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. 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,0 + ,0 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1) + ,dim=c(13 + ,154) + ,dimnames=list(c('Y' + ,'Use_limit_Yes' + ,'Use_limit_NO' + ,'T40_Treatment' + ,'T40_NO_treatment' + ,'T20_Treatment' + ,'T20_NO_treatment' + ,'Used_stat' + ,'used_No_statist' + ,'correctanalys_yes' + ,'correctanalysys_No' + ,'Useful_yes' + ,'Useful_NO') + ,1:154)) > y <- array(NA,dim=c(13,154),dimnames=list(c('Y','Use_limit_Yes','Use_limit_NO','T40_Treatment','T40_NO_treatment','T20_Treatment','T20_NO_treatment','Used_stat','used_No_statist','correctanalys_yes','correctanalysys_No','Useful_yes','Useful_NO'),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 = '1' > 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, 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 Y Use_limit_Yes Use_limit_NO T40_Treatment T40_NO_treatment T20_Treatment 1 4 1 0 1 0 0 2 4 0 1 0 1 0 3 4 0 1 0 1 0 4 4 0 1 0 1 0 5 4 0 1 0 1 0 6 4 1 0 0 1 0 7 4 0 1 0 1 0 8 4 0 1 1 0 0 9 4 0 1 0 1 0 10 4 1 0 0 1 0 11 4 1 0 1 0 0 12 4 0 1 0 1 0 13 4 0 1 0 1 0 14 4 1 0 1 0 0 15 4 0 1 0 1 0 16 4 0 1 1 0 0 17 4 1 0 1 0 0 18 4 1 0 1 0 0 19 4 0 1 0 1 0 20 4 0 1 1 0 0 21 4 1 0 0 1 0 22 4 1 0 0 1 0 23 4 0 1 0 1 0 24 4 1 0 0 1 0 25 4 0 1 1 0 0 26 4 0 1 0 1 0 27 4 1 0 0 1 0 28 4 0 1 0 1 0 29 4 0 1 0 1 0 30 4 0 1 0 1 0 31 4 0 1 0 1 0 32 4 1 0 0 1 0 33 4 1 0 0 1 0 34 4 0 1 1 0 0 35 4 0 1 0 1 0 36 4 0 1 0 1 0 37 4 1 0 1 0 0 38 4 0 1 0 1 0 39 4 0 1 0 1 0 40 4 0 1 1 0 0 41 4 0 1 0 1 0 42 4 0 1 0 1 0 43 4 1 0 0 1 0 44 4 1 0 1 0 0 45 4 0 1 0 1 0 46 4 0 1 0 1 0 47 4 0 1 0 1 0 48 4 0 1 0 1 0 49 4 0 1 0 1 0 50 4 0 1 0 1 0 51 4 0 1 1 0 0 52 4 1 0 1 0 0 53 4 0 1 0 1 0 54 4 0 1 0 1 0 55 4 0 1 0 1 0 56 4 0 1 1 0 0 57 4 0 1 0 1 0 58 4 0 1 0 1 0 59 4 0 1 0 1 0 60 4 1 0 1 0 0 61 4 1 0 1 0 0 62 4 0 1 0 1 0 63 4 0 1 0 1 0 64 4 1 0 1 0 0 65 4 0 1 0 1 0 66 4 0 1 0 1 0 67 4 0 1 1 0 0 68 4 1 0 0 1 0 69 4 0 1 0 1 0 70 4 0 1 0 1 0 71 4 0 1 0 1 0 72 4 0 1 0 1 0 73 4 0 1 0 1 0 74 4 1 0 0 1 0 75 4 0 1 0 1 0 76 4 0 1 1 0 0 77 4 0 1 0 1 0 78 4 0 1 0 1 0 79 4 0 1 1 0 0 80 4 0 1 1 0 0 81 4 0 1 0 1 0 82 4 1 0 0 1 0 83 4 0 1 0 1 0 84 4 0 1 0 1 0 85 4 0 1 0 1 0 86 4 1 0 0 1 0 87 2 1 0 0 0 0 88 2 1 0 0 0 1 89 2 0 1 0 0 0 90 2 0 1 0 0 0 91 2 0 1 0 0 0 92 2 1 0 0 0 1 93 2 1 0 0 0 0 94 2 0 1 0 0 0 95 2 0 1 0 0 1 96 2 0 1 0 0 0 97 2 1 0 0 0 1 98 2 0 1 0 0 0 99 2 1 0 0 0 0 100 2 0 1 0 0 0 101 2 1 0 0 0 0 102 2 0 1 0 0 0 103 2 0 1 0 0 0 104 2 0 1 0 0 0 105 2 0 1 0 0 1 106 2 0 1 0 0 0 107 2 0 1 0 0 0 108 2 1 0 0 0 1 109 2 0 1 0 0 0 110 2 1 0 0 0 0 111 2 1 0 0 0 1 112 2 0 1 0 0 1 113 2 0 1 0 0 0 114 2 1 0 0 0 1 115 2 1 0 0 0 0 116 2 0 1 0 0 0 117 2 1 0 0 0 0 118 2 1 0 0 0 0 119 2 0 1 0 0 0 120 2 0 1 0 0 0 121 2 1 0 0 0 0 122 2 0 1 0 0 0 123 2 1 0 0 0 1 124 2 0 1 0 0 0 125 2 0 1 0 0 0 126 2 0 1 0 0 1 127 2 0 1 0 0 0 128 2 0 1 0 0 0 129 2 0 1 0 0 0 130 2 0 1 0 0 0 131 2 1 0 0 0 0 132 2 1 0 0 0 0 133 2 1 0 0 0 0 134 2 0 1 0 0 0 135 2 0 1 0 0 0 136 2 0 1 0 0 0 137 2 1 0 0 0 0 138 2 1 0 0 0 1 139 2 0 1 0 0 1 140 2 0 1 0 0 0 141 2 0 1 0 0 0 142 2 0 1 0 0 1 143 2 1 0 0 0 0 144 2 0 1 0 0 0 145 2 0 1 0 0 0 146 2 0 1 0 0 1 147 2 0 1 0 0 1 148 2 0 1 0 0 1 149 2 1 0 0 0 0 150 2 0 1 0 0 0 151 2 0 1 0 0 0 152 2 1 0 0 0 0 153 2 1 0 0 0 0 154 2 1 0 0 0 0 T20_NO_treatment Used_stat used_No_statist correctanalys_yes 1 0 0 1 0 2 0 0 1 0 3 0 0 1 0 4 0 0 1 0 5 0 0 1 0 6 0 0 1 0 7 0 0 1 0 8 0 0 1 0 9 0 0 1 0 10 0 0 1 0 11 0 0 1 0 12 0 0 1 0 13 0 1 0 0 14 0 0 1 0 15 0 1 0 0 16 0 1 0 0 17 0 1 0 1 18 0 0 1 0 19 0 0 1 0 20 0 1 0 1 21 0 0 1 0 22 0 1 0 0 23 0 0 1 0 24 0 0 1 0 25 0 1 0 0 26 0 1 0 0 27 0 0 1 0 28 0 1 0 0 29 0 0 1 0 30 0 0 1 0 31 0 0 1 0 32 0 0 1 0 33 0 0 1 0 34 0 0 1 0 35 0 0 1 0 36 0 0 1 0 37 0 1 0 0 38 0 1 0 0 39 0 0 1 0 40 0 0 1 0 41 0 1 0 1 42 0 1 0 0 43 0 0 1 0 44 0 0 1 0 45 0 0 1 0 46 0 0 1 0 47 0 0 1 0 48 0 0 1 0 49 0 0 1 0 50 0 0 1 0 51 0 1 0 0 52 0 1 0 1 53 0 0 1 0 54 0 1 0 1 55 0 0 1 0 56 0 1 0 0 57 0 1 0 0 58 0 0 1 0 59 0 0 1 0 60 0 1 0 1 61 0 0 1 0 62 0 1 0 0 63 0 0 1 0 64 0 0 1 0 65 0 0 1 0 66 0 0 1 0 67 0 1 0 1 68 0 0 1 0 69 0 0 1 0 70 0 1 0 0 71 0 0 1 0 72 0 0 1 0 73 0 1 0 0 74 0 1 0 0 75 0 0 1 0 76 0 0 1 0 77 0 0 1 0 78 0 1 0 0 79 0 1 0 1 80 0 0 1 0 81 0 0 1 0 82 0 1 0 0 83 0 0 1 0 84 0 1 0 1 85 0 0 1 0 86 0 0 1 0 87 1 0 1 0 88 0 1 0 0 89 1 0 1 0 90 1 0 1 0 91 1 0 1 0 92 0 0 1 0 93 1 0 1 0 94 1 0 1 0 95 0 0 1 0 96 1 0 1 0 97 0 0 1 0 98 1 0 1 0 99 1 0 1 0 100 1 0 1 0 101 1 0 1 0 102 1 0 1 0 103 1 0 1 0 104 1 0 1 0 105 0 1 0 0 106 1 0 1 0 107 1 0 1 0 108 0 1 0 0 109 1 0 1 0 110 1 0 1 0 111 0 1 0 0 112 0 0 1 0 113 1 1 0 0 114 0 1 0 0 115 1 0 1 0 116 1 0 1 0 117 1 0 1 0 118 1 0 1 0 119 1 0 1 0 120 1 0 1 0 121 1 0 1 0 122 1 0 1 0 123 0 1 0 0 124 1 1 0 0 125 1 0 1 0 126 0 0 1 0 127 1 0 1 0 128 1 0 1 0 129 1 0 1 0 130 1 0 1 0 131 1 0 1 0 132 1 0 1 0 133 1 1 0 0 134 1 0 1 0 135 1 0 1 0 136 1 0 1 0 137 1 1 0 0 138 0 1 0 0 139 0 0 1 0 140 1 0 1 0 141 1 1 0 1 142 0 1 0 0 143 1 0 1 0 144 1 0 1 0 145 1 0 1 0 146 0 0 1 0 147 0 1 0 0 148 0 0 1 0 149 1 0 1 0 150 1 0 1 0 151 1 0 1 0 152 1 1 0 1 153 1 1 0 1 154 1 1 0 0 correctanalysys_No Useful_yes Useful_NO 1 1 0 1 2 1 0 1 3 1 0 1 4 1 0 1 5 1 0 1 6 1 1 0 7 1 0 1 8 1 0 1 9 1 0 1 10 1 0 1 11 1 0 1 12 1 0 1 13 1 1 0 14 1 0 1 15 1 1 0 16 1 1 0 17 0 1 0 18 1 0 1 19 1 0 1 20 0 1 0 21 1 1 0 22 1 1 0 23 1 1 0 24 1 1 0 25 1 0 1 26 1 1 0 27 1 0 1 28 1 0 1 29 1 0 1 30 1 1 0 31 1 0 1 32 1 0 1 33 1 1 0 34 1 0 1 35 1 0 1 36 1 0 1 37 1 1 0 38 1 0 1 39 1 1 0 40 1 1 0 41 0 1 0 42 1 0 1 43 1 1 0 44 1 0 1 45 1 1 0 46 1 1 0 47 1 0 1 48 1 0 1 49 1 1 0 50 1 0 1 51 1 0 1 52 0 1 0 53 1 0 1 54 0 0 1 55 1 0 1 56 1 0 1 57 1 1 0 58 1 0 1 59 1 0 1 60 0 1 0 61 1 0 1 62 1 1 0 63 1 0 1 64 1 0 1 65 1 0 1 66 1 0 1 67 0 1 0 68 1 0 1 69 1 0 1 70 1 0 1 71 1 0 1 72 1 0 1 73 1 0 1 74 1 0 1 75 1 0 1 76 1 1 0 77 1 0 1 78 1 1 0 79 0 0 1 80 1 1 0 81 1 0 1 82 1 0 1 83 1 0 1 84 0 0 1 85 1 1 0 86 1 0 1 87 1 0 1 88 1 0 1 89 1 0 1 90 1 0 1 91 1 1 0 92 1 0 1 93 1 1 0 94 1 0 1 95 1 0 1 96 1 0 1 97 1 0 1 98 1 0 1 99 1 0 1 100 1 0 1 101 1 0 1 102 1 0 1 103 1 0 1 104 1 0 1 105 1 0 1 106 1 0 1 107 1 0 1 108 1 0 1 109 1 0 1 110 1 0 1 111 1 1 0 112 1 0 1 113 1 0 1 114 1 0 1 115 1 0 1 116 1 0 1 117 1 0 1 118 1 0 1 119 1 0 1 120 1 0 1 121 1 0 1 122 1 0 1 123 1 0 1 124 1 1 0 125 1 0 1 126 1 0 1 127 1 1 0 128 1 0 1 129 1 0 1 130 1 0 1 131 1 0 1 132 1 0 1 133 1 0 1 134 1 0 1 135 1 0 1 136 1 0 1 137 1 1 0 138 1 1 0 139 1 0 1 140 1 0 1 141 0 0 1 142 1 0 1 143 1 0 1 144 1 1 0 145 1 1 0 146 1 0 1 147 1 0 1 148 1 0 1 149 1 0 1 150 1 1 0 151 1 0 1 152 0 0 1 153 0 1 0 154 1 0 1 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Use_limit_Yes Use_limit_NO T40_Treatment 2.000e+00 7.642e-17 NA 2.000e+00 T40_NO_treatment T20_Treatment T20_NO_treatment Used_stat 2.000e+00 5.180e-18 NA 5.942e-18 used_No_statist correctanalys_yes correctanalysys_No Useful_yes NA -1.380e-17 NA -2.752e-17 Useful_NO NA > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -1.173e-15 -3.939e-17 -6.690e-18 4.290e-17 1.320e-15 Coefficients: (5 not defined because of singularities) Estimate Std. Error t value Pr(>|t|) (Intercept) 2.000e+00 2.675e-17 7.477e+16 <2e-16 *** Use_limit_Yes 7.642e-17 3.023e-17 2.528e+00 0.0125 * Use_limit_NO NA NA NA NA T40_Treatment 2.000e+00 4.490e-17 4.454e+16 <2e-16 *** T40_NO_treatment 2.000e+00 3.295e-17 6.069e+16 <2e-16 *** T20_Treatment 5.180e-18 5.030e-17 1.030e-01 0.9181 T20_NO_treatment NA NA NA NA Used_stat 5.942e-18 3.626e-17 1.640e-01 0.8701 used_No_statist NA NA NA NA correctanalys_yes -1.380e-17 6.031e-17 -2.290e-01 0.8193 correctanalysys_No NA NA NA NA Useful_yes -2.751e-17 3.310e-17 -8.310e-01 0.4071 Useful_NO NA NA NA NA --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 1.702e-16 on 146 degrees of freedom Multiple R-squared: 1, Adjusted R-squared: 1 F-statistic: 7.489e+32 on 7 and 146 DF, p-value: < 2.2e-16 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 0.000000e+00 0.000000e+00 1.000000e+00 [2,] 2.130654e-01 4.261308e-01 7.869346e-01 [3,] 9.999983e-01 3.436704e-06 1.718352e-06 [4,] 1.000000e+00 8.374341e-08 4.187171e-08 [5,] 9.994940e-01 1.011936e-03 5.059681e-04 [6,] 3.652830e-13 7.305660e-13 1.000000e+00 [7,] 1.104744e-01 2.209488e-01 8.895256e-01 [8,] 1.000000e+00 2.822205e-34 1.411103e-34 [9,] 5.258413e-01 9.483175e-01 4.741587e-01 [10,] 2.330209e-01 4.660418e-01 7.669791e-01 [11,] 2.373755e-19 4.747511e-19 1.000000e+00 [12,] 1.000000e+00 3.771643e-08 1.885822e-08 [13,] 1.000000e+00 6.140335e-08 3.070167e-08 [14,] 8.082729e-01 3.834543e-01 1.917271e-01 [15,] 1.000000e+00 2.644260e-10 1.322130e-10 [16,] 9.975635e-01 4.872945e-03 2.436472e-03 [17,] 3.547085e-05 7.094171e-05 9.999645e-01 [18,] 1.000000e+00 1.858091e-15 9.290455e-16 [19,] 5.754314e-03 1.150863e-02 9.942457e-01 [20,] 5.890733e-02 1.178147e-01 9.410927e-01 [21,] 1.000000e+00 6.621090e-08 3.310545e-08 [22,] 8.543758e-01 2.912483e-01 1.456242e-01 [23,] 1.000000e+00 2.649374e-26 1.324687e-26 [24,] 1.616564e-32 3.233128e-32 1.000000e+00 [25,] 9.999958e-01 8.496298e-06 4.248149e-06 [26,] 6.210749e-07 1.242150e-06 9.999994e-01 [27,] 1.495021e-05 2.990042e-05 9.999850e-01 [28,] 1.000000e+00 1.812717e-08 9.063587e-09 [29,] 4.216447e-15 8.432895e-15 1.000000e+00 [30,] 9.999999e-01 1.124127e-07 5.620636e-08 [31,] 1.761507e-10 3.523013e-10 1.000000e+00 [32,] 9.999999e-01 1.827475e-07 9.137373e-08 [33,] 1.000000e+00 3.620696e-18 1.810348e-18 [34,] 9.989694e-01 2.061119e-03 1.030559e-03 [35,] 8.510092e-07 1.702018e-06 9.999991e-01 [36,] 1.000000e+00 8.628148e-15 4.314074e-15 [37,] 8.863631e-50 1.772726e-49 1.000000e+00 [38,] 1.000000e+00 2.957048e-15 1.478524e-15 [39,] 1.339099e-02 2.678198e-02 9.866090e-01 [40,] 9.999968e-01 6.366799e-06 3.183399e-06 [41,] 1.000000e+00 1.419165e-27 7.095827e-28 [42,] 5.571348e-02 1.114270e-01 9.442865e-01 [43,] 1.000000e+00 1.456937e-43 7.284686e-44 [44,] 1.000000e+00 1.618118e-27 8.090589e-28 [45,] 1.000000e+00 2.473159e-39 1.236580e-39 [46,] 1.000000e+00 1.516610e-08 7.583051e-09 [47,] 9.999918e-01 1.632963e-05 8.164816e-06 [48,] 1.000000e+00 1.441081e-14 7.205406e-15 [49,] 0.000000e+00 0.000000e+00 1.000000e+00 [50,] 1.000000e+00 5.938048e-12 2.969024e-12 [51,] 1.000000e+00 8.116107e-28 4.058053e-28 [52,] 6.436125e-03 1.287225e-02 9.935639e-01 [53,] 3.336265e-23 6.672529e-23 1.000000e+00 [54,] 9.754849e-05 1.950970e-04 9.999025e-01 [55,] 1.123769e-54 2.247537e-54 1.000000e+00 [56,] 9.999996e-01 8.177669e-07 4.088835e-07 [57,] 9.934107e-01 1.317853e-02 6.589263e-03 [58,] 1.000000e+00 1.215816e-11 6.079080e-12 [59,] 1.239722e-23 2.479444e-23 1.000000e+00 [60,] 1.000000e+00 2.348058e-32 1.174029e-32 [61,] 1.000000e+00 2.114409e-50 1.057204e-50 [62,] 1.000000e+00 2.356688e-16 1.178344e-16 [63,] 1.000000e+00 3.753423e-22 1.876712e-22 [64,] 9.987716e-01 2.456799e-03 1.228400e-03 [65,] 1.000000e+00 1.226483e-64 6.132415e-65 [66,] 9.999668e-01 6.641238e-05 3.320619e-05 [67,] 9.745321e-01 5.093582e-02 2.546791e-02 [68,] 1.000000e+00 1.074617e-57 5.373083e-58 [69,] 1.351678e-57 2.703356e-57 1.000000e+00 [70,] 1.000000e+00 1.158260e-61 5.791298e-62 [71,] 1.000000e+00 1.184285e-16 5.921423e-17 [72,] 2.018418e-07 4.036836e-07 9.999998e-01 [73,] 1.116155e-07 2.232310e-07 9.999999e-01 [74,] 9.999998e-01 4.858796e-07 2.429398e-07 [75,] 1.000000e+00 0.000000e+00 0.000000e+00 [76,] 9.916513e-01 1.669730e-02 8.348651e-03 [77,] 1.000000e+00 7.075318e-19 3.537659e-19 [78,] 2.180634e-04 4.361267e-04 9.997819e-01 [79,] 5.209520e-27 1.041904e-26 1.000000e+00 [80,] 2.794086e-01 5.588172e-01 7.205914e-01 [81,] 9.052223e-18 1.810445e-17 1.000000e+00 [82,] 1.000000e+00 3.488694e-12 1.744347e-12 [83,] 7.521562e-01 4.956876e-01 2.478438e-01 [84,] 9.302551e-01 1.394899e-01 6.974493e-02 [85,] 9.999998e-01 3.513634e-07 1.756817e-07 [86,] 5.078567e-07 1.015713e-06 9.999995e-01 [87,] 1.000000e+00 5.048851e-72 2.524426e-72 [88,] 9.234449e-01 1.531102e-01 7.655509e-02 [89,] 1.000000e+00 9.280879e-14 4.640439e-14 [90,] 9.999944e-01 1.121961e-05 5.609805e-06 [91,] 7.712573e-01 4.574853e-01 2.287427e-01 [92,] 9.999511e-01 9.777805e-05 4.888902e-05 [93,] 1.000000e+00 2.746273e-27 1.373137e-27 [94,] 9.999994e-01 1.288868e-06 6.444342e-07 [95,] 1.000000e+00 3.485033e-37 1.742517e-37 [96,] 9.884812e-01 2.303755e-02 1.151877e-02 [97,] 1.000000e+00 1.687851e-18 8.439256e-19 [98,] 1.000000e+00 2.323546e-21 1.161773e-21 [99,] 9.988243e-01 2.351327e-03 1.175663e-03 [100,] 1.000000e+00 2.569727e-46 1.284864e-46 [101,] 9.472976e-01 1.054049e-01 5.270244e-02 [102,] 1.000000e+00 1.118045e-10 5.590223e-11 [103,] 2.360607e-01 4.721214e-01 7.639393e-01 [104,] 9.972280e-01 5.544063e-03 2.772032e-03 [105,] 9.999998e-01 3.013580e-07 1.506790e-07 [106,] 6.443311e-02 1.288662e-01 9.355669e-01 [107,] 1.000000e+00 1.619909e-14 8.099547e-15 [108,] 8.063492e-01 3.873015e-01 1.936508e-01 [109,] 9.999527e-01 9.458671e-05 4.729336e-05 [110,] 3.460858e-01 6.921716e-01 6.539142e-01 [111,] 9.130810e-01 1.738380e-01 8.691898e-02 [112,] 9.955626e-01 8.874860e-03 4.437430e-03 [113,] 1.000000e+00 1.760769e-19 8.803845e-20 [114,] 9.996730e-01 6.539186e-04 3.269593e-04 [115,] 5.094284e-02 1.018857e-01 9.490572e-01 [116,] 6.201634e-03 1.240327e-02 9.937984e-01 [117,] 9.855885e-01 2.882294e-02 1.441147e-02 [118,] 1.000000e+00 3.716449e-12 1.858224e-12 [119,] 9.994780e-01 1.043921e-03 5.219605e-04 [120,] 4.680171e-07 9.360343e-07 9.999995e-01 [121,] 7.140853e-01 5.718294e-01 2.859147e-01 [122,] 9.972887e-01 5.422627e-03 2.711313e-03 [123,] 1.000000e+00 0.000000e+00 0.000000e+00 > postscript(file="/var/wessaorg/rcomp/tmp/1144b1355827917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2dj031355827917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3dac81355827917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4nepb1355827917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5mge91355827917.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 1.320002e-15 4.715360e-16 5.782818e-16 -1.172576e-15 3.368023e-17 6 7 8 9 10 -1.225544e-16 3.368023e-17 -5.236871e-17 3.368023e-17 -1.500697e-16 11 12 13 14 15 -9.841814e-17 3.368023e-17 5.525310e-17 -9.841814e-17 5.525310e-17 16 17 18 19 20 -3.079584e-17 -6.304240e-17 -9.841814e-17 3.368023e-17 -1.699297e-17 21 22 23 24 25 -1.225544e-16 -1.284968e-16 6.119553e-17 -1.225544e-16 -5.831114e-17 26 27 28 29 30 5.525310e-17 -1.500697e-16 2.773779e-17 3.368023e-17 6.119553e-17 31 32 33 34 35 3.368023e-17 -1.500697e-16 -1.225544e-16 -5.236871e-17 3.368023e-17 36 37 38 39 40 3.368023e-17 -7.684527e-17 2.773779e-17 6.119553e-17 -2.485340e-17 41 42 43 44 45 6.905596e-17 2.773779e-17 -1.225544e-16 -9.841814e-17 6.119553e-17 46 47 48 49 50 6.119553e-17 3.368023e-17 3.368023e-17 6.119553e-17 3.368023e-17 51 52 53 54 55 -5.831114e-17 -6.304240e-17 3.368023e-17 4.154066e-17 3.368023e-17 56 57 58 59 60 -5.831114e-17 5.525310e-17 3.368023e-17 3.368023e-17 -6.304240e-17 61 62 63 64 65 -9.841814e-17 5.525310e-17 3.368023e-17 -9.841814e-17 3.368023e-17 66 67 68 69 70 3.368023e-17 -1.699297e-17 -1.500697e-16 3.368023e-17 2.773779e-17 71 72 73 74 75 3.368023e-17 3.368023e-17 2.773779e-17 -1.560121e-16 3.368023e-17 76 77 78 79 80 -2.485340e-17 3.368023e-17 5.525310e-17 -4.450828e-17 -2.485340e-17 81 82 83 84 85 3.368023e-17 -1.560121e-16 3.368023e-17 4.154066e-17 6.119553e-17 86 87 88 89 90 -1.500697e-16 4.929783e-17 3.817550e-17 -3.420812e-17 -3.420812e-17 91 92 93 94 95 -6.692811e-18 4.411793e-17 7.681314e-17 -3.420812e-17 -3.938802e-17 96 97 98 99 100 -3.420812e-17 4.411793e-17 -3.420812e-17 4.929783e-17 -3.420812e-17 101 102 103 104 105 4.929783e-17 -3.420812e-17 -3.420812e-17 -3.420812e-17 -4.533045e-17 106 107 108 109 110 -3.420812e-17 -3.420812e-17 3.817550e-17 -3.420812e-17 4.929783e-17 111 112 113 114 115 6.569080e-17 -3.938802e-17 -4.015055e-17 3.817550e-17 4.929783e-17 116 117 118 119 120 -3.420812e-17 4.929783e-17 4.929783e-17 -3.420812e-17 -3.420812e-17 121 122 123 124 125 4.929783e-17 -3.420812e-17 3.817550e-17 -1.263524e-17 -3.420812e-17 126 127 128 129 130 -3.938802e-17 -6.692811e-18 -3.420812e-17 -3.420812e-17 -3.420812e-17 131 132 133 134 135 4.929783e-17 4.929783e-17 4.335540e-17 -3.420812e-17 -3.420812e-17 136 137 138 139 140 -3.420812e-17 7.087071e-17 6.569080e-17 -3.938802e-17 -3.420812e-17 141 142 143 144 145 -2.634769e-17 -4.533045e-17 4.929783e-17 -6.692811e-18 -6.692811e-18 146 147 148 149 150 -3.938802e-17 -4.533045e-17 -3.938802e-17 4.929783e-17 -6.692811e-18 151 152 153 154 -3.420812e-17 5.715826e-17 8.467357e-17 4.335540e-17 > postscript(file="/var/wessaorg/rcomp/tmp/69eb31355827917.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 1.320002e-15 NA 1 4.715360e-16 1.320002e-15 2 5.782818e-16 4.715360e-16 3 -1.172576e-15 5.782818e-16 4 3.368023e-17 -1.172576e-15 5 -1.225544e-16 3.368023e-17 6 3.368023e-17 -1.225544e-16 7 -5.236871e-17 3.368023e-17 8 3.368023e-17 -5.236871e-17 9 -1.500697e-16 3.368023e-17 10 -9.841814e-17 -1.500697e-16 11 3.368023e-17 -9.841814e-17 12 5.525310e-17 3.368023e-17 13 -9.841814e-17 5.525310e-17 14 5.525310e-17 -9.841814e-17 15 -3.079584e-17 5.525310e-17 16 -6.304240e-17 -3.079584e-17 17 -9.841814e-17 -6.304240e-17 18 3.368023e-17 -9.841814e-17 19 -1.699297e-17 3.368023e-17 20 -1.225544e-16 -1.699297e-17 21 -1.284968e-16 -1.225544e-16 22 6.119553e-17 -1.284968e-16 23 -1.225544e-16 6.119553e-17 24 -5.831114e-17 -1.225544e-16 25 5.525310e-17 -5.831114e-17 26 -1.500697e-16 5.525310e-17 27 2.773779e-17 -1.500697e-16 28 3.368023e-17 2.773779e-17 29 6.119553e-17 3.368023e-17 30 3.368023e-17 6.119553e-17 31 -1.500697e-16 3.368023e-17 32 -1.225544e-16 -1.500697e-16 33 -5.236871e-17 -1.225544e-16 34 3.368023e-17 -5.236871e-17 35 3.368023e-17 3.368023e-17 36 -7.684527e-17 3.368023e-17 37 2.773779e-17 -7.684527e-17 38 6.119553e-17 2.773779e-17 39 -2.485340e-17 6.119553e-17 40 6.905596e-17 -2.485340e-17 41 2.773779e-17 6.905596e-17 42 -1.225544e-16 2.773779e-17 43 -9.841814e-17 -1.225544e-16 44 6.119553e-17 -9.841814e-17 45 6.119553e-17 6.119553e-17 46 3.368023e-17 6.119553e-17 47 3.368023e-17 3.368023e-17 48 6.119553e-17 3.368023e-17 49 3.368023e-17 6.119553e-17 50 -5.831114e-17 3.368023e-17 51 -6.304240e-17 -5.831114e-17 52 3.368023e-17 -6.304240e-17 53 4.154066e-17 3.368023e-17 54 3.368023e-17 4.154066e-17 55 -5.831114e-17 3.368023e-17 56 5.525310e-17 -5.831114e-17 57 3.368023e-17 5.525310e-17 58 3.368023e-17 3.368023e-17 59 -6.304240e-17 3.368023e-17 60 -9.841814e-17 -6.304240e-17 61 5.525310e-17 -9.841814e-17 62 3.368023e-17 5.525310e-17 63 -9.841814e-17 3.368023e-17 64 3.368023e-17 -9.841814e-17 65 3.368023e-17 3.368023e-17 66 -1.699297e-17 3.368023e-17 67 -1.500697e-16 -1.699297e-17 68 3.368023e-17 -1.500697e-16 69 2.773779e-17 3.368023e-17 70 3.368023e-17 2.773779e-17 71 3.368023e-17 3.368023e-17 72 2.773779e-17 3.368023e-17 73 -1.560121e-16 2.773779e-17 74 3.368023e-17 -1.560121e-16 75 -2.485340e-17 3.368023e-17 76 3.368023e-17 -2.485340e-17 77 5.525310e-17 3.368023e-17 78 -4.450828e-17 5.525310e-17 79 -2.485340e-17 -4.450828e-17 80 3.368023e-17 -2.485340e-17 81 -1.560121e-16 3.368023e-17 82 3.368023e-17 -1.560121e-16 83 4.154066e-17 3.368023e-17 84 6.119553e-17 4.154066e-17 85 -1.500697e-16 6.119553e-17 86 4.929783e-17 -1.500697e-16 87 3.817550e-17 4.929783e-17 88 -3.420812e-17 3.817550e-17 89 -3.420812e-17 -3.420812e-17 90 -6.692811e-18 -3.420812e-17 91 4.411793e-17 -6.692811e-18 92 7.681314e-17 4.411793e-17 93 -3.420812e-17 7.681314e-17 94 -3.938802e-17 -3.420812e-17 95 -3.420812e-17 -3.938802e-17 96 4.411793e-17 -3.420812e-17 97 -3.420812e-17 4.411793e-17 98 4.929783e-17 -3.420812e-17 99 -3.420812e-17 4.929783e-17 100 4.929783e-17 -3.420812e-17 101 -3.420812e-17 4.929783e-17 102 -3.420812e-17 -3.420812e-17 103 -3.420812e-17 -3.420812e-17 104 -4.533045e-17 -3.420812e-17 105 -3.420812e-17 -4.533045e-17 106 -3.420812e-17 -3.420812e-17 107 3.817550e-17 -3.420812e-17 108 -3.420812e-17 3.817550e-17 109 4.929783e-17 -3.420812e-17 110 6.569080e-17 4.929783e-17 111 -3.938802e-17 6.569080e-17 112 -4.015055e-17 -3.938802e-17 113 3.817550e-17 -4.015055e-17 114 4.929783e-17 3.817550e-17 115 -3.420812e-17 4.929783e-17 116 4.929783e-17 -3.420812e-17 117 4.929783e-17 4.929783e-17 118 -3.420812e-17 4.929783e-17 119 -3.420812e-17 -3.420812e-17 120 4.929783e-17 -3.420812e-17 121 -3.420812e-17 4.929783e-17 122 3.817550e-17 -3.420812e-17 123 -1.263524e-17 3.817550e-17 124 -3.420812e-17 -1.263524e-17 125 -3.938802e-17 -3.420812e-17 126 -6.692811e-18 -3.938802e-17 127 -3.420812e-17 -6.692811e-18 128 -3.420812e-17 -3.420812e-17 129 -3.420812e-17 -3.420812e-17 130 4.929783e-17 -3.420812e-17 131 4.929783e-17 4.929783e-17 132 4.335540e-17 4.929783e-17 133 -3.420812e-17 4.335540e-17 134 -3.420812e-17 -3.420812e-17 135 -3.420812e-17 -3.420812e-17 136 7.087071e-17 -3.420812e-17 137 6.569080e-17 7.087071e-17 138 -3.938802e-17 6.569080e-17 139 -3.420812e-17 -3.938802e-17 140 -2.634769e-17 -3.420812e-17 141 -4.533045e-17 -2.634769e-17 142 4.929783e-17 -4.533045e-17 143 -6.692811e-18 4.929783e-17 144 -6.692811e-18 -6.692811e-18 145 -3.938802e-17 -6.692811e-18 146 -4.533045e-17 -3.938802e-17 147 -3.938802e-17 -4.533045e-17 148 4.929783e-17 -3.938802e-17 149 -6.692811e-18 4.929783e-17 150 -3.420812e-17 -6.692811e-18 151 5.715826e-17 -3.420812e-17 152 8.467357e-17 5.715826e-17 153 4.335540e-17 8.467357e-17 154 NA 4.335540e-17 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 4.715360e-16 1.320002e-15 [2,] 5.782818e-16 4.715360e-16 [3,] -1.172576e-15 5.782818e-16 [4,] 3.368023e-17 -1.172576e-15 [5,] -1.225544e-16 3.368023e-17 [6,] 3.368023e-17 -1.225544e-16 [7,] -5.236871e-17 3.368023e-17 [8,] 3.368023e-17 -5.236871e-17 [9,] -1.500697e-16 3.368023e-17 [10,] -9.841814e-17 -1.500697e-16 [11,] 3.368023e-17 -9.841814e-17 [12,] 5.525310e-17 3.368023e-17 [13,] -9.841814e-17 5.525310e-17 [14,] 5.525310e-17 -9.841814e-17 [15,] -3.079584e-17 5.525310e-17 [16,] -6.304240e-17 -3.079584e-17 [17,] -9.841814e-17 -6.304240e-17 [18,] 3.368023e-17 -9.841814e-17 [19,] -1.699297e-17 3.368023e-17 [20,] -1.225544e-16 -1.699297e-17 [21,] -1.284968e-16 -1.225544e-16 [22,] 6.119553e-17 -1.284968e-16 [23,] -1.225544e-16 6.119553e-17 [24,] -5.831114e-17 -1.225544e-16 [25,] 5.525310e-17 -5.831114e-17 [26,] -1.500697e-16 5.525310e-17 [27,] 2.773779e-17 -1.500697e-16 [28,] 3.368023e-17 2.773779e-17 [29,] 6.119553e-17 3.368023e-17 [30,] 3.368023e-17 6.119553e-17 [31,] -1.500697e-16 3.368023e-17 [32,] -1.225544e-16 -1.500697e-16 [33,] -5.236871e-17 -1.225544e-16 [34,] 3.368023e-17 -5.236871e-17 [35,] 3.368023e-17 3.368023e-17 [36,] -7.684527e-17 3.368023e-17 [37,] 2.773779e-17 -7.684527e-17 [38,] 6.119553e-17 2.773779e-17 [39,] -2.485340e-17 6.119553e-17 [40,] 6.905596e-17 -2.485340e-17 [41,] 2.773779e-17 6.905596e-17 [42,] -1.225544e-16 2.773779e-17 [43,] -9.841814e-17 -1.225544e-16 [44,] 6.119553e-17 -9.841814e-17 [45,] 6.119553e-17 6.119553e-17 [46,] 3.368023e-17 6.119553e-17 [47,] 3.368023e-17 3.368023e-17 [48,] 6.119553e-17 3.368023e-17 [49,] 3.368023e-17 6.119553e-17 [50,] -5.831114e-17 3.368023e-17 [51,] -6.304240e-17 -5.831114e-17 [52,] 3.368023e-17 -6.304240e-17 [53,] 4.154066e-17 3.368023e-17 [54,] 3.368023e-17 4.154066e-17 [55,] -5.831114e-17 3.368023e-17 [56,] 5.525310e-17 -5.831114e-17 [57,] 3.368023e-17 5.525310e-17 [58,] 3.368023e-17 3.368023e-17 [59,] -6.304240e-17 3.368023e-17 [60,] -9.841814e-17 -6.304240e-17 [61,] 5.525310e-17 -9.841814e-17 [62,] 3.368023e-17 5.525310e-17 [63,] -9.841814e-17 3.368023e-17 [64,] 3.368023e-17 -9.841814e-17 [65,] 3.368023e-17 3.368023e-17 [66,] -1.699297e-17 3.368023e-17 [67,] -1.500697e-16 -1.699297e-17 [68,] 3.368023e-17 -1.500697e-16 [69,] 2.773779e-17 3.368023e-17 [70,] 3.368023e-17 2.773779e-17 [71,] 3.368023e-17 3.368023e-17 [72,] 2.773779e-17 3.368023e-17 [73,] -1.560121e-16 2.773779e-17 [74,] 3.368023e-17 -1.560121e-16 [75,] -2.485340e-17 3.368023e-17 [76,] 3.368023e-17 -2.485340e-17 [77,] 5.525310e-17 3.368023e-17 [78,] -4.450828e-17 5.525310e-17 [79,] -2.485340e-17 -4.450828e-17 [80,] 3.368023e-17 -2.485340e-17 [81,] -1.560121e-16 3.368023e-17 [82,] 3.368023e-17 -1.560121e-16 [83,] 4.154066e-17 3.368023e-17 [84,] 6.119553e-17 4.154066e-17 [85,] -1.500697e-16 6.119553e-17 [86,] 4.929783e-17 -1.500697e-16 [87,] 3.817550e-17 4.929783e-17 [88,] -3.420812e-17 3.817550e-17 [89,] -3.420812e-17 -3.420812e-17 [90,] -6.692811e-18 -3.420812e-17 [91,] 4.411793e-17 -6.692811e-18 [92,] 7.681314e-17 4.411793e-17 [93,] -3.420812e-17 7.681314e-17 [94,] -3.938802e-17 -3.420812e-17 [95,] -3.420812e-17 -3.938802e-17 [96,] 4.411793e-17 -3.420812e-17 [97,] -3.420812e-17 4.411793e-17 [98,] 4.929783e-17 -3.420812e-17 [99,] -3.420812e-17 4.929783e-17 [100,] 4.929783e-17 -3.420812e-17 [101,] -3.420812e-17 4.929783e-17 [102,] -3.420812e-17 -3.420812e-17 [103,] -3.420812e-17 -3.420812e-17 [104,] -4.533045e-17 -3.420812e-17 [105,] -3.420812e-17 -4.533045e-17 [106,] -3.420812e-17 -3.420812e-17 [107,] 3.817550e-17 -3.420812e-17 [108,] -3.420812e-17 3.817550e-17 [109,] 4.929783e-17 -3.420812e-17 [110,] 6.569080e-17 4.929783e-17 [111,] -3.938802e-17 6.569080e-17 [112,] -4.015055e-17 -3.938802e-17 [113,] 3.817550e-17 -4.015055e-17 [114,] 4.929783e-17 3.817550e-17 [115,] -3.420812e-17 4.929783e-17 [116,] 4.929783e-17 -3.420812e-17 [117,] 4.929783e-17 4.929783e-17 [118,] -3.420812e-17 4.929783e-17 [119,] -3.420812e-17 -3.420812e-17 [120,] 4.929783e-17 -3.420812e-17 [121,] -3.420812e-17 4.929783e-17 [122,] 3.817550e-17 -3.420812e-17 [123,] -1.263524e-17 3.817550e-17 [124,] -3.420812e-17 -1.263524e-17 [125,] -3.938802e-17 -3.420812e-17 [126,] -6.692811e-18 -3.938802e-17 [127,] -3.420812e-17 -6.692811e-18 [128,] -3.420812e-17 -3.420812e-17 [129,] -3.420812e-17 -3.420812e-17 [130,] 4.929783e-17 -3.420812e-17 [131,] 4.929783e-17 4.929783e-17 [132,] 4.335540e-17 4.929783e-17 [133,] -3.420812e-17 4.335540e-17 [134,] -3.420812e-17 -3.420812e-17 [135,] -3.420812e-17 -3.420812e-17 [136,] 7.087071e-17 -3.420812e-17 [137,] 6.569080e-17 7.087071e-17 [138,] -3.938802e-17 6.569080e-17 [139,] -3.420812e-17 -3.938802e-17 [140,] -2.634769e-17 -3.420812e-17 [141,] -4.533045e-17 -2.634769e-17 [142,] 4.929783e-17 -4.533045e-17 [143,] -6.692811e-18 4.929783e-17 [144,] -6.692811e-18 -6.692811e-18 [145,] -3.938802e-17 -6.692811e-18 [146,] -4.533045e-17 -3.938802e-17 [147,] -3.938802e-17 -4.533045e-17 [148,] 4.929783e-17 -3.938802e-17 [149,] -6.692811e-18 4.929783e-17 [150,] -3.420812e-17 -6.692811e-18 [151,] 5.715826e-17 -3.420812e-17 [152,] 8.467357e-17 5.715826e-17 [153,] 4.335540e-17 8.467357e-17 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 4.715360e-16 1.320002e-15 2 5.782818e-16 4.715360e-16 3 -1.172576e-15 5.782818e-16 4 3.368023e-17 -1.172576e-15 5 -1.225544e-16 3.368023e-17 6 3.368023e-17 -1.225544e-16 7 -5.236871e-17 3.368023e-17 8 3.368023e-17 -5.236871e-17 9 -1.500697e-16 3.368023e-17 10 -9.841814e-17 -1.500697e-16 11 3.368023e-17 -9.841814e-17 12 5.525310e-17 3.368023e-17 13 -9.841814e-17 5.525310e-17 14 5.525310e-17 -9.841814e-17 15 -3.079584e-17 5.525310e-17 16 -6.304240e-17 -3.079584e-17 17 -9.841814e-17 -6.304240e-17 18 3.368023e-17 -9.841814e-17 19 -1.699297e-17 3.368023e-17 20 -1.225544e-16 -1.699297e-17 21 -1.284968e-16 -1.225544e-16 22 6.119553e-17 -1.284968e-16 23 -1.225544e-16 6.119553e-17 24 -5.831114e-17 -1.225544e-16 25 5.525310e-17 -5.831114e-17 26 -1.500697e-16 5.525310e-17 27 2.773779e-17 -1.500697e-16 28 3.368023e-17 2.773779e-17 29 6.119553e-17 3.368023e-17 30 3.368023e-17 6.119553e-17 31 -1.500697e-16 3.368023e-17 32 -1.225544e-16 -1.500697e-16 33 -5.236871e-17 -1.225544e-16 34 3.368023e-17 -5.236871e-17 35 3.368023e-17 3.368023e-17 36 -7.684527e-17 3.368023e-17 37 2.773779e-17 -7.684527e-17 38 6.119553e-17 2.773779e-17 39 -2.485340e-17 6.119553e-17 40 6.905596e-17 -2.485340e-17 41 2.773779e-17 6.905596e-17 42 -1.225544e-16 2.773779e-17 43 -9.841814e-17 -1.225544e-16 44 6.119553e-17 -9.841814e-17 45 6.119553e-17 6.119553e-17 46 3.368023e-17 6.119553e-17 47 3.368023e-17 3.368023e-17 48 6.119553e-17 3.368023e-17 49 3.368023e-17 6.119553e-17 50 -5.831114e-17 3.368023e-17 51 -6.304240e-17 -5.831114e-17 52 3.368023e-17 -6.304240e-17 53 4.154066e-17 3.368023e-17 54 3.368023e-17 4.154066e-17 55 -5.831114e-17 3.368023e-17 56 5.525310e-17 -5.831114e-17 57 3.368023e-17 5.525310e-17 58 3.368023e-17 3.368023e-17 59 -6.304240e-17 3.368023e-17 60 -9.841814e-17 -6.304240e-17 61 5.525310e-17 -9.841814e-17 62 3.368023e-17 5.525310e-17 63 -9.841814e-17 3.368023e-17 64 3.368023e-17 -9.841814e-17 65 3.368023e-17 3.368023e-17 66 -1.699297e-17 3.368023e-17 67 -1.500697e-16 -1.699297e-17 68 3.368023e-17 -1.500697e-16 69 2.773779e-17 3.368023e-17 70 3.368023e-17 2.773779e-17 71 3.368023e-17 3.368023e-17 72 2.773779e-17 3.368023e-17 73 -1.560121e-16 2.773779e-17 74 3.368023e-17 -1.560121e-16 75 -2.485340e-17 3.368023e-17 76 3.368023e-17 -2.485340e-17 77 5.525310e-17 3.368023e-17 78 -4.450828e-17 5.525310e-17 79 -2.485340e-17 -4.450828e-17 80 3.368023e-17 -2.485340e-17 81 -1.560121e-16 3.368023e-17 82 3.368023e-17 -1.560121e-16 83 4.154066e-17 3.368023e-17 84 6.119553e-17 4.154066e-17 85 -1.500697e-16 6.119553e-17 86 4.929783e-17 -1.500697e-16 87 3.817550e-17 4.929783e-17 88 -3.420812e-17 3.817550e-17 89 -3.420812e-17 -3.420812e-17 90 -6.692811e-18 -3.420812e-17 91 4.411793e-17 -6.692811e-18 92 7.681314e-17 4.411793e-17 93 -3.420812e-17 7.681314e-17 94 -3.938802e-17 -3.420812e-17 95 -3.420812e-17 -3.938802e-17 96 4.411793e-17 -3.420812e-17 97 -3.420812e-17 4.411793e-17 98 4.929783e-17 -3.420812e-17 99 -3.420812e-17 4.929783e-17 100 4.929783e-17 -3.420812e-17 101 -3.420812e-17 4.929783e-17 102 -3.420812e-17 -3.420812e-17 103 -3.420812e-17 -3.420812e-17 104 -4.533045e-17 -3.420812e-17 105 -3.420812e-17 -4.533045e-17 106 -3.420812e-17 -3.420812e-17 107 3.817550e-17 -3.420812e-17 108 -3.420812e-17 3.817550e-17 109 4.929783e-17 -3.420812e-17 110 6.569080e-17 4.929783e-17 111 -3.938802e-17 6.569080e-17 112 -4.015055e-17 -3.938802e-17 113 3.817550e-17 -4.015055e-17 114 4.929783e-17 3.817550e-17 115 -3.420812e-17 4.929783e-17 116 4.929783e-17 -3.420812e-17 117 4.929783e-17 4.929783e-17 118 -3.420812e-17 4.929783e-17 119 -3.420812e-17 -3.420812e-17 120 4.929783e-17 -3.420812e-17 121 -3.420812e-17 4.929783e-17 122 3.817550e-17 -3.420812e-17 123 -1.263524e-17 3.817550e-17 124 -3.420812e-17 -1.263524e-17 125 -3.938802e-17 -3.420812e-17 126 -6.692811e-18 -3.938802e-17 127 -3.420812e-17 -6.692811e-18 128 -3.420812e-17 -3.420812e-17 129 -3.420812e-17 -3.420812e-17 130 4.929783e-17 -3.420812e-17 131 4.929783e-17 4.929783e-17 132 4.335540e-17 4.929783e-17 133 -3.420812e-17 4.335540e-17 134 -3.420812e-17 -3.420812e-17 135 -3.420812e-17 -3.420812e-17 136 7.087071e-17 -3.420812e-17 137 6.569080e-17 7.087071e-17 138 -3.938802e-17 6.569080e-17 139 -3.420812e-17 -3.938802e-17 140 -2.634769e-17 -3.420812e-17 141 -4.533045e-17 -2.634769e-17 142 4.929783e-17 -4.533045e-17 143 -6.692811e-18 4.929783e-17 144 -6.692811e-18 -6.692811e-18 145 -3.938802e-17 -6.692811e-18 146 -4.533045e-17 -3.938802e-17 147 -3.938802e-17 -4.533045e-17 148 4.929783e-17 -3.938802e-17 149 -6.692811e-18 4.929783e-17 150 -3.420812e-17 -6.692811e-18 151 5.715826e-17 -3.420812e-17 152 8.467357e-17 5.715826e-17 153 4.335540e-17 8.467357e-17 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/71qny1355827917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8mgki1355827917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9f8t71355827917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10x2zp1355827917.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } Error: subscript out of bounds Execution halted