5.767242e-10 2.883621e-10 [201,] 1.000000e+00 1.362914e-09 6.814568e-10 [202,] 1.000000e+00 1.917028e-08 9.585139e-09 [203,] 9.999999e-01 2.544894e-07 1.272447e-07 [204,] 9.999995e-01 1.071559e-06 5.357795e-07 [205,] 9.999924e-01 1.517552e-05 7.587762e-06 [206,] 9.999503e-01 9.935896e-05 4.967948e-05 [207,] 9.999249e-01 1.502003e-04 7.510017e-05 > postscript(file="/var/www/html/rcomp/tmp/1paie1261239931.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2r44r1261239931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/37m941261239931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4lbsj1261239931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/51pq91261239931.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 = 216 Frequency = 1 1 2 3 4 5 6 -43.5739153 -43.4239153 -43.1639153 -43.0039153 -42.8539153 -43.0839153 7 8 9 10 11 12 -43.7839153 -43.5839153 -44.1039153 -44.2239153 -43.7239153 -43.2839153 13 14 15 16 17 18 -44.4839153 -44.4139153 -44.5839153 -45.6739153 -46.1839153 -46.0239153 19 20 21 22 23 24 -45.7239153 -45.5339153 -45.2839153 -46.3939153 -45.6939153 -46.0039153 25 26 27 28 29 30 -45.6639153 -46.2839153 -46.4839153 -46.1439153 -46.9039153 -46.3839153 31 32 33 34 35 36 -45.5139153 -45.8439153 -45.1739153 -45.0639153 -45.1639153 -45.2239153 37 38 39 40 41 42 -45.7239153 -46.3839153 -46.0239153 -46.7339153 -45.9339153 -46.3839153 43 44 45 46 47 48 -46.5139153 -45.8539153 -45.1839153 -45.0839153 -44.9039153 -45.5139153 49 50 51 52 53 54 -45.9339153 -46.0839153 -46.8139153 -46.0639153 -46.1239153 -44.7839153 55 56 57 58 59 60 -44.9239153 -44.2239153 -43.5939153 -43.4139153 -43.7739153 -44.1039153 61 62 63 64 65 66 -44.0039153 -44.4239153 -44.5739153 -44.5239153 -44.5239153 -43.3539153 67 68 69 70 71 72 -42.2839153 -41.5139153 -41.0939153 -40.3139153 -39.7639153 -40.2339153 73 74 75 76 77 78 -40.0139153 -39.5939153 -40.1439153 -40.1039153 -38.3939153 -37.1739153 79 80 81 82 83 84 -35.6639153 -34.5639153 -33.6139153 -33.4739153 -32.7239153 -32.6439153 85 86 87 88 89 90 -32.3939153 -31.2739153 -32.5039153 -31.5639153 -30.5939153 -29.4639153 91 92 93 94 95 96 -28.4439153 -27.1739153 -25.9539153 -26.0839153 -25.2739153 -24.9639153 97 98 99 100 101 102 -24.2939153 -24.2139153 -23.7839153 -21.8239153 -22.3339153 -20.3739153 103 104 105 106 107 108 -19.3439153 -17.5339153 -16.3739153 -16.1539153 -14.5939153 -13.9639153 109 110 111 112 113 114 -13.3339153 -11.7639153 -11.0639153 -10.8239153 -8.7239153 -6.7439153 115 116 117 118 119 120 -5.9539153 -4.6139153 -3.4339153 -2.7739153 -1.8939153 -0.5039153 121 122 123 124 125 126 -0.8839153 -0.4139153 1.2460847 2.2660847 3.6060847 5.7960847 127 128 129 130 131 132 7.2360847 9.7860847 11.8160847 13.3960847 14.9860847 16.1660847 133 134 135 136 137 138 17.5560847 18.1660847 19.5760847 21.2160847 22.8660847 24.8660847 139 140 141 142 143 144 26.5060847 28.9160847 30.0060847 32.6660847 33.7960847 35.4060847 145 146 147 148 149 150 37.2260847 40.2960847 41.8460847 44.7260847 46.3960847 48.4060847 151 152 153 154 155 156 49.6860847 52.9460847 56.6060847 59.4560847 61.7460847 64.4260847 157 158 159 160 161 162 65.0960847 69.0660847 72.6260847 72.4460847 75.4860847 78.2360847 163 164 165 166 167 168 81.1060847 86.5860847 88.5060847 91.7460847 93.1360847 98.5860847 169 170 171 172 173 174 98.9660847 100.4060847 104.1560847 105.0160847 106.3960847 107.7660847 175 176 177 178 179 180 110.6160847 111.9360847 113.9060847 114.5860847 114.4360847 114.8060847 181 182 183 184 185 186 113.6660847 113.6660847 112.9460847 115.0360847 114.2060847 119.0660847 187 188 189 190 191 192 118.7960847 117.7660847 117.4660847 48.0674074 44.5474074 42.5774074 193 194 195 196 197 198 36.7874074 30.1674074 26.8174074 20.5274074 20.7474074 14.0774074 199 200 201 202 203 204 9.9174074 7.9074074 4.2274074 0.0974074 -6.1425926 -10.4625926 205 206 207 208 209 210 -17.0125926 -23.7725926 -26.1025926 -30.5625926 -25.2125926 -28.5025926 211 212 213 214 215 216 -29.1025926 -24.6225926 -22.6125926 -20.4625926 -20.9725926 -20.9225926 > postscript(file="/var/www/html/rcomp/tmp/6w0oh1261239931.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 = 216 Frequency = 1 lag(myerror, k = 1) myerror 0 -43.5739153 NA 1 -43.4239153 -43.5739153 2 -43.1639153 -43.4239153 3 -43.0039153 -43.1639153 4 -42.8539153 -43.0039153 5 -43.0839153 -42.8539153 6 -43.7839153 -43.0839153 7 -43.5839153 -43.7839153 8 -44.1039153 -43.5839153 9 -44.2239153 -44.1039153 10 -43.7239153 -44.2239153 11 -43.2839153 -43.7239153 12 -44.4839153 -43.2839153 13 -44.4139153 -44.4839153 14 -44.5839153 -44.4139153 15 -45.6739153 -44.5839153 16 -46.1839153 -45.6739153 17 -46.0239153 -46.1839153 18 -45.7239153 -46.0239153 19 -45.5339153 -45.7239153 20 -45.2839153 -45.5339153 21 -46.3939153 -45.2839153 22 -45.6939153 -46.3939153 23 -46.0039153 -45.6939153 24 -45.6639153 -46.0039153 25 -46.2839153 -45.6639153 26 -46.4839153 -46.2839153 27 -46.1439153 -46.4839153 28 -46.9039153 -46.1439153 29 -46.3839153 -46.9039153 30 -45.5139153 -46.3839153 31 -45.8439153 -45.5139153 32 -45.1739153 -45.8439153 33 -45.0639153 -45.1739153 34 -45.1639153 -45.0639153 35 -45.2239153 -45.1639153 36 -45.7239153 -45.2239153 37 -46.3839153 -45.7239153 38 -46.0239153 -46.3839153 39 -46.7339153 -46.0239153 40 -45.9339153 -46.7339153 41 -46.3839153 -45.9339153 42 -46.5139153 -46.3839153 43 -45.8539153 -46.5139153 44 -45.1839153 -45.8539153 45 -45.0839153 -45.1839153 46 -44.9039153 -45.0839153 47 -45.5139153 -44.9039153 48 -45.9339153 -45.5139153 49 -46.0839153 -45.9339153 50 -46.8139153 -46.0839153 51 -46.0639153 -46.8139153 52 -46.1239153 -46.0639153 53 -44.7839153 -46.1239153 54 -44.9239153 -44.7839153 55 -44.2239153 -44.9239153 56 -43.5939153 -44.2239153 57 -43.4139153 -43.5939153 58 -43.7739153 -43.4139153 59 -44.1039153 -43.7739153 60 -44.0039153 -44.1039153 61 -44.4239153 -44.0039153 62 -44.5739153 -44.4239153 63 -44.5239153 -44.5739153 64 -44.5239153 -44.5239153 65 -43.3539153 -44.5239153 66 -42.2839153 -43.3539153 67 -41.5139153 -42.2839153 68 -41.0939153 -41.5139153 69 -40.3139153 -41.0939153 70 -39.7639153 -40.3139153 71 -40.2339153 -39.7639153 72 -40.0139153 -40.2339153 73 -39.5939153 -40.0139153 74 -40.1439153 -39.5939153 75 -40.1039153 -40.1439153 76 -38.3939153 -40.1039153 77 -37.1739153 -38.3939153 78 -35.6639153 -37.1739153 79 -34.5639153 -35.6639153 80 -33.6139153 -34.5639153 81 -33.4739153 -33.6139153 82 -32.7239153 -33.4739153 83 -32.6439153 -32.7239153 84 -32.3939153 -32.6439153 85 -31.2739153 -32.3939153 86 -32.5039153 -31.2739153 87 -31.5639153 -32.5039153 88 -30.5939153 -31.5639153 89 -29.4639153 -30.5939153 90 -28.4439153 -29.4639153 91 -27.1739153 -28.4439153 92 -25.9539153 -27.1739153 93 -26.0839153 -25.9539153 94 -25.2739153 -26.0839153 95 -24.9639153 -25.2739153 96 -24.2939153 -24.9639153 97 -24.2139153 -24.2939153 98 -23.7839153 -24.2139153 99 -21.8239153 -23.7839153 100 -22.3339153 -21.8239153 101 -20.3739153 -22.3339153 102 -19.3439153 -20.3739153 103 -17.5339153 -19.3439153 104 -16.3739153 -17.5339153 105 -16.1539153 -16.3739153 106 -14.5939153 -16.1539153 107 -13.9639153 -14.5939153 108 -13.3339153 -13.9639153 109 -11.7639153 -13.3339153 110 -11.0639153 -11.7639153 111 -10.8239153 -11.0639153 112 -8.7239153 -10.8239153 113 -6.7439153 -8.7239153 114 -5.9539153 -6.7439153 115 -4.6139153 -5.9539153 116 -3.4339153 -4.6139153 117 -2.7739153 -3.4339153 118 -1.8939153 -2.7739153 119 -0.5039153 -1.8939153 120 -0.8839153 -0.5039153 121 -0.4139153 -0.8839153 122 1.2460847 -0.4139153 123 2.2660847 1.2460847 124 3.6060847 2.2660847 125 5.7960847 3.6060847 126 7.2360847 5.7960847 127 9.7860847 7.2360847 128 11.8160847 9.7860847 129 13.3960847 11.8160847 130 14.9860847 13.3960847 131 16.1660847 14.9860847 132 17.5560847 16.1660847 133 18.1660847 17.5560847 134 19.5760847 18.1660847 135 21.2160847 19.5760847 136 22.8660847 21.2160847 137 24.8660847 22.8660847 138 26.5060847 24.8660847 139 28.9160847 26.5060847 140 30.0060847 28.9160847 141 32.6660847 30.0060847 142 33.7960847 32.6660847 143 35.4060847 33.7960847 144 37.2260847 35.4060847 145 40.2960847 37.2260847 146 41.8460847 40.2960847 147 44.7260847 41.8460847 148 46.3960847 44.7260847 149 48.4060847 46.3960847 150 49.6860847 48.4060847 151 52.9460847 49.6860847 152 56.6060847 52.9460847 153 59.4560847 56.6060847 154 61.7460847 59.4560847 155 64.4260847 61.7460847 156 65.0960847 64.4260847 157 69.0660847 65.0960847 158 72.6260847 69.0660847 159 72.4460847 72.6260847 160 75.4860847 72.4460847 161 78.2360847 75.4860847 162 81.1060847 78.2360847 163 86.5860847 81.1060847 164 88.5060847 86.5860847 165 91.7460847 88.5060847 166 93.1360847 91.7460847 167 98.5860847 93.1360847 168 98.9660847 98.5860847 169 100.4060847 98.9660847 170 104.1560847 100.4060847 171 105.0160847 104.1560847 172 106.3960847 105.0160847 173 107.7660847 106.3960847 174 110.6160847 107.7660847 175 111.9360847 110.6160847 176 113.9060847 111.9360847 177 114.5860847 113.9060847 178 114.4360847 114.5860847 179 114.8060847 114.4360847 180 113.6660847 114.8060847 181 113.6660847 113.6660847 182 112.9460847 113.6660847 183 115.0360847 112.9460847 184 114.2060847 115.0360847 185 119.0660847 114.2060847 186 118.7960847 119.0660847 187 117.7660847 118.7960847 188 117.4660847 117.7660847 189 48.0674074 117.4660847 190 44.5474074 48.0674074 191 42.5774074 44.5474074 192 36.7874074 42.5774074 193 30.1674074 36.7874074 194 26.8174074 30.1674074 195 20.5274074 26.8174074 196 20.7474074 20.5274074 197 14.0774074 20.7474074 198 9.9174074 14.0774074 199 7.9074074 9.9174074 200 4.2274074 7.9074074 201 0.0974074 4.2274074 202 -6.1425926 0.0974074 203 -10.4625926 -6.1425926 204 -17.0125926 -10.4625926 205 -23.7725926 -17.0125926 206 -26.1025926 -23.7725926 207 -30.5625926 -26.1025926 208 -25.2125926 -30.5625926 209 -28.5025926 -25.2125926 210 -29.1025926 -28.5025926 211 -24.6225926 -29.1025926 212 -22.6125926 -24.6225926 213 -20.4625926 -22.6125926 214 -20.9725926 -20.4625926 215 -20.9225926 -20.9725926 216 NA -20.9225926 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -43.4239153 -43.5739153 [2,] -43.1639153 -43.4239153 [3,] -43.0039153 -43.1639153 [4,] -42.8539153 -43.0039153 [5,] -43.0839153 -42.8539153 [6,] -43.7839153 -43.0839153 [7,] -43.5839153 -43.7839153 [8,] -44.1039153 -43.5839153 [9,] -44.2239153 -44.1039153 [10,] -43.7239153 -44.2239153 [11,] -43.2839153 -43.7239153 [12,] -44.4839153 -43.2839153 [13,] -44.4139153 -44.4839153 [14,] -44.5839153 -44.4139153 [15,] -45.6739153 -44.5839153 [16,] -46.1839153 -45.6739153 [17,] -46.0239153 -46.1839153 [18,] -45.7239153 -46.0239153 [19,] -45.5339153 -45.7239153 [20,] -45.2839153 -45.5339153 [21,] -46.3939153 -45.2839153 [22,] -45.6939153 -46.3939153 [23,] -46.0039153 -45.6939153 [24,] -45.6639153 -46.0039153 [25,] -46.2839153 -45.6639153 [26,] -46.4839153 -46.2839153 [27,] -46.1439153 -46.4839153 [28,] -46.9039153 -46.1439153 [29,] -46.3839153 -46.9039153 [30,] -45.5139153 -46.3839153 [31,] -45.8439153 -45.5139153 [32,] -45.1739153 -45.8439153 [33,] -45.0639153 -45.1739153 [34,] -45.1639153 -45.0639153 [35,] -45.2239153 -45.1639153 [36,] -45.7239153 -45.2239153 [37,] -46.3839153 -45.7239153 [38,] -46.0239153 -46.3839153 [39,] -46.7339153 -46.0239153 [40,] -45.9339153 -46.7339153 [41,] -46.3839153 -45.9339153 [42,] -46.5139153 -46.3839153 [43,] -45.8539153 -46.5139153 [44,] -45.1839153 -45.8539153 [45,] -45.0839153 -45.1839153 [46,] -44.9039153 -45.0839153 [47,] -45.5139153 -44.9039153 [48,] -45.9339153 -45.5139153 [49,] -46.0839153 -45.9339153 [50,] -46.8139153 -46.0839153 [51,] -46.0639153 -46.8139153 [52,] -46.1239153 -46.0639153 [53,] -44.7839153 -46.1239153 [54,] -44.9239153 -44.7839153 [55,] -44.2239153 -44.9239153 [56,] -43.5939153 -44.2239153 [57,] -43.4139153 -43.5939153 [58,] -43.7739153 -43.4139153 [59,] -44.1039153 -43.7739153 [60,] -44.0039153 -44.1039153 [61,] -44.4239153 -44.0039153 [62,] -44.5739153 -44.4239153 [63,] -44.5239153 -44.5739153 [64,] -44.5239153 -44.5239153 [65,] -43.3539153 -44.5239153 [66,] -42.2839153 -43.3539153 [67,] -41.5139153 -42.2839153 [68,] -41.0939153 -41.5139153 [69,] -40.3139153 -41.0939153 [70,] -39.7639153 -40.3139153 [71,] -40.2339153 -39.7639153 [72,] -40.0139153 -40.2339153 [73,] -39.5939153 -40.0139153 [74,] -40.1439153 -39.5939153 [75,] -40.1039153 -40.1439153 [76,] -38.3939153 -40.1039153 [77,] -37.1739153 -38.3939153 [78,] -35.6639153 -37.1739153 [79,] -34.5639153 -35.6639153 [80,] -33.6139153 -34.5639153 [81,] -33.4739153 -33.6139153 [82,] -32.7239153 -33.4739153 [83,] -32.6439153 -32.7239153 [84,] -32.3939153 -32.6439153 [85,] -31.2739153 -32.3939153 [86,] -32.5039153 -31.2739153 [87,] -31.5639153 -32.5039153 [88,] -30.5939153 -31.5639153 [89,] -29.4639153 -30.5939153 [90,] -28.4439153 -29.4639153 [91,] -27.1739153 -28.4439153 [92,] -25.9539153 -27.1739153 [93,] -26.0839153 -25.9539153 [94,] -25.2739153 -26.0839153 [95,] -24.9639153 -25.2739153 [96,] -24.2939153 -24.9639153 [97,] -24.2139153 -24.2939153 [98,] -23.7839153 -24.2139153 [99,] -21.8239153 -23.7839153 [100,] -22.3339153 -21.8239153 [101,] -20.3739153 -22.3339153 [102,] -19.3439153 -20.3739153 [103,] -17.5339153 -19.3439153 [104,] -16.3739153 -17.5339153 [105,] -16.1539153 -16.3739153 [106,] -14.5939153 -16.1539153 [107,] -13.9639153 -14.5939153 [108,] -13.3339153 -13.9639153 [109,] -11.7639153 -13.3339153 [110,] -11.0639153 -11.7639153 [111,] -10.8239153 -11.0639153 [112,] -8.7239153 -10.8239153 [113,] -6.7439153 -8.7239153 [114,] -5.9539153 -6.7439153 [115,] -4.6139153 -5.9539153 [116,] -3.4339153 -4.6139153 [117,] -2.7739153 -3.4339153 [118,] -1.8939153 -2.7739153 [119,] -0.5039153 -1.8939153 [120,] -0.8839153 -0.5039153 [121,] -0.4139153 -0.8839153 [122,] 1.2460847 -0.4139153 [123,] 2.2660847 1.2460847 [124,] 3.6060847 2.2660847 [125,] 5.7960847 3.6060847 [126,] 7.2360847 5.7960847 [127,] 9.7860847 7.2360847 [128,] 11.8160847 9.7860847 [129,] 13.3960847 11.8160847 [130,] 14.9860847 13.3960847 [131,] 16.1660847 14.9860847 [132,] 17.5560847 16.1660847 [133,] 18.1660847 17.5560847 [134,] 19.5760847 18.1660847 [135,] 21.2160847 19.5760847 [136,] 22.8660847 21.2160847 [137,] 24.8660847 22.8660847 [138,] 26.5060847 24.8660847 [139,] 28.9160847 26.5060847 [140,] 30.0060847 28.9160847 [141,] 32.6660847 30.0060847 [142,] 33.7960847 32.6660847 [143,] 35.4060847 33.7960847 [144,] 37.2260847 35.4060847 [145,] 40.2960847 37.2260847 [146,] 41.8460847 40.2960847 [147,] 44.7260847 41.8460847 [148,] 46.3960847 44.7260847 [149,] 48.4060847 46.3960847 [150,] 49.6860847 48.4060847 [151,] 52.9460847 49.6860847 [152,] 56.6060847 52.9460847 [153,] 59.4560847 56.6060847 [154,] 61.7460847 59.4560847 [155,] 64.4260847 61.7460847 [156,] 65.0960847 64.4260847 [157,] 69.0660847 65.0960847 [158,] 72.6260847 69.0660847 [159,] 72.4460847 72.6260847 [160,] 75.4860847 72.4460847 [161,] 78.2360847 75.4860847 [162,] 81.1060847 78.2360847 [163,] 86.5860847 81.1060847 [164,] 88.5060847 86.5860847 [165,] 91.7460847 88.5060847 [166,] 93.1360847 91.7460847 [167,] 98.5860847 93.1360847 [168,] 98.9660847 98.5860847 [169,] 100.4060847 98.9660847 [170,] 104.1560847 100.4060847 [171,] 105.0160847 104.1560847 [172,] 106.3960847 105.0160847 [173,] 107.7660847 106.3960847 [174,] 110.6160847 107.7660847 [175,] 111.9360847 110.6160847 [176,] 113.9060847 111.9360847 [177,] 114.5860847 113.9060847 [178,] 114.4360847 114.5860847 [179,] 114.8060847 114.4360847 [180,] 113.6660847 114.8060847 [181,] 113.6660847 113.6660847 [182,] 112.9460847 113.6660847 [183,] 115.0360847 112.9460847 [184,] 114.2060847 115.0360847 [185,] 119.0660847 114.2060847 [186,] 118.7960847 119.0660847 [187,] 117.7660847 118.7960847 [188,] 117.4660847 117.7660847 [189,] 48.0674074 117.4660847 [190,] 44.5474074 48.0674074 [191,] 42.5774074 44.5474074 [192,] 36.7874074 42.5774074 [193,] 30.1674074 36.7874074 [194,] 26.8174074 30.1674074 [195,] 20.5274074 26.8174074 [196,] 20.7474074 20.5274074 [197,] 14.0774074 20.7474074 [198,] 9.9174074 14.0774074 [199,] 7.9074074 9.9174074 [200,] 4.2274074 7.9074074 [201,] 0.0974074 4.2274074 [202,] -6.1425926 0.0974074 [203,] -10.4625926 -6.1425926 [204,] -17.0125926 -10.4625926 [205,] -23.7725926 -17.0125926 [206,] -26.1025926 -23.7725926 [207,] -30.5625926 -26.1025926 [208,] -25.2125926 -30.5625926 [209,] -28.5025926 -25.2125926 [210,] -29.1025926 -28.5025926 [211,] -24.6225926 -29.1025926 [212,] -22.6125926 -24.6225926 [213,] -20.4625926 -22.6125926 [214,] -20.9725926 -20.4625926 [215,] -20.9225926 -20.9725926 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -43.4239153 -43.5739153 2 -43.1639153 -43.4239153 3 -43.0039153 -43.1639153 4 -42.8539153 -43.0039153 5 -43.0839153 -42.8539153 6 -43.7839153 -43.0839153 7 -43.5839153 -43.7839153 8 -44.1039153 -43.5839153 9 -44.2239153 -44.1039153 10 -43.7239153 -44.2239153 11 -43.2839153 -43.7239153 12 -44.4839153 -43.2839153 13 -44.4139153 -44.4839153 14 -44.5839153 -44.4139153 15 -45.6739153 -44.5839153 16 -46.1839153 -45.6739153 17 -46.0239153 -46.1839153 18 -45.7239153 -46.0239153 19 -45.5339153 -45.7239153 20 -45.2839153 -45.5339153 21 -46.3939153 -45.2839153 22 -45.6939153 -46.3939153 23 -46.0039153 -45.6939153 24 -45.6639153 -46.0039153 25 -46.2839153 -45.6639153 26 -46.4839153 -46.2839153 27 -46.1439153 -46.4839153 28 -46.9039153 -46.1439153 29 -46.3839153 -46.9039153 30 -45.5139153 -46.3839153 31 -45.8439153 -45.5139153 32 -45.1739153 -45.8439153 33 -45.0639153 -45.1739153 34 -45.1639153 -45.0639153 35 -45.2239153 -45.1639153 36 -45.7239153 -45.2239153 37 -46.3839153 -45.7239153 38 -46.0239153 -46.3839153 39 -46.7339153 -46.0239153 40 -45.9339153 -46.7339153 41 -46.3839153 -45.9339153 42 -46.5139153 -46.3839153 43 -45.8539153 -46.5139153 44 -45.1839153 -45.8539153 45 -45.0839153 -45.1839153 46 -44.9039153 -45.0839153 47 -45.5139153 -44.9039153 48 -45.9339153 -45.5139153 49 -46.0839153 -45.9339153 50 -46.8139153 -46.0839153 51 -46.0639153 -46.8139153 52 -46.1239153 -46.0639153 53 -44.7839153 -46.1239153 54 -44.9239153 -44.7839153 55 -44.2239153 -44.9239153 56 -43.5939153 -44.2239153 57 -43.4139153 -43.5939153 58 -43.7739153 -43.4139153 59 -44.1039153 -43.7739153 60 -44.0039153 -44.1039153 61 -44.4239153 -44.0039153 62 -44.5739153 -44.4239153 63 -44.5239153 -44.5739153 64 -44.5239153 -44.5239153 65 -43.3539153 -44.5239153 66 -42.2839153 -43.3539153 67 -41.5139153 -42.2839153 68 -41.0939153 -41.5139153 69 -40.3139153 -41.0939153 70 -39.7639153 -40.3139153 71 -40.2339153 -39.7639153 72 -40.0139153 -40.2339153 73 -39.5939153 -40.0139153 74 -40.1439153 -39.5939153 75 -40.1039153 -40.1439153 76 -38.3939153 -40.1039153 77 -37.1739153 -38.3939153 78 -35.6639153 -37.1739153 79 -34.5639153 -35.6639153 80 -33.6139153 -34.5639153 81 -33.4739153 -33.6139153 82 -32.7239153 -33.4739153 83 -32.6439153 -32.7239153 84 -32.3939153 -32.6439153 85 -31.2739153 -32.3939153 86 -32.5039153 -31.2739153 87 -31.5639153 -32.5039153 88 -30.5939153 -31.5639153 89 -29.4639153 -30.5939153 90 -28.4439153 -29.4639153 91 -27.1739153 -28.4439153 92 -25.9539153 -27.1739153 93 -26.0839153 -25.9539153 94 -25.2739153 -26.0839153 95 -24.9639153 -25.2739153 96 -24.2939153 -24.9639153 97 -24.2139153 -24.2939153 98 -23.7839153 -24.2139153 99 -21.8239153 -23.7839153 100 -22.3339153 -21.8239153 101 -20.3739153 -22.3339153 102 -19.3439153 -20.3739153 103 -17.5339153 -19.3439153 104 -16.3739153 -17.5339153 105 -16.1539153 -16.3739153 106 -14.5939153 -16.1539153 107 -13.9639153 -14.5939153 108 -13.3339153 -13.9639153 109 -11.7639153 -13.3339153 110 -11.0639153 -11.7639153 111 -10.8239153 -11.0639153 112 -8.7239153 -10.8239153 113 -6.7439153 -8.7239153 114 -5.9539153 -6.7439153 115 -4.6139153 -5.9539153 116 -3.4339153 -4.6139153 117 -2.7739153 -3.4339153 118 -1.8939153 -2.7739153 119 -0.5039153 -1.8939153 120 -0.8839153 -0.5039153 121 -0.4139153 -0.8839153 122 1.2460847 -0.4139153 123 2.2660847 1.2460847 124 3.6060847 2.2660847 125 5.7960847 3.6060847 126 7.2360847 5.7960847 127 9.7860847 7.2360847 128 11.8160847 9.7860847 129 13.3960847 11.8160847 130 14.9860847 13.3960847 131 16.1660847 14.9860847 132 17.5560847 16.1660847 133 18.1660847 17.5560847 134 19.5760847 18.1660847 135 21.2160847 19.5760847 136 22.8660847 21.2160847 137 24.8660847 22.8660847 138 26.5060847 24.8660847 139 28.9160847 26.5060847 140 30.0060847 28.9160847 141 32.6660847 30.0060847 142 33.7960847 32.6660847 143 35.4060847 33.7960847 144 37.2260847 35.4060847 145 40.2960847 37.2260847 146 41.8460847 40.2960847 147 44.7260847 41.8460847 148 46.3960847 44.7260847 149 48.4060847 46.3960847 150 49.6860847 48.4060847 151 52.9460847 49.6860847 152 56.6060847 52.9460847 153 59.4560847 56.6060847 154 61.7460847 59.4560847 155 64.4260847 61.7460847 156 65.0960847 64.4260847 157 69.0660847 65.0960847 158 72.6260847 69.0660847 159 72.4460847 72.6260847 160 75.4860847 72.4460847 161 78.2360847 75.4860847 162 81.1060847 78.2360847 163 86.5860847 81.1060847 164 88.5060847 86.5860847 165 91.7460847 88.5060847 166 93.1360847 91.7460847 167 98.5860847 93.1360847 168 98.9660847 98.5860847 169 100.4060847 98.9660847 170 104.1560847 100.4060847 171 105.0160847 104.1560847 172 106.3960847 105.0160847 173 107.7660847 106.3960847 174 110.6160847 107.7660847 175 111.9360847 110.6160847 176 113.9060847 111.9360847 177 114.5860847 113.9060847 178 114.4360847 114.5860847 179 114.8060847 114.4360847 180 113.6660847 114.8060847 181 113.6660847 113.6660847 182 112.9460847 113.6660847 183 115.0360847 112.9460847 184 114.2060847 115.0360847 185 119.0660847 114.2060847 186 118.7960847 119.0660847 187 117.7660847 118.7960847 188 117.4660847 117.7660847 189 48.0674074 117.4660847 190 44.5474074 48.0674074 191 42.5774074 44.5474074 192 36.7874074 42.5774074 193 30.1674074 36.7874074 194 26.8174074 30.1674074 195 20.5274074 26.8174074 196 20.7474074 20.5274074 197 14.0774074 20.7474074 198 9.9174074 14.0774074 199 7.9074074 9.9174074 200 4.2274074 7.9074074 201 0.0974074 4.2274074 202 -6.1425926 0.0974074 203 -10.4625926 -6.1425926 204 -17.0125926 -10.4625926 205 -23.7725926 -17.0125926 206 -26.1025926 -23.7725926 207 -30.5625926 -26.1025926 208 -25.2125926 -30.5625926 209 -28.5025926 -25.2125926 210 -29.1025926 -28.5025926 211 -24.6225926 -29.1025926 212 -22.6125926 -24.6225926 213 -20.4625926 -22.6125926 214 -20.9725926 -20.4625926 215 -20.9225926 -20.9725926 > 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/7fbqb1261239931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/84tuj1261239931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9rjw71261239931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10ka681261239931.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/111lt71261239931.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/12zp4w1261239931.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/13t3cm1261239931.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/14w9u41261239931.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/153hm01261239931.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/16ceh21261239932.tab") + } > > try(system("convert tmp/1paie1261239931.ps tmp/1paie1261239931.png",intern=TRUE)) character(0) > try(system("convert tmp/2r44r1261239931.ps tmp/2r44r1261239931.png",intern=TRUE)) character(0) > try(system("convert tmp/37m941261239931.ps tmp/37m941261239931.png",intern=TRUE)) character(0) > try(system("convert tmp/4lbsj1261239931.ps tmp/4lbsj1261239931.png",intern=TRUE)) character(0) > try(system("convert tmp/51pq91261239931.ps tmp/51pq91261239931.png",intern=TRUE)) character(0) > try(system("convert tmp/6w0oh1261239931.ps tmp/6w0oh1261239931.png",intern=TRUE)) character(0) > try(system("convert tmp/7fbqb1261239931.ps tmp/7fbqb1261239931.png",intern=TRUE)) character(0) > try(system("convert tmp/84tuj1261239931.ps tmp/84tuj1261239931.png",intern=TRUE)) character(0) > try(system("convert tmp/9rjw71261239931.ps tmp/9rjw71261239931.png",intern=TRUE)) character(0) > try(system("convert tmp/10ka681261239931.ps tmp/10ka681261239931.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.774 1.730 5.565