R version 2.15.2 (2012-10-26) -- "Trick or Treat" Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i686-pc-linux-gnu (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(4 + ,1 + ,1 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,4 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,4 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,4 + ,0 + ,1 + ,1 + ,0 + ,1 + ,1 + ,4 + ,1 + ,1 + ,1 + ,1 + ,1 + ,0 + ,4 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,4 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,1 + ,1 + ,1 + ,1 + ,1 + ,4 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,4 + ,1 + ,0 + ,1 + ,0 + ,1 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,1 + ,1 + ,4 + ,1 + ,0 + ,0 + ,0 + ,1 + ,1 + ,4 + ,0 + ,1 + ,1 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,4 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,4 + ,0 + ,0 + 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,0 + ,1 + ,2 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,4 + ,0 + ,0 + ,1 + ,1 + ,2 + ,0 + ,4 + ,0 + ,0 + ,1 + ,0 + ,2 + ,0 + ,3 + ,0 + ,0 + ,0 + ,1 + ,2 + ,0 + ,3 + ,1 + ,0 + ,0 + ,0 + ,2 + ,0 + ,3 + ,0 + ,0 + ,0 + ,0 + ,2 + ,1 + ,4 + ,0 + ,0 + ,0 + ,0 + ,2 + ,0 + ,4 + ,0 + ,0 + ,1 + ,1 + ,2 + ,0 + ,4 + ,0 + ,0 + ,0 + ,1 + ,2 + ,1 + ,4 + ,1 + ,1 + ,0 + ,0 + ,2 + ,1 + ,4 + ,1 + ,1 + ,1 + ,0 + ,2 + ,1 + ,4 + ,1 + ,0 + ,0 + ,0) + ,dim=c(7 + ,154) + ,dimnames=list(c('Weeks' + ,'UseLimit' + ,'Group' + ,'Used' + ,'CorrectAnalysis' + ,'Useful' + ,'Outcome') + ,1:154)) > y <- array(NA,dim=c(7,154),dimnames=list(c('Weeks','UseLimit','Group','Used','CorrectAnalysis','Useful','Outcome'),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 Weeks UseLimit Group Used CorrectAnalysis Useful Outcome 1 4 1 1 0 0 0 1 2 4 0 0 0 0 0 0 3 4 0 0 0 0 0 0 4 4 0 0 0 0 0 0 5 4 0 0 0 0 0 0 6 4 1 0 0 0 1 1 7 4 0 0 0 0 0 0 8 4 0 1 0 0 0 0 9 4 0 0 0 0 0 1 10 4 1 0 0 0 0 0 11 4 1 1 0 0 0 0 12 4 0 0 0 0 0 0 13 4 0 0 1 0 1 0 14 4 1 1 0 0 0 0 15 4 0 0 1 0 1 1 16 4 0 1 1 0 1 1 17 4 1 1 1 1 1 0 18 4 1 1 0 0 0 0 19 4 0 0 0 0 0 1 20 4 0 1 1 1 1 1 21 4 1 0 0 0 1 0 22 4 1 0 1 0 1 1 23 4 0 0 0 0 1 1 24 4 1 0 0 0 1 1 25 4 0 1 1 0 0 1 26 4 0 0 1 0 1 0 27 4 1 0 0 0 0 1 28 4 0 0 1 0 0 0 29 4 0 0 0 0 0 1 30 4 0 0 0 0 1 0 31 4 0 0 0 0 0 0 32 4 1 0 0 0 0 0 33 4 1 0 0 0 1 0 34 4 0 1 0 0 0 1 35 4 0 0 0 0 0 0 36 4 0 0 0 0 0 0 37 4 1 1 1 0 1 0 38 4 0 0 1 0 0 1 39 4 0 0 0 0 1 1 40 4 0 1 0 0 1 0 41 4 0 0 1 1 1 1 42 4 0 0 1 0 0 1 43 4 1 0 0 0 1 1 44 4 1 1 0 0 0 0 45 4 0 0 0 0 1 0 46 4 0 0 0 0 1 1 47 4 0 0 0 0 0 0 48 4 0 0 0 0 0 1 49 4 0 0 0 0 1 1 50 4 0 0 0 0 0 0 51 4 0 1 1 0 0 0 52 4 1 1 1 1 1 0 53 4 0 0 0 0 0 1 54 4 0 0 1 1 0 0 55 4 0 0 0 0 0 0 56 4 0 1 1 0 0 1 57 4 0 0 1 0 1 1 58 4 0 0 0 0 0 1 59 4 0 0 0 0 0 1 60 4 1 1 1 1 1 1 61 4 1 1 0 0 0 1 62 4 0 0 1 0 1 0 63 4 0 0 0 0 0 0 64 4 1 1 0 0 0 1 65 4 0 0 0 0 0 0 66 4 0 0 0 0 0 0 67 4 0 1 1 1 1 0 68 4 1 0 0 0 0 0 69 4 0 0 0 0 0 1 70 4 0 0 1 0 0 0 71 4 0 0 0 0 0 0 72 4 0 0 0 0 0 1 73 4 0 0 1 0 0 1 74 4 1 0 1 0 0 0 75 4 0 0 0 0 0 1 76 4 0 1 0 0 1 1 77 4 0 0 0 0 0 1 78 4 0 0 1 0 1 1 79 4 0 1 1 1 0 1 80 4 0 1 0 0 1 0 81 4 0 0 0 0 0 0 82 4 1 0 1 0 0 1 83 4 0 0 0 0 0 0 84 4 0 0 1 1 0 0 85 4 0 0 0 0 1 1 86 4 1 0 0 0 0 0 87 2 1 4 0 0 0 1 88 2 1 3 1 0 0 1 89 2 0 4 0 0 0 0 90 2 0 4 0 0 0 1 91 2 0 4 0 0 1 0 92 2 1 3 0 0 0 0 93 2 1 4 0 0 1 0 94 2 0 4 0 0 0 0 95 2 0 3 0 0 0 0 96 2 0 4 0 0 0 1 97 2 1 3 0 0 0 0 98 2 0 4 0 0 0 0 99 2 1 4 0 0 0 0 100 2 0 4 0 0 0 1 101 2 1 4 0 0 0 1 102 2 0 4 0 0 0 0 103 2 0 4 0 0 0 0 104 2 0 4 0 0 0 0 105 2 0 3 1 0 0 0 106 2 0 4 0 0 0 0 107 2 0 4 0 0 0 0 108 2 1 3 1 0 0 0 109 2 0 4 0 0 0 0 110 2 1 4 0 0 0 0 111 2 1 3 1 0 1 0 112 2 0 3 0 0 0 0 113 2 0 4 1 0 0 0 114 2 1 3 1 0 0 0 115 2 1 4 0 0 0 0 116 2 0 4 0 0 0 0 117 2 1 4 0 0 0 1 118 2 1 4 0 0 0 0 119 2 0 4 0 0 0 0 120 2 0 4 0 0 0 1 121 2 1 4 0 0 0 0 122 2 0 4 0 0 0 0 123 2 1 3 1 0 0 0 124 2 0 4 1 0 1 1 125 2 0 4 0 0 0 1 126 2 0 3 0 0 0 0 127 2 0 4 0 0 1 0 128 2 0 4 0 0 0 1 129 2 0 4 0 0 0 0 130 2 0 4 0 0 0 1 131 2 1 4 0 0 0 0 132 2 1 4 0 0 0 1 133 2 1 4 1 0 0 0 134 2 0 4 0 0 0 0 135 2 0 4 0 0 0 0 136 2 0 4 0 0 0 0 137 2 1 4 1 0 1 1 138 2 1 3 1 0 1 1 139 2 0 3 0 0 0 0 140 2 0 4 0 0 0 0 141 2 0 4 1 1 0 1 142 2 0 3 1 0 0 1 143 2 1 4 0 0 0 0 144 2 0 4 0 0 1 1 145 2 0 4 0 0 1 0 146 2 0 3 0 0 0 1 147 2 0 3 1 0 0 0 148 2 0 3 0 0 0 0 149 2 1 4 0 0 0 0 150 2 0 4 0 0 1 1 151 2 0 4 0 0 0 1 152 2 1 4 1 1 0 0 153 2 1 4 1 1 1 0 154 2 1 4 1 0 0 0 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) UseLimit Group Used 4.04968 0.03593 -0.53670 -0.11233 CorrectAnalysis Useful Outcome 0.29846 0.06121 0.04456 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.48415 -0.09424 0.00071 0.09710 0.59935 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 4.04968 0.03749 108.031 < 2e-16 *** UseLimit 0.03593 0.04121 0.872 0.384674 Group -0.53670 0.01097 -48.942 < 2e-16 *** Used -0.11233 0.04784 -2.348 0.020200 * CorrectAnalysis 0.29846 0.07968 3.746 0.000258 *** Useful 0.06121 0.04571 1.339 0.182629 Outcome 0.04456 0.03974 1.121 0.264052 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.2347 on 147 degrees of freedom Multiple R-squared: 0.9467, Adjusted R-squared: 0.9445 F-statistic: 435 on 6 and 147 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,] 6.466953e-46 1.293391e-45 1.000000e+00 [2,] 1.392322e-63 2.784645e-63 1.000000e+00 [3,] 5.546166e-74 1.109233e-73 1.000000e+00 [4,] 3.904877e-101 7.809754e-101 1.000000e+00 [5,] 1.990581e-102 3.981161e-102 1.000000e+00 [6,] 7.961106e-117 1.592221e-116 1.000000e+00 [7,] 0.000000e+00 0.000000e+00 1.000000e+00 [8,] 2.102188e-157 4.204377e-157 1.000000e+00 [9,] 9.543417e-162 1.908683e-161 1.000000e+00 [10,] 5.894451e-175 1.178890e-174 1.000000e+00 [11,] 4.243545e-199 8.487089e-199 1.000000e+00 [12,] 3.681759e-232 7.363519e-232 1.000000e+00 [13,] 1.348304e-221 2.696608e-221 1.000000e+00 [14,] 2.445316e-232 4.890632e-232 1.000000e+00 [15,] 4.928363e-250 9.856725e-250 1.000000e+00 [16,] 9.658100e-268 1.931620e-267 1.000000e+00 [17,] 2.124634e-309 4.249267e-309 1.000000e+00 [18,] 1.138539e-295 2.277079e-295 1.000000e+00 [19,] 3.058361e-305 6.116721e-305 1.000000e+00 [20,] 0.000000e+00 0.000000e+00 1.000000e+00 [21,] 0.000000e+00 0.000000e+00 1.000000e+00 [22,] 0.000000e+00 0.000000e+00 1.000000e+00 [23,] 0.000000e+00 0.000000e+00 1.000000e+00 [24,] 0.000000e+00 0.000000e+00 1.000000e+00 [25,] 0.000000e+00 0.000000e+00 1.000000e+00 [26,] 0.000000e+00 0.000000e+00 1.000000e+00 [27,] 0.000000e+00 0.000000e+00 1.000000e+00 [28,] 0.000000e+00 0.000000e+00 1.000000e+00 [29,] 0.000000e+00 0.000000e+00 1.000000e+00 [30,] 0.000000e+00 0.000000e+00 1.000000e+00 [31,] 0.000000e+00 0.000000e+00 1.000000e+00 [32,] 0.000000e+00 0.000000e+00 1.000000e+00 [33,] 0.000000e+00 0.000000e+00 1.000000e+00 [34,] 0.000000e+00 0.000000e+00 1.000000e+00 [35,] 0.000000e+00 0.000000e+00 1.000000e+00 [36,] 0.000000e+00 0.000000e+00 1.000000e+00 [37,] 0.000000e+00 0.000000e+00 1.000000e+00 [38,] 0.000000e+00 0.000000e+00 1.000000e+00 [39,] 0.000000e+00 0.000000e+00 1.000000e+00 [40,] 0.000000e+00 0.000000e+00 1.000000e+00 [41,] 0.000000e+00 0.000000e+00 1.000000e+00 [42,] 0.000000e+00 0.000000e+00 1.000000e+00 [43,] 0.000000e+00 0.000000e+00 1.000000e+00 [44,] 0.000000e+00 0.000000e+00 1.000000e+00 [45,] 0.000000e+00 0.000000e+00 1.000000e+00 [46,] 0.000000e+00 0.000000e+00 1.000000e+00 [47,] 0.000000e+00 0.000000e+00 1.000000e+00 [48,] 0.000000e+00 0.000000e+00 1.000000e+00 [49,] 0.000000e+00 0.000000e+00 1.000000e+00 [50,] 0.000000e+00 0.000000e+00 1.000000e+00 [51,] 0.000000e+00 0.000000e+00 1.000000e+00 [52,] 0.000000e+00 0.000000e+00 1.000000e+00 [53,] 0.000000e+00 0.000000e+00 1.000000e+00 [54,] 0.000000e+00 0.000000e+00 1.000000e+00 [55,] 0.000000e+00 0.000000e+00 1.000000e+00 [56,] 0.000000e+00 0.000000e+00 1.000000e+00 [57,] 0.000000e+00 0.000000e+00 1.000000e+00 [58,] 0.000000e+00 0.000000e+00 1.000000e+00 [59,] 0.000000e+00 0.000000e+00 1.000000e+00 [60,] 0.000000e+00 0.000000e+00 1.000000e+00 [61,] 0.000000e+00 0.000000e+00 1.000000e+00 [62,] 0.000000e+00 0.000000e+00 1.000000e+00 [63,] 0.000000e+00 0.000000e+00 1.000000e+00 [64,] 0.000000e+00 0.000000e+00 1.000000e+00 [65,] 0.000000e+00 0.000000e+00 1.000000e+00 [66,] 0.000000e+00 0.000000e+00 1.000000e+00 [67,] 0.000000e+00 0.000000e+00 1.000000e+00 [68,] 0.000000e+00 0.000000e+00 1.000000e+00 [69,] 0.000000e+00 0.000000e+00 1.000000e+00 [70,] 0.000000e+00 0.000000e+00 1.000000e+00 [71,] 0.000000e+00 0.000000e+00 1.000000e+00 [72,] 0.000000e+00 0.000000e+00 1.000000e+00 [73,] 0.000000e+00 0.000000e+00 1.000000e+00 [74,] 0.000000e+00 0.000000e+00 1.000000e+00 [75,] 0.000000e+00 0.000000e+00 1.000000e+00 [76,] 0.000000e+00 0.000000e+00 1.000000e+00 [77,] 1.000000e+00 8.293611e-19 4.146805e-19 [78,] 1.000000e+00 0.000000e+00 0.000000e+00 [79,] 1.000000e+00 0.000000e+00 0.000000e+00 [80,] 1.000000e+00 0.000000e+00 0.000000e+00 [81,] 1.000000e+00 0.000000e+00 0.000000e+00 [82,] 1.000000e+00 0.000000e+00 0.000000e+00 [83,] 1.000000e+00 0.000000e+00 0.000000e+00 [84,] 1.000000e+00 0.000000e+00 0.000000e+00 [85,] 1.000000e+00 0.000000e+00 0.000000e+00 [86,] 1.000000e+00 0.000000e+00 0.000000e+00 [87,] 1.000000e+00 0.000000e+00 0.000000e+00 [88,] 1.000000e+00 0.000000e+00 0.000000e+00 [89,] 1.000000e+00 0.000000e+00 0.000000e+00 [90,] 1.000000e+00 0.000000e+00 0.000000e+00 [91,] 1.000000e+00 0.000000e+00 0.000000e+00 [92,] 1.000000e+00 0.000000e+00 0.000000e+00 [93,] 1.000000e+00 0.000000e+00 0.000000e+00 [94,] 1.000000e+00 0.000000e+00 0.000000e+00 [95,] 1.000000e+00 0.000000e+00 0.000000e+00 [96,] 1.000000e+00 0.000000e+00 0.000000e+00 [97,] 1.000000e+00 0.000000e+00 0.000000e+00 [98,] 1.000000e+00 0.000000e+00 0.000000e+00 [99,] 1.000000e+00 0.000000e+00 0.000000e+00 [100,] 1.000000e+00 0.000000e+00 0.000000e+00 [101,] 1.000000e+00 0.000000e+00 0.000000e+00 [102,] 1.000000e+00 0.000000e+00 0.000000e+00 [103,] 1.000000e+00 0.000000e+00 0.000000e+00 [104,] 1.000000e+00 0.000000e+00 0.000000e+00 [105,] 1.000000e+00 0.000000e+00 0.000000e+00 [106,] 1.000000e+00 0.000000e+00 0.000000e+00 [107,] 1.000000e+00 0.000000e+00 0.000000e+00 [108,] 1.000000e+00 0.000000e+00 0.000000e+00 [109,] 1.000000e+00 0.000000e+00 0.000000e+00 [110,] 1.000000e+00 0.000000e+00 0.000000e+00 [111,] 1.000000e+00 0.000000e+00 0.000000e+00 [112,] 1.000000e+00 0.000000e+00 0.000000e+00 [113,] 1.000000e+00 0.000000e+00 0.000000e+00 [114,] 1.000000e+00 0.000000e+00 0.000000e+00 [115,] 1.000000e+00 0.000000e+00 0.000000e+00 [116,] 1.000000e+00 0.000000e+00 0.000000e+00 [117,] 1.000000e+00 1.192760e-311 5.963802e-312 [118,] 1.000000e+00 3.134427e-301 1.567213e-301 [119,] 1.000000e+00 2.546455e-314 1.273227e-314 [120,] 1.000000e+00 1.497102e-272 7.485510e-273 [121,] 1.000000e+00 3.946645e-254 1.973323e-254 [122,] 1.000000e+00 3.687038e-237 1.843519e-237 [123,] 1.000000e+00 1.493755e-225 7.468777e-226 [124,] 1.000000e+00 3.890227e-235 1.945113e-235 [125,] 1.000000e+00 8.575202e-202 4.287601e-202 [126,] 1.000000e+00 1.668463e-177 8.342315e-178 [127,] 1.000000e+00 1.886051e-164 9.430253e-165 [128,] 1.000000e+00 5.077209e-161 2.538605e-161 [129,] 1.000000e+00 0.000000e+00 0.000000e+00 [130,] 1.000000e+00 1.080744e-118 5.403718e-119 [131,] 1.000000e+00 1.223186e-104 6.115929e-105 [132,] 1.000000e+00 3.060129e-102 1.530065e-102 [133,] 1.000000e+00 1.298145e-74 6.490725e-75 [134,] 1.000000e+00 6.144759e-64 3.072379e-64 [135,] 1.000000e+00 2.691776e-46 1.345888e-46 > postscript(file="/var/wessaorg/rcomp/tmp/1t4z11355679607.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2fa4o1355679607.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3adz11355679607.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4apqi1355679607.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5g6ci1355679607.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 4.065242e-01 -4.968117e-02 -4.968117e-02 -4.968117e-02 -4.968117e-02 6 7 8 9 10 -1.913788e-01 -4.968117e-02 4.870149e-01 -9.424111e-02 -8.561185e-02 11 12 13 14 15 4.510842e-01 -4.968117e-02 1.446221e-03 4.510842e-01 -4.311372e-02 16 17 18 19 20 4.935823e-01 2.037562e-01 4.510842e-01 -9.424111e-02 1.951269e-01 21 22 23 24 25 -1.468188e-01 -7.904441e-02 -1.554481e-01 -1.913788e-01 5.547893e-01 26 27 28 29 30 1.446221e-03 -1.301718e-01 6.265319e-02 -9.424111e-02 -1.108881e-01 31 32 33 34 35 -4.968117e-02 -8.561185e-02 -1.468188e-01 4.424549e-01 -4.968117e-02 36 37 38 39 40 -4.968117e-02 5.022116e-01 1.809325e-02 -1.554481e-01 4.258079e-01 41 42 43 44 45 -3.415691e-01 1.809325e-02 -1.913788e-01 4.510842e-01 -1.108881e-01 46 47 48 49 50 -1.554481e-01 -4.968117e-02 -9.424111e-02 -1.554481e-01 -4.968117e-02 51 52 53 54 55 5.993492e-01 2.037562e-01 -9.424111e-02 -2.358022e-01 -4.968117e-02 56 57 58 59 60 5.547893e-01 -4.311372e-02 -9.424111e-02 -9.424111e-02 1.591962e-01 61 62 63 64 65 4.065242e-01 1.446221e-03 -4.968117e-02 4.065242e-01 -4.968117e-02 66 67 68 69 70 -4.968117e-02 2.396868e-01 -8.561185e-02 -9.424111e-02 6.265319e-02 71 72 73 74 75 -4.968117e-02 -9.424111e-02 1.809325e-02 2.672251e-02 -9.424111e-02 76 77 78 79 80 3.812479e-01 -9.424111e-02 -4.311372e-02 2.563339e-01 4.258079e-01 81 82 83 84 85 -4.968117e-02 -1.783744e-02 -4.968117e-02 -2.358022e-01 -1.554481e-01 86 87 88 89 90 -8.561185e-02 1.661231e-02 -4.077494e-01 9.710293e-02 5.254299e-02 91 92 93 94 95 3.589596e-02 -4.755238e-01 -3.471892e-05 9.710293e-02 -4.395931e-01 96 97 98 99 100 5.254299e-02 -4.755238e-01 9.710293e-02 6.117225e-02 5.254299e-02 101 102 103 104 105 1.661231e-02 9.710293e-02 9.710293e-02 9.710293e-02 -3.272587e-01 106 107 108 109 110 9.710293e-02 9.710293e-02 -3.631894e-01 9.710293e-02 6.117225e-02 111 112 113 114 115 -4.243964e-01 -4.395931e-01 2.094373e-01 -3.631894e-01 6.117225e-02 116 117 118 119 120 9.710293e-02 1.661231e-02 6.117225e-02 9.710293e-02 5.254299e-02 121 122 123 124 125 6.117225e-02 9.710293e-02 -3.631894e-01 1.036704e-01 5.254299e-02 126 127 128 129 130 -4.395931e-01 3.589596e-02 5.254299e-02 9.710293e-02 5.254299e-02 131 132 133 134 135 6.117225e-02 1.661231e-02 1.735066e-01 9.710293e-02 9.710293e-02 136 137 138 139 140 9.710293e-02 6.773969e-02 -4.689563e-01 -4.395931e-01 9.710293e-02 141 142 143 144 145 -1.335781e-01 -3.718187e-01 6.117225e-02 -8.663981e-03 3.589596e-02 146 147 148 149 150 -4.841530e-01 -3.272587e-01 -4.395931e-01 6.117225e-02 -8.663981e-03 151 152 153 154 5.254299e-02 -1.249488e-01 -1.861558e-01 1.735066e-01 > postscript(file="/var/wessaorg/rcomp/tmp/6a9wq1355679607.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 4.065242e-01 NA 1 -4.968117e-02 4.065242e-01 2 -4.968117e-02 -4.968117e-02 3 -4.968117e-02 -4.968117e-02 4 -4.968117e-02 -4.968117e-02 5 -1.913788e-01 -4.968117e-02 6 -4.968117e-02 -1.913788e-01 7 4.870149e-01 -4.968117e-02 8 -9.424111e-02 4.870149e-01 9 -8.561185e-02 -9.424111e-02 10 4.510842e-01 -8.561185e-02 11 -4.968117e-02 4.510842e-01 12 1.446221e-03 -4.968117e-02 13 4.510842e-01 1.446221e-03 14 -4.311372e-02 4.510842e-01 15 4.935823e-01 -4.311372e-02 16 2.037562e-01 4.935823e-01 17 4.510842e-01 2.037562e-01 18 -9.424111e-02 4.510842e-01 19 1.951269e-01 -9.424111e-02 20 -1.468188e-01 1.951269e-01 21 -7.904441e-02 -1.468188e-01 22 -1.554481e-01 -7.904441e-02 23 -1.913788e-01 -1.554481e-01 24 5.547893e-01 -1.913788e-01 25 1.446221e-03 5.547893e-01 26 -1.301718e-01 1.446221e-03 27 6.265319e-02 -1.301718e-01 28 -9.424111e-02 6.265319e-02 29 -1.108881e-01 -9.424111e-02 30 -4.968117e-02 -1.108881e-01 31 -8.561185e-02 -4.968117e-02 32 -1.468188e-01 -8.561185e-02 33 4.424549e-01 -1.468188e-01 34 -4.968117e-02 4.424549e-01 35 -4.968117e-02 -4.968117e-02 36 5.022116e-01 -4.968117e-02 37 1.809325e-02 5.022116e-01 38 -1.554481e-01 1.809325e-02 39 4.258079e-01 -1.554481e-01 40 -3.415691e-01 4.258079e-01 41 1.809325e-02 -3.415691e-01 42 -1.913788e-01 1.809325e-02 43 4.510842e-01 -1.913788e-01 44 -1.108881e-01 4.510842e-01 45 -1.554481e-01 -1.108881e-01 46 -4.968117e-02 -1.554481e-01 47 -9.424111e-02 -4.968117e-02 48 -1.554481e-01 -9.424111e-02 49 -4.968117e-02 -1.554481e-01 50 5.993492e-01 -4.968117e-02 51 2.037562e-01 5.993492e-01 52 -9.424111e-02 2.037562e-01 53 -2.358022e-01 -9.424111e-02 54 -4.968117e-02 -2.358022e-01 55 5.547893e-01 -4.968117e-02 56 -4.311372e-02 5.547893e-01 57 -9.424111e-02 -4.311372e-02 58 -9.424111e-02 -9.424111e-02 59 1.591962e-01 -9.424111e-02 60 4.065242e-01 1.591962e-01 61 1.446221e-03 4.065242e-01 62 -4.968117e-02 1.446221e-03 63 4.065242e-01 -4.968117e-02 64 -4.968117e-02 4.065242e-01 65 -4.968117e-02 -4.968117e-02 66 2.396868e-01 -4.968117e-02 67 -8.561185e-02 2.396868e-01 68 -9.424111e-02 -8.561185e-02 69 6.265319e-02 -9.424111e-02 70 -4.968117e-02 6.265319e-02 71 -9.424111e-02 -4.968117e-02 72 1.809325e-02 -9.424111e-02 73 2.672251e-02 1.809325e-02 74 -9.424111e-02 2.672251e-02 75 3.812479e-01 -9.424111e-02 76 -9.424111e-02 3.812479e-01 77 -4.311372e-02 -9.424111e-02 78 2.563339e-01 -4.311372e-02 79 4.258079e-01 2.563339e-01 80 -4.968117e-02 4.258079e-01 81 -1.783744e-02 -4.968117e-02 82 -4.968117e-02 -1.783744e-02 83 -2.358022e-01 -4.968117e-02 84 -1.554481e-01 -2.358022e-01 85 -8.561185e-02 -1.554481e-01 86 1.661231e-02 -8.561185e-02 87 -4.077494e-01 1.661231e-02 88 9.710293e-02 -4.077494e-01 89 5.254299e-02 9.710293e-02 90 3.589596e-02 5.254299e-02 91 -4.755238e-01 3.589596e-02 92 -3.471892e-05 -4.755238e-01 93 9.710293e-02 -3.471892e-05 94 -4.395931e-01 9.710293e-02 95 5.254299e-02 -4.395931e-01 96 -4.755238e-01 5.254299e-02 97 9.710293e-02 -4.755238e-01 98 6.117225e-02 9.710293e-02 99 5.254299e-02 6.117225e-02 100 1.661231e-02 5.254299e-02 101 9.710293e-02 1.661231e-02 102 9.710293e-02 9.710293e-02 103 9.710293e-02 9.710293e-02 104 -3.272587e-01 9.710293e-02 105 9.710293e-02 -3.272587e-01 106 9.710293e-02 9.710293e-02 107 -3.631894e-01 9.710293e-02 108 9.710293e-02 -3.631894e-01 109 6.117225e-02 9.710293e-02 110 -4.243964e-01 6.117225e-02 111 -4.395931e-01 -4.243964e-01 112 2.094373e-01 -4.395931e-01 113 -3.631894e-01 2.094373e-01 114 6.117225e-02 -3.631894e-01 115 9.710293e-02 6.117225e-02 116 1.661231e-02 9.710293e-02 117 6.117225e-02 1.661231e-02 118 9.710293e-02 6.117225e-02 119 5.254299e-02 9.710293e-02 120 6.117225e-02 5.254299e-02 121 9.710293e-02 6.117225e-02 122 -3.631894e-01 9.710293e-02 123 1.036704e-01 -3.631894e-01 124 5.254299e-02 1.036704e-01 125 -4.395931e-01 5.254299e-02 126 3.589596e-02 -4.395931e-01 127 5.254299e-02 3.589596e-02 128 9.710293e-02 5.254299e-02 129 5.254299e-02 9.710293e-02 130 6.117225e-02 5.254299e-02 131 1.661231e-02 6.117225e-02 132 1.735066e-01 1.661231e-02 133 9.710293e-02 1.735066e-01 134 9.710293e-02 9.710293e-02 135 9.710293e-02 9.710293e-02 136 6.773969e-02 9.710293e-02 137 -4.689563e-01 6.773969e-02 138 -4.395931e-01 -4.689563e-01 139 9.710293e-02 -4.395931e-01 140 -1.335781e-01 9.710293e-02 141 -3.718187e-01 -1.335781e-01 142 6.117225e-02 -3.718187e-01 143 -8.663981e-03 6.117225e-02 144 3.589596e-02 -8.663981e-03 145 -4.841530e-01 3.589596e-02 146 -3.272587e-01 -4.841530e-01 147 -4.395931e-01 -3.272587e-01 148 6.117225e-02 -4.395931e-01 149 -8.663981e-03 6.117225e-02 150 5.254299e-02 -8.663981e-03 151 -1.249488e-01 5.254299e-02 152 -1.861558e-01 -1.249488e-01 153 1.735066e-01 -1.861558e-01 154 NA 1.735066e-01 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -4.968117e-02 4.065242e-01 [2,] -4.968117e-02 -4.968117e-02 [3,] -4.968117e-02 -4.968117e-02 [4,] -4.968117e-02 -4.968117e-02 [5,] -1.913788e-01 -4.968117e-02 [6,] -4.968117e-02 -1.913788e-01 [7,] 4.870149e-01 -4.968117e-02 [8,] -9.424111e-02 4.870149e-01 [9,] -8.561185e-02 -9.424111e-02 [10,] 4.510842e-01 -8.561185e-02 [11,] -4.968117e-02 4.510842e-01 [12,] 1.446221e-03 -4.968117e-02 [13,] 4.510842e-01 1.446221e-03 [14,] -4.311372e-02 4.510842e-01 [15,] 4.935823e-01 -4.311372e-02 [16,] 2.037562e-01 4.935823e-01 [17,] 4.510842e-01 2.037562e-01 [18,] -9.424111e-02 4.510842e-01 [19,] 1.951269e-01 -9.424111e-02 [20,] -1.468188e-01 1.951269e-01 [21,] -7.904441e-02 -1.468188e-01 [22,] -1.554481e-01 -7.904441e-02 [23,] -1.913788e-01 -1.554481e-01 [24,] 5.547893e-01 -1.913788e-01 [25,] 1.446221e-03 5.547893e-01 [26,] -1.301718e-01 1.446221e-03 [27,] 6.265319e-02 -1.301718e-01 [28,] -9.424111e-02 6.265319e-02 [29,] -1.108881e-01 -9.424111e-02 [30,] -4.968117e-02 -1.108881e-01 [31,] -8.561185e-02 -4.968117e-02 [32,] -1.468188e-01 -8.561185e-02 [33,] 4.424549e-01 -1.468188e-01 [34,] -4.968117e-02 4.424549e-01 [35,] -4.968117e-02 -4.968117e-02 [36,] 5.022116e-01 -4.968117e-02 [37,] 1.809325e-02 5.022116e-01 [38,] -1.554481e-01 1.809325e-02 [39,] 4.258079e-01 -1.554481e-01 [40,] -3.415691e-01 4.258079e-01 [41,] 1.809325e-02 -3.415691e-01 [42,] -1.913788e-01 1.809325e-02 [43,] 4.510842e-01 -1.913788e-01 [44,] -1.108881e-01 4.510842e-01 [45,] -1.554481e-01 -1.108881e-01 [46,] -4.968117e-02 -1.554481e-01 [47,] -9.424111e-02 -4.968117e-02 [48,] -1.554481e-01 -9.424111e-02 [49,] -4.968117e-02 -1.554481e-01 [50,] 5.993492e-01 -4.968117e-02 [51,] 2.037562e-01 5.993492e-01 [52,] -9.424111e-02 2.037562e-01 [53,] -2.358022e-01 -9.424111e-02 [54,] -4.968117e-02 -2.358022e-01 [55,] 5.547893e-01 -4.968117e-02 [56,] -4.311372e-02 5.547893e-01 [57,] -9.424111e-02 -4.311372e-02 [58,] -9.424111e-02 -9.424111e-02 [59,] 1.591962e-01 -9.424111e-02 [60,] 4.065242e-01 1.591962e-01 [61,] 1.446221e-03 4.065242e-01 [62,] -4.968117e-02 1.446221e-03 [63,] 4.065242e-01 -4.968117e-02 [64,] -4.968117e-02 4.065242e-01 [65,] -4.968117e-02 -4.968117e-02 [66,] 2.396868e-01 -4.968117e-02 [67,] -8.561185e-02 2.396868e-01 [68,] -9.424111e-02 -8.561185e-02 [69,] 6.265319e-02 -9.424111e-02 [70,] -4.968117e-02 6.265319e-02 [71,] -9.424111e-02 -4.968117e-02 [72,] 1.809325e-02 -9.424111e-02 [73,] 2.672251e-02 1.809325e-02 [74,] -9.424111e-02 2.672251e-02 [75,] 3.812479e-01 -9.424111e-02 [76,] -9.424111e-02 3.812479e-01 [77,] -4.311372e-02 -9.424111e-02 [78,] 2.563339e-01 -4.311372e-02 [79,] 4.258079e-01 2.563339e-01 [80,] -4.968117e-02 4.258079e-01 [81,] -1.783744e-02 -4.968117e-02 [82,] -4.968117e-02 -1.783744e-02 [83,] -2.358022e-01 -4.968117e-02 [84,] -1.554481e-01 -2.358022e-01 [85,] -8.561185e-02 -1.554481e-01 [86,] 1.661231e-02 -8.561185e-02 [87,] -4.077494e-01 1.661231e-02 [88,] 9.710293e-02 -4.077494e-01 [89,] 5.254299e-02 9.710293e-02 [90,] 3.589596e-02 5.254299e-02 [91,] -4.755238e-01 3.589596e-02 [92,] -3.471892e-05 -4.755238e-01 [93,] 9.710293e-02 -3.471892e-05 [94,] -4.395931e-01 9.710293e-02 [95,] 5.254299e-02 -4.395931e-01 [96,] -4.755238e-01 5.254299e-02 [97,] 9.710293e-02 -4.755238e-01 [98,] 6.117225e-02 9.710293e-02 [99,] 5.254299e-02 6.117225e-02 [100,] 1.661231e-02 5.254299e-02 [101,] 9.710293e-02 1.661231e-02 [102,] 9.710293e-02 9.710293e-02 [103,] 9.710293e-02 9.710293e-02 [104,] -3.272587e-01 9.710293e-02 [105,] 9.710293e-02 -3.272587e-01 [106,] 9.710293e-02 9.710293e-02 [107,] -3.631894e-01 9.710293e-02 [108,] 9.710293e-02 -3.631894e-01 [109,] 6.117225e-02 9.710293e-02 [110,] -4.243964e-01 6.117225e-02 [111,] -4.395931e-01 -4.243964e-01 [112,] 2.094373e-01 -4.395931e-01 [113,] -3.631894e-01 2.094373e-01 [114,] 6.117225e-02 -3.631894e-01 [115,] 9.710293e-02 6.117225e-02 [116,] 1.661231e-02 9.710293e-02 [117,] 6.117225e-02 1.661231e-02 [118,] 9.710293e-02 6.117225e-02 [119,] 5.254299e-02 9.710293e-02 [120,] 6.117225e-02 5.254299e-02 [121,] 9.710293e-02 6.117225e-02 [122,] -3.631894e-01 9.710293e-02 [123,] 1.036704e-01 -3.631894e-01 [124,] 5.254299e-02 1.036704e-01 [125,] -4.395931e-01 5.254299e-02 [126,] 3.589596e-02 -4.395931e-01 [127,] 5.254299e-02 3.589596e-02 [128,] 9.710293e-02 5.254299e-02 [129,] 5.254299e-02 9.710293e-02 [130,] 6.117225e-02 5.254299e-02 [131,] 1.661231e-02 6.117225e-02 [132,] 1.735066e-01 1.661231e-02 [133,] 9.710293e-02 1.735066e-01 [134,] 9.710293e-02 9.710293e-02 [135,] 9.710293e-02 9.710293e-02 [136,] 6.773969e-02 9.710293e-02 [137,] -4.689563e-01 6.773969e-02 [138,] -4.395931e-01 -4.689563e-01 [139,] 9.710293e-02 -4.395931e-01 [140,] -1.335781e-01 9.710293e-02 [141,] -3.718187e-01 -1.335781e-01 [142,] 6.117225e-02 -3.718187e-01 [143,] -8.663981e-03 6.117225e-02 [144,] 3.589596e-02 -8.663981e-03 [145,] -4.841530e-01 3.589596e-02 [146,] -3.272587e-01 -4.841530e-01 [147,] -4.395931e-01 -3.272587e-01 [148,] 6.117225e-02 -4.395931e-01 [149,] -8.663981e-03 6.117225e-02 [150,] 5.254299e-02 -8.663981e-03 [151,] -1.249488e-01 5.254299e-02 [152,] -1.861558e-01 -1.249488e-01 [153,] 1.735066e-01 -1.861558e-01 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -4.968117e-02 4.065242e-01 2 -4.968117e-02 -4.968117e-02 3 -4.968117e-02 -4.968117e-02 4 -4.968117e-02 -4.968117e-02 5 -1.913788e-01 -4.968117e-02 6 -4.968117e-02 -1.913788e-01 7 4.870149e-01 -4.968117e-02 8 -9.424111e-02 4.870149e-01 9 -8.561185e-02 -9.424111e-02 10 4.510842e-01 -8.561185e-02 11 -4.968117e-02 4.510842e-01 12 1.446221e-03 -4.968117e-02 13 4.510842e-01 1.446221e-03 14 -4.311372e-02 4.510842e-01 15 4.935823e-01 -4.311372e-02 16 2.037562e-01 4.935823e-01 17 4.510842e-01 2.037562e-01 18 -9.424111e-02 4.510842e-01 19 1.951269e-01 -9.424111e-02 20 -1.468188e-01 1.951269e-01 21 -7.904441e-02 -1.468188e-01 22 -1.554481e-01 -7.904441e-02 23 -1.913788e-01 -1.554481e-01 24 5.547893e-01 -1.913788e-01 25 1.446221e-03 5.547893e-01 26 -1.301718e-01 1.446221e-03 27 6.265319e-02 -1.301718e-01 28 -9.424111e-02 6.265319e-02 29 -1.108881e-01 -9.424111e-02 30 -4.968117e-02 -1.108881e-01 31 -8.561185e-02 -4.968117e-02 32 -1.468188e-01 -8.561185e-02 33 4.424549e-01 -1.468188e-01 34 -4.968117e-02 4.424549e-01 35 -4.968117e-02 -4.968117e-02 36 5.022116e-01 -4.968117e-02 37 1.809325e-02 5.022116e-01 38 -1.554481e-01 1.809325e-02 39 4.258079e-01 -1.554481e-01 40 -3.415691e-01 4.258079e-01 41 1.809325e-02 -3.415691e-01 42 -1.913788e-01 1.809325e-02 43 4.510842e-01 -1.913788e-01 44 -1.108881e-01 4.510842e-01 45 -1.554481e-01 -1.108881e-01 46 -4.968117e-02 -1.554481e-01 47 -9.424111e-02 -4.968117e-02 48 -1.554481e-01 -9.424111e-02 49 -4.968117e-02 -1.554481e-01 50 5.993492e-01 -4.968117e-02 51 2.037562e-01 5.993492e-01 52 -9.424111e-02 2.037562e-01 53 -2.358022e-01 -9.424111e-02 54 -4.968117e-02 -2.358022e-01 55 5.547893e-01 -4.968117e-02 56 -4.311372e-02 5.547893e-01 57 -9.424111e-02 -4.311372e-02 58 -9.424111e-02 -9.424111e-02 59 1.591962e-01 -9.424111e-02 60 4.065242e-01 1.591962e-01 61 1.446221e-03 4.065242e-01 62 -4.968117e-02 1.446221e-03 63 4.065242e-01 -4.968117e-02 64 -4.968117e-02 4.065242e-01 65 -4.968117e-02 -4.968117e-02 66 2.396868e-01 -4.968117e-02 67 -8.561185e-02 2.396868e-01 68 -9.424111e-02 -8.561185e-02 69 6.265319e-02 -9.424111e-02 70 -4.968117e-02 6.265319e-02 71 -9.424111e-02 -4.968117e-02 72 1.809325e-02 -9.424111e-02 73 2.672251e-02 1.809325e-02 74 -9.424111e-02 2.672251e-02 75 3.812479e-01 -9.424111e-02 76 -9.424111e-02 3.812479e-01 77 -4.311372e-02 -9.424111e-02 78 2.563339e-01 -4.311372e-02 79 4.258079e-01 2.563339e-01 80 -4.968117e-02 4.258079e-01 81 -1.783744e-02 -4.968117e-02 82 -4.968117e-02 -1.783744e-02 83 -2.358022e-01 -4.968117e-02 84 -1.554481e-01 -2.358022e-01 85 -8.561185e-02 -1.554481e-01 86 1.661231e-02 -8.561185e-02 87 -4.077494e-01 1.661231e-02 88 9.710293e-02 -4.077494e-01 89 5.254299e-02 9.710293e-02 90 3.589596e-02 5.254299e-02 91 -4.755238e-01 3.589596e-02 92 -3.471892e-05 -4.755238e-01 93 9.710293e-02 -3.471892e-05 94 -4.395931e-01 9.710293e-02 95 5.254299e-02 -4.395931e-01 96 -4.755238e-01 5.254299e-02 97 9.710293e-02 -4.755238e-01 98 6.117225e-02 9.710293e-02 99 5.254299e-02 6.117225e-02 100 1.661231e-02 5.254299e-02 101 9.710293e-02 1.661231e-02 102 9.710293e-02 9.710293e-02 103 9.710293e-02 9.710293e-02 104 -3.272587e-01 9.710293e-02 105 9.710293e-02 -3.272587e-01 106 9.710293e-02 9.710293e-02 107 -3.631894e-01 9.710293e-02 108 9.710293e-02 -3.631894e-01 109 6.117225e-02 9.710293e-02 110 -4.243964e-01 6.117225e-02 111 -4.395931e-01 -4.243964e-01 112 2.094373e-01 -4.395931e-01 113 -3.631894e-01 2.094373e-01 114 6.117225e-02 -3.631894e-01 115 9.710293e-02 6.117225e-02 116 1.661231e-02 9.710293e-02 117 6.117225e-02 1.661231e-02 118 9.710293e-02 6.117225e-02 119 5.254299e-02 9.710293e-02 120 6.117225e-02 5.254299e-02 121 9.710293e-02 6.117225e-02 122 -3.631894e-01 9.710293e-02 123 1.036704e-01 -3.631894e-01 124 5.254299e-02 1.036704e-01 125 -4.395931e-01 5.254299e-02 126 3.589596e-02 -4.395931e-01 127 5.254299e-02 3.589596e-02 128 9.710293e-02 5.254299e-02 129 5.254299e-02 9.710293e-02 130 6.117225e-02 5.254299e-02 131 1.661231e-02 6.117225e-02 132 1.735066e-01 1.661231e-02 133 9.710293e-02 1.735066e-01 134 9.710293e-02 9.710293e-02 135 9.710293e-02 9.710293e-02 136 6.773969e-02 9.710293e-02 137 -4.689563e-01 6.773969e-02 138 -4.395931e-01 -4.689563e-01 139 9.710293e-02 -4.395931e-01 140 -1.335781e-01 9.710293e-02 141 -3.718187e-01 -1.335781e-01 142 6.117225e-02 -3.718187e-01 143 -8.663981e-03 6.117225e-02 144 3.589596e-02 -8.663981e-03 145 -4.841530e-01 3.589596e-02 146 -3.272587e-01 -4.841530e-01 147 -4.395931e-01 -3.272587e-01 148 6.117225e-02 -4.395931e-01 149 -8.663981e-03 6.117225e-02 150 5.254299e-02 -8.663981e-03 151 -1.249488e-01 5.254299e-02 152 -1.861558e-01 -1.249488e-01 153 1.735066e-01 -1.861558e-01 > 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/77z8e1355679607.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8vqok1355679607.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9a8yc1355679607.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10pzo31355679607.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/11do3i1355679607.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/129ho01355679607.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/131okc1355679607.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/144fh51355679607.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/15m2yt1355679607.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/16g8731355679607.tab") + } > > try(system("convert tmp/1t4z11355679607.ps tmp/1t4z11355679607.png",intern=TRUE)) character(0) > try(system("convert tmp/2fa4o1355679607.ps tmp/2fa4o1355679607.png",intern=TRUE)) character(0) > try(system("convert tmp/3adz11355679607.ps tmp/3adz11355679607.png",intern=TRUE)) character(0) > try(system("convert tmp/4apqi1355679607.ps tmp/4apqi1355679607.png",intern=TRUE)) character(0) > try(system("convert tmp/5g6ci1355679607.ps tmp/5g6ci1355679607.png",intern=TRUE)) character(0) > try(system("convert tmp/6a9wq1355679607.ps tmp/6a9wq1355679607.png",intern=TRUE)) character(0) > try(system("convert tmp/77z8e1355679607.ps tmp/77z8e1355679607.png",intern=TRUE)) character(0) > try(system("convert tmp/8vqok1355679607.ps tmp/8vqok1355679607.png",intern=TRUE)) character(0) > try(system("convert tmp/9a8yc1355679607.ps tmp/9a8yc1355679607.png",intern=TRUE)) character(0) > try(system("convert tmp/10pzo31355679607.ps tmp/10pzo31355679607.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 10.662 1.143 11.806