R version 2.8.0 (2008-10-20) Copyright (C) 2008 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. Natural language support but running in an English locale 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 + ,4 + ,3 + ,3 + ,2 + ,2 + ,2 + ,2 + ,2 + ,4 + ,2 + ,4 + ,2 + ,3 + ,1 + ,1 + ,2 + ,3 + ,3 + ,2 + ,2 + ,1 + ,2 + ,2 + ,5 + ,4 + ,4 + ,3 + ,4 + ,3 + ,2 + ,2 + ,4 + ,4 + ,4 + ,2 + ,2 + ,1 + ,1 + ,2 + ,4 + ,4 + ,4 + ,4 + ,2 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,2 + ,1 + ,1 + ,2 + ,3 + ,4 + ,4 + ,2 + ,3 + ,3 + ,2 + ,3 + ,3 + ,4 + ,4 + ,3 + ,4 + ,1 + ,2 + ,2 + ,2 + ,2 + ,3 + ,2 + ,2 + ,1 + ,3 + ,1 + ,2 + ,4 + ,3 + ,4 + ,3 + ,4 + ,3 + ,4 + ,4 + ,1 + ,2 + ,2 + ,2 + ,4 + ,4 + ,4 + ,3 + ,5 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,3 + ,3 + ,2 + ,2 + ,2 + ,2 + ,2 + ,2 + ,2 + ,2 + ,4 + ,4 + ,2 + ,4 + ,4 + ,3 + ,4 + ,3 + ,2 + ,2 + ,1 + ,3 + ,3 + ,2 + ,4 + ,2 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,1 + ,3 + ,2 + ,2 + ,2 + ,2 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,3 + ,4 + ,1 + ,1 + ,1 + ,2 + ,2 + ,2 + ,3 + ,1 + ,4 + ,2 + ,2 + ,2 + ,2 + ,2 + ,1 + ,3 + ,3 + ,4 + ,3 + ,3 + ,4 + ,3 + ,4 + ,4 + ,1 + ,2 + ,1 + ,2 + ,3 + ,2 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,1 + ,1 + ,1 + ,2 + ,4 + ,5 + ,4 + ,2 + ,3 + ,2 + ,4 + ,3 + ,1 + ,3 + ,2 + ,2 + ,1 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,3 + ,2 + ,3 + ,4 + ,4 + ,4 + ,4 + ,2 + ,2 + ,2 + ,4 + ,4 + ,3 + ,4 + ,4 + ,2 + ,2 + ,2 + ,2 + ,4 + ,4 + ,4 + ,4 + ,5 + ,5 + ,5 + ,4 + ,3 + ,3 + ,4 + ,4 + ,2 + ,1 + ,1 + ,2 + ,4 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,3 + ,2 + ,2 + ,1 + ,2 + ,3 + ,3 + ,3 + ,4 + ,1 + ,1 + ,1 + ,1 + ,4 + ,3 + ,4 + ,3 + ,4 + ,2 + ,4 + ,3 + ,4 + ,3 + ,2 + ,2 + ,4 + ,4 + ,4 + ,2 + ,3 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,3 + ,3 + ,3 + ,4 + ,3 + ,2 + ,2 + ,1 + ,3 + ,1 + ,1 + ,2 + ,2 + ,2 + ,2 + ,1 + ,2 + ,4 + ,3 + ,3 + ,3 + ,3 + ,4 + ,3 + ,3 + ,5 + ,1 + ,3 + ,2 + ,1 + ,1 + ,1 + ,2 + ,3 + ,3 + ,3 + ,3 + ,2 + ,2 + ,2 + ,2 + ,3 + ,2 + ,3 + ,3 + ,4 + ,3 + ,4 + ,3 + ,3 + ,2 + ,2 + ,2 + ,3 + ,2 + ,2 + ,3 + ,4 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,2 + ,4 + ,3 + ,2 + ,2 + ,2 + ,2 + ,1 + ,1 + ,1 + ,1 + ,1 + ,2 + ,2 + ,2 + ,4 + ,3 + ,4 + ,3 + ,2 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,5 + ,3 + ,4 + ,4 + ,4 + ,5 + ,4 + ,3 + ,5 + ,1 + ,NA + ,2 + ,2 + ,1 + ,1 + ,1 + ,1 + ,2 + ,3 + ,2 + ,3 + ,4 + ,2 + ,2 + ,3 + ,4 + ,3 + ,4 + ,4 + ,3 + ,3 + ,2 + ,2 + ,4 + ,2 + ,1 + ,2 + ,4 + ,3 + ,2 + ,3 + ,5 + ,2 + ,4 + ,4 + ,1 + ,2 + ,2 + ,2 + ,4 + ,3 + ,3 + ,3 + ,4 + ,2 + ,3 + ,3 + ,4 + ,3 + ,3 + ,4 + ,2 + ,4 + ,4 + ,4 + ,2 + ,2 + ,2 + ,2 + ,4 + ,4 + ,4 + ,3 + ,3 + ,3 + ,4 + ,2 + ,3 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,2 + ,2 + ,3 + ,2 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,1 + ,1 + ,2 + ,2 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,3 + ,3 + ,2 + ,2 + ,3 + ,1 + ,1 + ,1 + ,3 + ,4 + ,4 + ,2 + ,4 + ,3 + ,2 + ,4 + ,3 + ,2 + ,2 + ,2 + ,2 + ,3 + ,3 + ,2 + ,3 + ,4 + ,3 + ,3 + ,3 + ,2 + ,2 + ,2 + ,3 + ,4 + ,3 + ,4 + ,4 + ,4 + ,3 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,3 + ,4 + ,4 + ,3 + ,3 + ,3 + ,3 + ,2 + ,2 + ,3 + ,2 + ,2 + ,3 + ,1 + ,1 + ,1 + ,1 + ,2 + ,2 + ,2 + ,2 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,3 + ,3 + ,3 + ,3 + ,3 + ,3 + ,4 + ,3 + ,4 + ,4 + ,3 + ,2 + ,2 + ,2 + ,4 + ,NA + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,2 + ,2 + ,3) + ,dim=c(4 + ,156) + ,dimnames=list(c('Q1' + ,'Q2' + ,'Q3' + ,'Q4 ') + ,1:156)) > y <- array(NA,dim=c(4,156),dimnames=list(c('Q1','Q2','Q3','Q4 '),1:156)) > 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 = '4' > #'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 Q4\r Q1 Q2 Q3 1 3 4 4 3 2 2 2 2 2 3 4 2 4 2 4 1 2 3 1 5 2 2 3 3 6 2 2 1 2 7 3 5 4 4 8 2 4 3 2 9 2 4 4 4 10 2 2 1 1 11 4 4 4 4 12 3 2 3 3 13 4 4 4 4 14 2 4 4 2 15 3 1 1 2 16 3 4 4 2 17 3 3 2 3 18 4 4 4 3 19 2 1 2 2 20 2 2 3 2 21 2 1 3 1 22 3 4 3 4 23 4 4 3 4 24 2 1 2 2 25 3 4 4 4 26 4 5 4 4 27 3 4 4 4 28 3 4 4 3 29 3 4 4 3 30 2 2 2 2 31 2 2 2 2 32 4 4 4 2 33 3 4 3 4 34 3 2 2 1 35 2 3 2 4 36 4 4 4 4 37 3 3 3 1 38 2 2 2 2 39 3 4 4 3 40 4 4 4 4 41 4 3 3 3 42 2 1 1 1 43 1 2 2 3 44 2 4 2 2 45 3 2 2 1 46 3 3 4 3 47 4 4 3 4 48 2 1 2 1 49 3 3 2 4 50 4 4 4 4 51 2 1 1 1 52 2 4 5 4 53 3 3 2 4 54 2 1 3 2 55 4 1 4 4 56 3 4 4 3 57 3 4 3 2 58 4 4 4 4 59 4 2 2 2 60 4 4 3 4 61 2 2 2 2 62 4 4 4 4 63 4 5 5 5 64 4 3 3 4 65 2 2 1 1 66 3 4 3 3 67 3 4 4 4 68 2 2 2 1 69 4 3 3 3 70 1 1 1 1 71 3 4 3 4 72 3 4 2 4 73 2 4 3 2 74 2 4 4 4 75 3 3 3 3 76 3 4 4 4 77 3 3 4 4 78 3 3 3 4 79 3 2 2 1 80 2 1 1 2 81 2 2 2 1 82 3 4 3 3 83 3 3 4 3 84 2 5 1 3 85 2 1 1 1 86 3 3 3 3 87 2 2 2 2 88 3 3 2 3 89 3 4 3 4 90 2 3 2 2 91 3 3 2 2 92 3 4 3 3 93 4 4 4 4 94 4 4 4 4 95 3 2 2 4 96 2 2 2 2 97 1 1 1 1 98 2 1 2 2 99 3 4 3 4 100 3 2 3 3 101 5 4 4 4 102 4 3 4 4 103 5 5 4 3 104 2 1 NA 2 105 1 1 1 1 106 3 2 3 2 107 3 4 2 2 108 4 4 3 4 109 2 3 3 2 110 2 4 2 1 111 3 4 3 2 112 4 5 2 4 113 2 1 2 2 114 3 4 3 3 115 3 4 2 3 116 4 4 3 3 117 4 2 4 4 118 2 2 2 2 119 3 4 4 4 120 2 3 3 4 121 3 3 3 3 122 4 4 4 4 123 2 2 2 3 124 4 4 3 4 125 4 4 4 3 126 2 1 1 2 127 3 4 4 3 128 3 4 4 4 129 3 3 2 2 130 3 1 1 1 131 4 4 4 2 132 3 3 2 4 133 2 2 2 2 134 3 3 3 2 135 3 4 3 3 136 3 2 2 2 137 4 4 3 4 138 3 4 3 3 139 4 3 4 4 140 4 4 3 3 141 4 4 4 4 142 3 4 3 4 143 3 4 4 3 144 2 3 3 2 145 3 3 2 2 146 1 1 1 1 147 2 2 2 2 148 4 4 4 3 149 4 4 4 4 150 3 3 3 3 151 3 3 3 3 152 4 4 3 4 153 2 3 2 2 154 4 4 NA 4 155 3 4 4 3 156 3 4 2 2 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Q1 Q2 Q3 1.0764 0.1533 0.2308 0.2475 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -1.83363 -0.36786 -0.04002 0.39717 1.66039 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.07640 0.16966 6.344 2.50e-09 *** Q1 0.15332 0.06471 2.369 0.01910 * Q2 0.23080 0.07255 3.181 0.00178 ** Q3 0.24749 0.06806 3.636 0.00038 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.638 on 150 degrees of freedom (2 observations deleted due to missingness) Multiple R-squared: 0.4622, Adjusted R-squared: 0.4514 F-statistic: 42.97 on 3 and 150 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,] 0.9536404 0.09271918 0.04635959 [2,] 0.9114042 0.17719168 0.08859584 [3,] 0.9525786 0.09484281 0.04742140 [4,] 0.9345943 0.13081137 0.06540568 [5,] 0.9602302 0.07953956 0.03976978 [6,] 0.9372453 0.12550948 0.06275474 [7,] 0.9402461 0.11950781 0.05975390 [8,] 0.9276816 0.14463683 0.07231841 [9,] 0.9345668 0.13086643 0.06543322 [10,] 0.9322811 0.13543790 0.06771895 [11,] 0.9121888 0.17562233 0.08781117 [12,] 0.9430522 0.11389565 0.05694782 [13,] 0.9294250 0.14114991 0.07057495 [14,] 0.9179147 0.16417060 0.08208530 [15,] 0.8885786 0.22284287 0.11142143 [16,] 0.8572580 0.28548410 0.14274205 [17,] 0.8621126 0.27577490 0.13788745 [18,] 0.8308665 0.33826696 0.16913348 [19,] 0.8107446 0.37851082 0.18925541 [20,] 0.7932876 0.41342472 0.20671236 [21,] 0.7726498 0.45470041 0.22735020 [22,] 0.7278690 0.54426196 0.27213098 [23,] 0.6801443 0.63971143 0.31985572 [24,] 0.6342803 0.73143942 0.36571971 [25,] 0.5861436 0.82771273 0.41385637 [26,] 0.7338713 0.53225745 0.26612872 [27,] 0.6928454 0.61430930 0.30715465 [28,] 0.7524670 0.49506602 0.24753301 [29,] 0.7874516 0.42509673 0.21254836 [30,] 0.7794895 0.44102099 0.22051050 [31,] 0.7671802 0.46563962 0.23281981 [32,] 0.7324613 0.53507742 0.26753871 [33,] 0.6935585 0.61288297 0.30644149 [34,] 0.6818902 0.63621964 0.31810982 [35,] 0.7654410 0.46911801 0.23455900 [36,] 0.7300816 0.53983685 0.26991843 [37,] 0.8799501 0.24009972 0.12004986 [38,] 0.8728281 0.25434370 0.12717185 [39,] 0.8951315 0.20973690 0.10486845 [40,] 0.8717120 0.25657608 0.12828804 [41,] 0.8826096 0.23478087 0.11739044 [42,] 0.8559096 0.28818071 0.14409036 [43,] 0.8279517 0.34409659 0.17204830 [44,] 0.8141251 0.37174971 0.18587485 [45,] 0.7857485 0.42850297 0.21425149 [46,] 0.9397003 0.12059934 0.06029967 [47,] 0.9242014 0.15159725 0.07579862 [48,] 0.9122146 0.17557076 0.08778538 [49,] 0.9315415 0.13691698 0.06845849 [50,] 0.9194359 0.16112827 0.08056413 [51,] 0.9018566 0.19628672 0.09814336 [52,] 0.8923172 0.21536559 0.10768279 [53,] 0.9716933 0.05661332 0.02830666 [54,] 0.9722827 0.05543459 0.02771730 [55,] 0.9664556 0.06708878 0.03354439 [56,] 0.9613848 0.07723038 0.03861519 [57,] 0.9530901 0.09381974 0.04690987 [58,] 0.9586307 0.08273863 0.04136932 [59,] 0.9478910 0.10421791 0.05210895 [60,] 0.9348009 0.13039819 0.06519910 [61,] 0.9339801 0.13203977 0.06601988 [62,] 0.9178888 0.16422239 0.08211120 [63,] 0.9423836 0.11523286 0.05761643 [64,] 0.9452716 0.10945681 0.05472840 [65,] 0.9360561 0.12788778 0.06394389 [66,] 0.9205081 0.15898385 0.07949193 [67,] 0.9366542 0.12669166 0.06334583 [68,] 0.9867981 0.02640386 0.01320193 [69,] 0.9823037 0.03539259 0.01769629 [70,] 0.9835864 0.03282723 0.01641361 [71,] 0.9825051 0.03498976 0.01749488 [72,] 0.9778539 0.04429223 0.02214611 [73,] 0.9846643 0.03067136 0.01533568 [74,] 0.9803020 0.03939606 0.01969803 [75,] 0.9740050 0.05199000 0.02599500 [76,] 0.9671697 0.06566058 0.03283029 [77,] 0.9609854 0.07802922 0.03901461 [78,] 0.9674627 0.06507468 0.03253734 [79,] 0.9636663 0.07266746 0.03633373 [80,] 0.9532811 0.09343780 0.04671890 [81,] 0.9436054 0.11278922 0.05639461 [82,] 0.9316693 0.13666147 0.06833073 [83,] 0.9268121 0.14637572 0.07318786 [84,] 0.9207053 0.15858947 0.07929474 [85,] 0.9156023 0.16879533 0.08439767 [86,] 0.9001629 0.19967420 0.09983710 [87,] 0.8847084 0.23058320 0.11529160 [88,] 0.8670833 0.26583341 0.13291671 [89,] 0.8416647 0.31667050 0.15833525 [90,] 0.8176660 0.36466800 0.18233400 [91,] 0.8149558 0.37008843 0.18504421 [92,] 0.7823830 0.43523403 0.21761701 [93,] 0.7734403 0.45311934 0.22655967 [94,] 0.7373547 0.52529061 0.26264531 [95,] 0.8484648 0.30307038 0.15153519 [96,] 0.8367936 0.32641274 0.16320637 [97,] 0.9267761 0.14644774 0.07322387 [98,] 0.9275212 0.14495768 0.07247884 [99,] 0.9199007 0.16019851 0.08009925 [100,] 0.9032113 0.19357733 0.09678867 [101,] 0.8961186 0.20776277 0.10388138 [102,] 0.9077429 0.18451417 0.09225709 [103,] 0.9065130 0.18697400 0.09348700 [104,] 0.8838324 0.23233524 0.11616762 [105,] 0.8787556 0.24248872 0.12124436 [106,] 0.8506502 0.29869955 0.14934978 [107,] 0.8230860 0.35382798 0.17691399 [108,] 0.7854938 0.42901243 0.21450621 [109,] 0.8044770 0.39104596 0.19552298 [110,] 0.8433342 0.31333161 0.15666580 [111,] 0.8178652 0.36426953 0.18213477 [112,] 0.8193428 0.36131432 0.18065716 [113,] 0.9113467 0.17730654 0.08865327 [114,] 0.8849133 0.23017349 0.11508674 [115,] 0.8604149 0.27917017 0.13958508 [116,] 0.8631157 0.27376859 0.13688429 [117,] 0.8490870 0.30182599 0.15091300 [118,] 0.8408033 0.31839348 0.15919674 [119,] 0.7988520 0.40229606 0.20114803 [120,] 0.7788596 0.44228071 0.22114035 [121,] 0.8042395 0.39152094 0.19576047 [122,] 0.7756534 0.44869311 0.22434656 [123,] 0.9525169 0.09496626 0.04748313 [124,] 0.9682470 0.06350609 0.03175305 [125,] 0.9585798 0.08284031 0.04142016 [126,] 0.9419763 0.11604745 0.05802373 [127,] 0.9331895 0.13362094 0.06681047 [128,] 0.9123472 0.17530556 0.08765278 [129,] 0.9523401 0.09531983 0.04765991 [130,] 0.9302922 0.13941562 0.06970781 [131,] 0.9095952 0.18080964 0.09040482 [132,] 0.9107299 0.17854014 0.08927007 [133,] 0.9255918 0.14881634 0.07440817 [134,] 0.8915808 0.21683838 0.10841919 [135,] 0.9610684 0.07786322 0.03893161 [136,] 0.9445648 0.11087041 0.05543520 [137,] 0.9350311 0.12993776 0.06496888 [138,] 0.9480293 0.10394142 0.05197071 [139,] 0.9004788 0.19904238 0.09952119 [140,] 0.8262901 0.34741981 0.17370991 [141,] 0.9163365 0.16732694 0.08366347 [142,] 0.7826455 0.43470892 0.21735446 [143,] 0.5272161 0.94556790 0.47278395 > postscript(file="/var/www/html/freestat/rcomp/tmp/1f3ad1291196222.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$resid) Warning message: In x[, 1] - mysum$resid : longer object length is not a multiple of shorter object length > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/2f3ad1291196222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/3f3ad1291196222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/48u9x1291196222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/58u9x1291196222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 154 Frequency = 1 1 2 3 4 5 6 -0.35534061 -0.33961357 1.19879179 -1.32292051 -0.81790127 -0.10881625 7 8 9 10 11 12 -0.75615200 -0.87705291 -1.60283098 0.13867412 0.39716902 0.18209873 13 14 15 16 17 18 0.39716902 -1.10785023 1.04450476 -0.10785023 0.25957504 0.64465939 19 20 21 22 23 24 -0.18629256 -0.57041089 -0.16959950 -0.37203367 0.62796633 -0.18629256 25 26 27 28 29 30 -0.60283098 0.24384800 -0.60283098 -0.35534061 -0.35534061 -0.33961357 31 32 33 34 35 36 -0.33961357 0.89214977 -0.37203367 0.90787680 -0.98791534 0.39716902 37 38 39 40 41 42 0.52375848 -0.33961357 -0.35534061 0.39716902 1.02877772 0.29199513 43 44 45 46 47 48 -1.58710395 -0.64625560 0.90787680 -0.20201959 0.62796633 0.06119782 49 50 51 52 53 54 0.01208466 0.39716902 0.29199513 -1.83362830 0.01208466 -0.41708988 55 56 57 58 59 60 0.85713205 -0.35534061 0.12294709 0.39716902 1.66038643 0.62796633 61 62 63 64 65 66 -0.33961357 0.39716902 -0.23443969 0.78128735 0.13867412 -0.12454329 67 68 69 70 71 72 -0.60283098 -0.09212320 1.02877772 -0.70800487 -0.37203367 -0.14123635 73 74 75 76 77 78 -0.87705291 -1.60283098 0.02877772 -0.60283098 -0.44950997 -0.21871265 79 80 81 82 83 84 0.90787680 0.04450476 -0.09212320 -0.12454329 -0.20201959 -0.81626967 85 86 87 88 89 90 0.29199513 0.02877772 -0.33961357 0.25957504 -0.37203367 -0.49293458 91 92 93 94 95 96 0.50706542 -0.12454329 0.39716902 0.39716902 0.16540567 -0.33961357 97 98 99 100 101 102 -0.70800487 -0.18629256 -0.37203367 0.18209873 1.39716902 0.55049003 103 105 106 107 108 109 1.49133838 -0.70800487 0.42958911 0.35374440 0.62796633 -0.72373190 110 111 112 113 114 115 -0.39876522 0.12294709 0.70544264 -0.18629256 -0.12454329 0.10625403 116 117 118 119 120 121 0.87545671 0.70381104 -0.33961357 -0.60283098 -1.21871265 0.02877772 122 123 124 125 126 127 0.39716902 -0.58710395 0.62796633 0.64465939 0.04450476 -0.35534061 128 129 130 131 132 133 -0.60283098 0.50706542 1.29199513 0.89214977 0.01208466 -0.33961357 134 135 136 137 138 139 0.27626810 -0.12454329 0.66038643 0.62796633 -0.12454329 0.55049003 140 141 142 143 144 145 0.87545671 0.39716902 -0.37203367 -0.35534061 -0.72373190 0.50706542 146 147 148 149 150 151 -0.70800487 -0.33961357 0.64465939 0.39716902 0.02877772 0.02877772 152 153 155 156 0.62796633 -0.49293458 -0.35534061 0.35374440 > postscript(file="/var/www/html/freestat/rcomp/tmp/6j4qi1291196222.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 154 Frequency = 1 lag(myerror, k = 1) myerror 0 -0.35534061 NA 1 -0.33961357 -0.35534061 2 1.19879179 -0.33961357 3 -1.32292051 1.19879179 4 -0.81790127 -1.32292051 5 -0.10881625 -0.81790127 6 -0.75615200 -0.10881625 7 -0.87705291 -0.75615200 8 -1.60283098 -0.87705291 9 0.13867412 -1.60283098 10 0.39716902 0.13867412 11 0.18209873 0.39716902 12 0.39716902 0.18209873 13 -1.10785023 0.39716902 14 1.04450476 -1.10785023 15 -0.10785023 1.04450476 16 0.25957504 -0.10785023 17 0.64465939 0.25957504 18 -0.18629256 0.64465939 19 -0.57041089 -0.18629256 20 -0.16959950 -0.57041089 21 -0.37203367 -0.16959950 22 0.62796633 -0.37203367 23 -0.18629256 0.62796633 24 -0.60283098 -0.18629256 25 0.24384800 -0.60283098 26 -0.60283098 0.24384800 27 -0.35534061 -0.60283098 28 -0.35534061 -0.35534061 29 -0.33961357 -0.35534061 30 -0.33961357 -0.33961357 31 0.89214977 -0.33961357 32 -0.37203367 0.89214977 33 0.90787680 -0.37203367 34 -0.98791534 0.90787680 35 0.39716902 -0.98791534 36 0.52375848 0.39716902 37 -0.33961357 0.52375848 38 -0.35534061 -0.33961357 39 0.39716902 -0.35534061 40 1.02877772 0.39716902 41 0.29199513 1.02877772 42 -1.58710395 0.29199513 43 -0.64625560 -1.58710395 44 0.90787680 -0.64625560 45 -0.20201959 0.90787680 46 0.62796633 -0.20201959 47 0.06119782 0.62796633 48 0.01208466 0.06119782 49 0.39716902 0.01208466 50 0.29199513 0.39716902 51 -1.83362830 0.29199513 52 0.01208466 -1.83362830 53 -0.41708988 0.01208466 54 0.85713205 -0.41708988 55 -0.35534061 0.85713205 56 0.12294709 -0.35534061 57 0.39716902 0.12294709 58 1.66038643 0.39716902 59 0.62796633 1.66038643 60 -0.33961357 0.62796633 61 0.39716902 -0.33961357 62 -0.23443969 0.39716902 63 0.78128735 -0.23443969 64 0.13867412 0.78128735 65 -0.12454329 0.13867412 66 -0.60283098 -0.12454329 67 -0.09212320 -0.60283098 68 1.02877772 -0.09212320 69 -0.70800487 1.02877772 70 -0.37203367 -0.70800487 71 -0.14123635 -0.37203367 72 -0.87705291 -0.14123635 73 -1.60283098 -0.87705291 74 0.02877772 -1.60283098 75 -0.60283098 0.02877772 76 -0.44950997 -0.60283098 77 -0.21871265 -0.44950997 78 0.90787680 -0.21871265 79 0.04450476 0.90787680 80 -0.09212320 0.04450476 81 -0.12454329 -0.09212320 82 -0.20201959 -0.12454329 83 -0.81626967 -0.20201959 84 0.29199513 -0.81626967 85 0.02877772 0.29199513 86 -0.33961357 0.02877772 87 0.25957504 -0.33961357 88 -0.37203367 0.25957504 89 -0.49293458 -0.37203367 90 0.50706542 -0.49293458 91 -0.12454329 0.50706542 92 0.39716902 -0.12454329 93 0.39716902 0.39716902 94 0.16540567 0.39716902 95 -0.33961357 0.16540567 96 -0.70800487 -0.33961357 97 -0.18629256 -0.70800487 98 -0.37203367 -0.18629256 99 0.18209873 -0.37203367 100 1.39716902 0.18209873 101 0.55049003 1.39716902 102 1.49133838 0.55049003 103 -0.70800487 1.49133838 104 0.42958911 -0.70800487 105 0.35374440 0.42958911 106 0.62796633 0.35374440 107 -0.72373190 0.62796633 108 -0.39876522 -0.72373190 109 0.12294709 -0.39876522 110 0.70544264 0.12294709 111 -0.18629256 0.70544264 112 -0.12454329 -0.18629256 113 0.10625403 -0.12454329 114 0.87545671 0.10625403 115 0.70381104 0.87545671 116 -0.33961357 0.70381104 117 -0.60283098 -0.33961357 118 -1.21871265 -0.60283098 119 0.02877772 -1.21871265 120 0.39716902 0.02877772 121 -0.58710395 0.39716902 122 0.62796633 -0.58710395 123 0.64465939 0.62796633 124 0.04450476 0.64465939 125 -0.35534061 0.04450476 126 -0.60283098 -0.35534061 127 0.50706542 -0.60283098 128 1.29199513 0.50706542 129 0.89214977 1.29199513 130 0.01208466 0.89214977 131 -0.33961357 0.01208466 132 0.27626810 -0.33961357 133 -0.12454329 0.27626810 134 0.66038643 -0.12454329 135 0.62796633 0.66038643 136 -0.12454329 0.62796633 137 0.55049003 -0.12454329 138 0.87545671 0.55049003 139 0.39716902 0.87545671 140 -0.37203367 0.39716902 141 -0.35534061 -0.37203367 142 -0.72373190 -0.35534061 143 0.50706542 -0.72373190 144 -0.70800487 0.50706542 145 -0.33961357 -0.70800487 146 0.64465939 -0.33961357 147 0.39716902 0.64465939 148 0.02877772 0.39716902 149 0.02877772 0.02877772 150 0.62796633 0.02877772 151 -0.49293458 0.62796633 152 -0.35534061 -0.49293458 153 0.35374440 -0.35534061 154 NA 0.35374440 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -0.33961357 -0.35534061 [2,] 1.19879179 -0.33961357 [3,] -1.32292051 1.19879179 [4,] -0.81790127 -1.32292051 [5,] -0.10881625 -0.81790127 [6,] -0.75615200 -0.10881625 [7,] -0.87705291 -0.75615200 [8,] -1.60283098 -0.87705291 [9,] 0.13867412 -1.60283098 [10,] 0.39716902 0.13867412 [11,] 0.18209873 0.39716902 [12,] 0.39716902 0.18209873 [13,] -1.10785023 0.39716902 [14,] 1.04450476 -1.10785023 [15,] -0.10785023 1.04450476 [16,] 0.25957504 -0.10785023 [17,] 0.64465939 0.25957504 [18,] -0.18629256 0.64465939 [19,] -0.57041089 -0.18629256 [20,] -0.16959950 -0.57041089 [21,] -0.37203367 -0.16959950 [22,] 0.62796633 -0.37203367 [23,] -0.18629256 0.62796633 [24,] -0.60283098 -0.18629256 [25,] 0.24384800 -0.60283098 [26,] -0.60283098 0.24384800 [27,] -0.35534061 -0.60283098 [28,] -0.35534061 -0.35534061 [29,] -0.33961357 -0.35534061 [30,] -0.33961357 -0.33961357 [31,] 0.89214977 -0.33961357 [32,] -0.37203367 0.89214977 [33,] 0.90787680 -0.37203367 [34,] -0.98791534 0.90787680 [35,] 0.39716902 -0.98791534 [36,] 0.52375848 0.39716902 [37,] -0.33961357 0.52375848 [38,] -0.35534061 -0.33961357 [39,] 0.39716902 -0.35534061 [40,] 1.02877772 0.39716902 [41,] 0.29199513 1.02877772 [42,] -1.58710395 0.29199513 [43,] -0.64625560 -1.58710395 [44,] 0.90787680 -0.64625560 [45,] -0.20201959 0.90787680 [46,] 0.62796633 -0.20201959 [47,] 0.06119782 0.62796633 [48,] 0.01208466 0.06119782 [49,] 0.39716902 0.01208466 [50,] 0.29199513 0.39716902 [51,] -1.83362830 0.29199513 [52,] 0.01208466 -1.83362830 [53,] -0.41708988 0.01208466 [54,] 0.85713205 -0.41708988 [55,] -0.35534061 0.85713205 [56,] 0.12294709 -0.35534061 [57,] 0.39716902 0.12294709 [58,] 1.66038643 0.39716902 [59,] 0.62796633 1.66038643 [60,] -0.33961357 0.62796633 [61,] 0.39716902 -0.33961357 [62,] -0.23443969 0.39716902 [63,] 0.78128735 -0.23443969 [64,] 0.13867412 0.78128735 [65,] -0.12454329 0.13867412 [66,] -0.60283098 -0.12454329 [67,] -0.09212320 -0.60283098 [68,] 1.02877772 -0.09212320 [69,] -0.70800487 1.02877772 [70,] -0.37203367 -0.70800487 [71,] -0.14123635 -0.37203367 [72,] -0.87705291 -0.14123635 [73,] -1.60283098 -0.87705291 [74,] 0.02877772 -1.60283098 [75,] -0.60283098 0.02877772 [76,] -0.44950997 -0.60283098 [77,] -0.21871265 -0.44950997 [78,] 0.90787680 -0.21871265 [79,] 0.04450476 0.90787680 [80,] -0.09212320 0.04450476 [81,] -0.12454329 -0.09212320 [82,] -0.20201959 -0.12454329 [83,] -0.81626967 -0.20201959 [84,] 0.29199513 -0.81626967 [85,] 0.02877772 0.29199513 [86,] -0.33961357 0.02877772 [87,] 0.25957504 -0.33961357 [88,] -0.37203367 0.25957504 [89,] -0.49293458 -0.37203367 [90,] 0.50706542 -0.49293458 [91,] -0.12454329 0.50706542 [92,] 0.39716902 -0.12454329 [93,] 0.39716902 0.39716902 [94,] 0.16540567 0.39716902 [95,] -0.33961357 0.16540567 [96,] -0.70800487 -0.33961357 [97,] -0.18629256 -0.70800487 [98,] -0.37203367 -0.18629256 [99,] 0.18209873 -0.37203367 [100,] 1.39716902 0.18209873 [101,] 0.55049003 1.39716902 [102,] 1.49133838 0.55049003 [103,] -0.70800487 1.49133838 [104,] 0.42958911 -0.70800487 [105,] 0.35374440 0.42958911 [106,] 0.62796633 0.35374440 [107,] -0.72373190 0.62796633 [108,] -0.39876522 -0.72373190 [109,] 0.12294709 -0.39876522 [110,] 0.70544264 0.12294709 [111,] -0.18629256 0.70544264 [112,] -0.12454329 -0.18629256 [113,] 0.10625403 -0.12454329 [114,] 0.87545671 0.10625403 [115,] 0.70381104 0.87545671 [116,] -0.33961357 0.70381104 [117,] -0.60283098 -0.33961357 [118,] -1.21871265 -0.60283098 [119,] 0.02877772 -1.21871265 [120,] 0.39716902 0.02877772 [121,] -0.58710395 0.39716902 [122,] 0.62796633 -0.58710395 [123,] 0.64465939 0.62796633 [124,] 0.04450476 0.64465939 [125,] -0.35534061 0.04450476 [126,] -0.60283098 -0.35534061 [127,] 0.50706542 -0.60283098 [128,] 1.29199513 0.50706542 [129,] 0.89214977 1.29199513 [130,] 0.01208466 0.89214977 [131,] -0.33961357 0.01208466 [132,] 0.27626810 -0.33961357 [133,] -0.12454329 0.27626810 [134,] 0.66038643 -0.12454329 [135,] 0.62796633 0.66038643 [136,] -0.12454329 0.62796633 [137,] 0.55049003 -0.12454329 [138,] 0.87545671 0.55049003 [139,] 0.39716902 0.87545671 [140,] -0.37203367 0.39716902 [141,] -0.35534061 -0.37203367 [142,] -0.72373190 -0.35534061 [143,] 0.50706542 -0.72373190 [144,] -0.70800487 0.50706542 [145,] -0.33961357 -0.70800487 [146,] 0.64465939 -0.33961357 [147,] 0.39716902 0.64465939 [148,] 0.02877772 0.39716902 [149,] 0.02877772 0.02877772 [150,] 0.62796633 0.02877772 [151,] -0.49293458 0.62796633 [152,] -0.35534061 -0.49293458 [153,] 0.35374440 -0.35534061 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -0.33961357 -0.35534061 2 1.19879179 -0.33961357 3 -1.32292051 1.19879179 4 -0.81790127 -1.32292051 5 -0.10881625 -0.81790127 6 -0.75615200 -0.10881625 7 -0.87705291 -0.75615200 8 -1.60283098 -0.87705291 9 0.13867412 -1.60283098 10 0.39716902 0.13867412 11 0.18209873 0.39716902 12 0.39716902 0.18209873 13 -1.10785023 0.39716902 14 1.04450476 -1.10785023 15 -0.10785023 1.04450476 16 0.25957504 -0.10785023 17 0.64465939 0.25957504 18 -0.18629256 0.64465939 19 -0.57041089 -0.18629256 20 -0.16959950 -0.57041089 21 -0.37203367 -0.16959950 22 0.62796633 -0.37203367 23 -0.18629256 0.62796633 24 -0.60283098 -0.18629256 25 0.24384800 -0.60283098 26 -0.60283098 0.24384800 27 -0.35534061 -0.60283098 28 -0.35534061 -0.35534061 29 -0.33961357 -0.35534061 30 -0.33961357 -0.33961357 31 0.89214977 -0.33961357 32 -0.37203367 0.89214977 33 0.90787680 -0.37203367 34 -0.98791534 0.90787680 35 0.39716902 -0.98791534 36 0.52375848 0.39716902 37 -0.33961357 0.52375848 38 -0.35534061 -0.33961357 39 0.39716902 -0.35534061 40 1.02877772 0.39716902 41 0.29199513 1.02877772 42 -1.58710395 0.29199513 43 -0.64625560 -1.58710395 44 0.90787680 -0.64625560 45 -0.20201959 0.90787680 46 0.62796633 -0.20201959 47 0.06119782 0.62796633 48 0.01208466 0.06119782 49 0.39716902 0.01208466 50 0.29199513 0.39716902 51 -1.83362830 0.29199513 52 0.01208466 -1.83362830 53 -0.41708988 0.01208466 54 0.85713205 -0.41708988 55 -0.35534061 0.85713205 56 0.12294709 -0.35534061 57 0.39716902 0.12294709 58 1.66038643 0.39716902 59 0.62796633 1.66038643 60 -0.33961357 0.62796633 61 0.39716902 -0.33961357 62 -0.23443969 0.39716902 63 0.78128735 -0.23443969 64 0.13867412 0.78128735 65 -0.12454329 0.13867412 66 -0.60283098 -0.12454329 67 -0.09212320 -0.60283098 68 1.02877772 -0.09212320 69 -0.70800487 1.02877772 70 -0.37203367 -0.70800487 71 -0.14123635 -0.37203367 72 -0.87705291 -0.14123635 73 -1.60283098 -0.87705291 74 0.02877772 -1.60283098 75 -0.60283098 0.02877772 76 -0.44950997 -0.60283098 77 -0.21871265 -0.44950997 78 0.90787680 -0.21871265 79 0.04450476 0.90787680 80 -0.09212320 0.04450476 81 -0.12454329 -0.09212320 82 -0.20201959 -0.12454329 83 -0.81626967 -0.20201959 84 0.29199513 -0.81626967 85 0.02877772 0.29199513 86 -0.33961357 0.02877772 87 0.25957504 -0.33961357 88 -0.37203367 0.25957504 89 -0.49293458 -0.37203367 90 0.50706542 -0.49293458 91 -0.12454329 0.50706542 92 0.39716902 -0.12454329 93 0.39716902 0.39716902 94 0.16540567 0.39716902 95 -0.33961357 0.16540567 96 -0.70800487 -0.33961357 97 -0.18629256 -0.70800487 98 -0.37203367 -0.18629256 99 0.18209873 -0.37203367 100 1.39716902 0.18209873 101 0.55049003 1.39716902 102 1.49133838 0.55049003 103 -0.70800487 1.49133838 104 0.42958911 -0.70800487 105 0.35374440 0.42958911 106 0.62796633 0.35374440 107 -0.72373190 0.62796633 108 -0.39876522 -0.72373190 109 0.12294709 -0.39876522 110 0.70544264 0.12294709 111 -0.18629256 0.70544264 112 -0.12454329 -0.18629256 113 0.10625403 -0.12454329 114 0.87545671 0.10625403 115 0.70381104 0.87545671 116 -0.33961357 0.70381104 117 -0.60283098 -0.33961357 118 -1.21871265 -0.60283098 119 0.02877772 -1.21871265 120 0.39716902 0.02877772 121 -0.58710395 0.39716902 122 0.62796633 -0.58710395 123 0.64465939 0.62796633 124 0.04450476 0.64465939 125 -0.35534061 0.04450476 126 -0.60283098 -0.35534061 127 0.50706542 -0.60283098 128 1.29199513 0.50706542 129 0.89214977 1.29199513 130 0.01208466 0.89214977 131 -0.33961357 0.01208466 132 0.27626810 -0.33961357 133 -0.12454329 0.27626810 134 0.66038643 -0.12454329 135 0.62796633 0.66038643 136 -0.12454329 0.62796633 137 0.55049003 -0.12454329 138 0.87545671 0.55049003 139 0.39716902 0.87545671 140 -0.37203367 0.39716902 141 -0.35534061 -0.37203367 142 -0.72373190 -0.35534061 143 0.50706542 -0.72373190 144 -0.70800487 0.50706542 145 -0.33961357 -0.70800487 146 0.64465939 -0.33961357 147 0.39716902 0.64465939 148 0.02877772 0.39716902 149 0.02877772 0.02877772 150 0.62796633 0.02877772 151 -0.49293458 0.62796633 152 -0.35534061 -0.49293458 153 0.35374440 -0.35534061 > 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/freestat/rcomp/tmp/7tv731291196222.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/www/html/freestat/rcomp/tmp/8tv731291196222.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/www/html/freestat/rcomp/tmp/9tv731291196222.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/www/html/freestat/rcomp/tmp/104m761291196222.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/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/11p5nc1291196222.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/12tnm01291196222.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$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$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/137fjr1291196222.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$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/freestat/rcomp/tmp/14ay0x1291196222.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/freestat/rcomp/tmp/15egyk1291196222.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/freestat/rcomp/tmp/16zyfq1291196222.tab") + } > > try(system("convert tmp/1f3ad1291196222.ps tmp/1f3ad1291196222.png",intern=TRUE)) character(0) > try(system("convert tmp/2f3ad1291196222.ps tmp/2f3ad1291196222.png",intern=TRUE)) character(0) > try(system("convert tmp/3f3ad1291196222.ps tmp/3f3ad1291196222.png",intern=TRUE)) character(0) > try(system("convert tmp/48u9x1291196222.ps tmp/48u9x1291196222.png",intern=TRUE)) character(0) > try(system("convert tmp/58u9x1291196222.ps tmp/58u9x1291196222.png",intern=TRUE)) character(0) > try(system("convert tmp/6j4qi1291196222.ps tmp/6j4qi1291196222.png",intern=TRUE)) character(0) > try(system("convert tmp/7tv731291196222.ps tmp/7tv731291196222.png",intern=TRUE)) character(0) > try(system("convert tmp/8tv731291196222.ps tmp/8tv731291196222.png",intern=TRUE)) character(0) > try(system("convert tmp/9tv731291196222.ps tmp/9tv731291196222.png",intern=TRUE)) character(0) > try(system("convert tmp/104m761291196222.ps tmp/104m761291196222.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.444 2.701 5.780