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 + ,4 + ,4 + ,4 + ,3 + ,5 + ,5 + ,4 + ,2 + ,3 + ,4 + ,2 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,2 + ,2 + ,2 + ,4 + ,4 + ,3 + ,2 + ,3 + ,4 + ,2 + ,2 + ,3 + ,2 + ,2 + ,4 + ,1 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,5 + ,4 + ,2 + ,4 + ,2 + ,2 + ,2 + ,4 + ,3 + ,4 + ,4 + ,3 + ,3 + ,4 + ,3 + ,4 + ,3 + ,4 + ,2 + ,2 + ,3 + ,2 + ,4 + ,2 + ,4 + ,2 + ,2 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,2 + ,5 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,5 + ,4 + ,4 + ,5 + ,4 + ,4 + ,4 + ,4 + ,5 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,2 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,5 + ,5 + ,4 + ,4 + ,4 + ,3 + ,4 + ,2 + ,2 + ,2 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,2 + ,2 + ,4 + ,5 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,3 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,2 + ,4 + ,5 + ,4 + ,3 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,5 + ,2 + ,1 + ,3 + ,4 + ,3 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,4 + ,3 + ,3 + ,4 + ,4 + ,5 + ,4 + ,2 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,3 + ,4 + ,4 + ,2 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,2 + ,2 + ,4 + ,3 + ,2 + ,2 + ,5 + ,3 + ,4 + ,3 + ,2 + ,3 + ,3 + ,2 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,3 + ,4 + ,2 + ,2 + ,3 + ,4 + ,5 + ,4 + ,2 + ,2 + ,4 + ,3 + ,4 + ,4 + ,3 + ,4 + ,5 + ,5 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,2 + ,3 + ,3 + ,3 + ,2 + ,4 + ,3 + ,4 + ,4 + ,3 + ,3 + ,3 + ,4 + ,3 + ,2 + ,4 + ,3 + ,4 + ,2 + ,4 + ,3 + ,3 + ,1 + ,2 + ,3 + ,3 + ,3 + ,4 + ,2 + ,4 + ,4 + ,3 + ,4 + ,2 + ,2 + ,4 + ,3 + ,2 + ,2 + ,4 + ,2 + ,2 + ,4 + ,4 + ,3 + ,5 + ,5 + ,5 + ,3 + ,5 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,3 + ,3 + ,4 + ,2 + ,2 + ,3 + ,4 + ,4 + ,4 + ,3 + ,2 + ,4 + ,4 + ,3 + ,3 + ,5 + ,2 + ,4 + ,4 + ,2 + ,3 + ,3 + ,2 + ,4 + ,3 + ,4 + ,4 + ,3 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,3 + ,2 + ,4 + ,2 + ,4 + ,5 + ,3 + ,3 + ,2 + ,2 + ,2 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,3 + ,3 + ,4 + ,3 + ,4 + ,4 + ,3 + ,4 + ,4 + ,3 + ,3 + ,5 + ,4 + ,4 + ,3 + ,5 + ,1 + ,4 + ,2 + ,3 + ,4 + ,2 + ,4 + ,4 + ,4 + ,4 + ,5 + ,3 + ,4 + ,3 + ,3 + ,4 + ,2 + ,1 + ,3 + ,4 + ,2 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,5 + ,5 + ,4 + ,3 + ,2 + ,4 + ,3 + ,4 + ,3 + ,3 + ,3 + ,4 + ,5 + ,2 + ,4 + ,4 + ,4 + ,3 + ,2 + ,2 + ,3) + ,dim=c(3 + ,159) + ,dimnames=list(c('Competent' + ,'Goals' + ,'Focus') + ,1:159)) > y <- array(NA,dim=c(3,159),dimnames=list(c('Competent','Goals','Focus'),1:159)) > 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 = '2' > #'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 Goals Competent Focus 1 4 4 4 2 4 4 3 3 5 5 4 4 3 2 4 5 4 2 4 6 3 4 4 7 4 4 4 8 3 4 4 9 2 4 2 10 4 2 4 11 2 3 3 12 2 4 2 13 2 3 2 14 1 4 3 15 4 4 4 16 4 4 5 17 2 4 4 18 2 2 2 19 3 4 4 20 3 4 3 21 3 4 4 22 4 3 2 23 3 2 2 24 2 4 4 25 2 2 4 26 4 3 4 27 4 4 4 28 3 3 3 29 4 4 4 30 2 4 5 31 4 4 4 32 4 4 4 33 5 4 4 34 5 4 4 35 4 4 4 36 4 5 4 37 4 4 4 38 2 2 4 39 4 4 4 40 4 4 5 41 4 5 4 42 3 4 4 43 2 2 2 44 3 4 4 45 4 4 4 46 3 4 4 47 2 2 4 48 4 5 4 49 4 4 4 50 3 4 4 51 4 4 3 52 3 4 4 53 4 4 4 54 2 3 4 55 4 5 3 56 4 4 3 57 4 4 4 58 4 4 4 59 3 4 5 60 1 2 3 61 3 4 4 62 3 4 4 63 4 4 4 64 2 4 4 65 3 3 4 66 5 4 4 67 4 2 4 68 4 4 4 69 3 4 4 70 4 4 4 71 2 4 4 72 3 4 4 73 4 4 4 74 3 3 3 75 4 4 4 76 4 4 4 77 3 4 3 78 3 4 4 79 2 4 4 80 4 4 4 81 3 4 4 82 2 2 4 83 2 3 2 84 3 5 4 85 2 3 3 86 2 3 3 87 4 4 4 88 4 4 4 89 4 4 4 90 2 4 3 91 2 4 2 92 4 3 5 93 2 4 2 94 3 4 4 95 3 4 4 96 5 5 4 97 3 4 3 98 4 4 4 99 3 2 3 100 2 3 4 101 4 3 4 102 3 3 3 103 3 4 2 104 3 4 4 105 4 2 3 106 1 3 2 107 3 3 3 108 2 4 4 109 3 4 4 110 2 2 4 111 2 3 2 112 2 4 2 113 4 4 3 114 5 5 5 115 5 3 4 116 3 3 4 117 4 4 4 118 4 3 4 119 3 3 4 120 2 2 3 121 4 4 4 122 2 3 4 123 3 4 3 124 2 5 4 125 2 4 3 126 2 3 4 127 4 3 4 128 4 3 4 129 4 3 4 130 4 4 4 131 3 4 4 132 2 3 4 133 4 2 5 134 3 3 2 135 2 2 4 136 4 4 4 137 3 4 3 138 3 4 3 139 3 4 4 140 3 4 4 141 3 4 3 142 4 5 4 143 5 3 1 144 2 4 3 145 2 4 4 146 4 4 4 147 3 5 4 148 3 3 4 149 1 2 3 150 2 4 4 151 4 3 4 152 4 4 4 153 5 5 4 154 2 3 4 155 4 3 3 156 3 3 4 157 2 5 4 158 4 4 3 159 2 2 3 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Competent Focus 0.7797 0.3112 0.3496 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -2.07317 -0.72358 -0.07317 0.57724 2.93717 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.77974 0.42660 1.828 0.069488 . Competent 0.31117 0.08906 3.494 0.000620 *** Focus 0.34959 0.09754 3.584 0.000452 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.8832 on 156 degrees of freedom Multiple R-squared: 0.1725, Adjusted R-squared: 0.1619 F-statistic: 16.26 on 2 and 156 DF, p-value: 3.855e-07 > 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,] 0.53324526 0.93350947 0.4667547 [2,] 0.36375549 0.72751098 0.6362445 [3,] 0.38991309 0.77982619 0.6100869 [4,] 0.42058217 0.84116435 0.5794178 [5,] 0.36368159 0.72736318 0.6363184 [6,] 0.36597645 0.73195289 0.6340236 [7,] 0.27411480 0.54822959 0.7258852 [8,] 0.19851492 0.39702985 0.8014851 [9,] 0.55999377 0.88001247 0.4400062 [10,] 0.47870990 0.95741980 0.5212901 [11,] 0.44125547 0.88251095 0.5587445 [12,] 0.62370124 0.75259752 0.3762988 [13,] 0.55131721 0.89736557 0.4486828 [14,] 0.49857455 0.99714911 0.5014254 [15,] 0.43060252 0.86120503 0.5693975 [16,] 0.38015603 0.76031207 0.6198440 [17,] 0.62075826 0.75848347 0.3792417 [18,] 0.59466470 0.81067060 0.4053353 [19,] 0.67877394 0.64245211 0.3212261 [20,] 0.72705497 0.54589006 0.2729450 [21,] 0.71105850 0.57788300 0.2889415 [22,] 0.68317114 0.63365771 0.3168289 [23,] 0.62803881 0.74392238 0.3719612 [24,] 0.59584954 0.80830091 0.4041505 [25,] 0.74626970 0.50746060 0.2537303 [26,] 0.72456630 0.55086741 0.2754337 [27,] 0.70017303 0.59965394 0.2998270 [28,] 0.79539360 0.40921281 0.2046064 [29,] 0.86115334 0.27769332 0.1388467 [30,] 0.83942292 0.32115416 0.1605771 [31,] 0.80811053 0.38377893 0.1918895 [32,] 0.78111701 0.43776599 0.2188830 [33,] 0.79272012 0.41455976 0.2072799 [34,] 0.76509770 0.46980461 0.2349023 [35,] 0.72352312 0.55295375 0.2764769 [36,] 0.68049314 0.63901373 0.3195069 [37,] 0.64765549 0.70468902 0.3523445 [38,] 0.60004352 0.79991296 0.3999565 [39,] 0.56478954 0.87042092 0.4352105 [40,] 0.53048788 0.93902425 0.4695121 [41,] 0.49490275 0.98980551 0.5050972 [42,] 0.49617553 0.99235106 0.5038245 [43,] 0.44874828 0.89749656 0.5512517 [44,] 0.41616282 0.83232563 0.5838372 [45,] 0.38225466 0.76450931 0.6177453 [46,] 0.38147324 0.76294647 0.6185268 [47,] 0.34883965 0.69767930 0.6511603 [48,] 0.31972410 0.63944821 0.6802759 [49,] 0.35085616 0.70171232 0.6491438 [50,] 0.32283988 0.64567977 0.6771601 [51,] 0.32042809 0.64085619 0.6795719 [52,] 0.29314277 0.58628555 0.7068572 [53,] 0.26705346 0.53410692 0.7329465 [54,] 0.26001850 0.52003700 0.7399815 [55,] 0.32921175 0.65842351 0.6707882 [56,] 0.29889009 0.59778018 0.7011099 [57,] 0.26968660 0.53937321 0.7303134 [58,] 0.24632047 0.49264094 0.7536795 [59,] 0.31402852 0.62805704 0.6859715 [60,] 0.27395622 0.54791244 0.7260438 [61,] 0.36133674 0.72267348 0.6386633 [62,] 0.40386282 0.80772564 0.5961372 [63,] 0.37687105 0.75374211 0.6231289 [64,] 0.34490409 0.68980819 0.6550959 [65,] 0.31975024 0.63950048 0.6802498 [66,] 0.39056298 0.78112595 0.6094370 [67,] 0.35751166 0.71502331 0.6424883 [68,] 0.33254447 0.66508894 0.6674555 [69,] 0.29418345 0.58836690 0.7058166 [70,] 0.27150207 0.54300415 0.7284979 [71,] 0.24994258 0.49988517 0.7500574 [72,] 0.21593677 0.43187354 0.7840632 [73,] 0.19135258 0.38270517 0.8086474 [74,] 0.24466427 0.48932854 0.7553357 [75,] 0.22457875 0.44915751 0.7754212 [76,] 0.19894415 0.39788831 0.8010558 [77,] 0.19200616 0.38401232 0.8079938 [78,] 0.16938879 0.33877759 0.8306112 [79,] 0.16074410 0.32148819 0.8392559 [80,] 0.15352731 0.30705462 0.8464727 [81,] 0.14642725 0.29285449 0.8535728 [82,] 0.13207490 0.26414979 0.8679251 [83,] 0.11886403 0.23772807 0.8811360 [84,] 0.10677062 0.21354125 0.8932294 [85,] 0.11613824 0.23227648 0.8838618 [86,] 0.10851188 0.21702376 0.8914881 [87,] 0.09610799 0.19221597 0.9038920 [88,] 0.09004372 0.18008745 0.9099563 [89,] 0.07593659 0.15187318 0.9240634 [90,] 0.06354770 0.12709539 0.9364523 [91,] 0.08236996 0.16473992 0.9176300 [92,] 0.06609464 0.13218929 0.9339054 [93,] 0.05884793 0.11769587 0.9411521 [94,] 0.05044158 0.10088317 0.9495584 [95,] 0.05648882 0.11297764 0.9435112 [96,] 0.05664160 0.11328319 0.9433584 [97,] 0.04513238 0.09026476 0.9548676 [98,] 0.03575407 0.07150813 0.9642459 [99,] 0.02873027 0.05746055 0.9712697 [100,] 0.04571472 0.09142944 0.9542853 [101,] 0.06867331 0.13734661 0.9313267 [102,] 0.05480802 0.10961605 0.9451920 [103,] 0.07397448 0.14794895 0.9260255 [104,] 0.06089538 0.12179076 0.9391046 [105,] 0.05764569 0.11529137 0.9423543 [106,] 0.04988365 0.09976730 0.9501163 [107,] 0.05031583 0.10063166 0.9496842 [108,] 0.04855834 0.09711668 0.9514417 [109,] 0.05978383 0.11956766 0.9402162 [110,] 0.13512674 0.27025347 0.8648733 [111,] 0.10956528 0.21913055 0.8904347 [112,] 0.10147646 0.20295291 0.8985235 [113,] 0.10657846 0.21315693 0.8934215 [114,] 0.08490831 0.16981663 0.9150917 [115,] 0.07583060 0.15166119 0.9241694 [116,] 0.07112200 0.14224400 0.9288780 [117,] 0.07519740 0.15039481 0.9248026 [118,] 0.05838372 0.11676744 0.9416163 [119,] 0.09025088 0.18050175 0.9097491 [120,] 0.10922537 0.21845075 0.8907746 [121,] 0.11643465 0.23286930 0.8835653 [122,] 0.11980233 0.23960467 0.8801977 [123,] 0.12641663 0.25283326 0.8735834 [124,] 0.13764213 0.27528426 0.8623579 [125,] 0.12961028 0.25922056 0.8703897 [126,] 0.10263563 0.20527127 0.8973644 [127,] 0.10220256 0.20440513 0.8977974 [128,] 0.19528346 0.39056691 0.8047165 [129,] 0.16538833 0.33077665 0.8346117 [130,] 0.13439718 0.26879435 0.8656028 [131,] 0.13418038 0.26836076 0.8658196 [132,] 0.10817623 0.21635247 0.8918238 [133,] 0.08676470 0.17352940 0.9132353 [134,] 0.06355133 0.12710267 0.9364487 [135,] 0.04517886 0.09035773 0.9548211 [136,] 0.03454291 0.06908583 0.9654571 [137,] 0.02469962 0.04939924 0.9753004 [138,] 0.06297071 0.12594142 0.9370293 [139,] 0.07161017 0.14322035 0.9283898 [140,] 0.08718507 0.17437014 0.9128149 [141,] 0.07392379 0.14784759 0.9260762 [142,] 0.06131483 0.12262965 0.9386852 [143,] 0.04007560 0.08015121 0.9599244 [144,] 0.07176841 0.14353681 0.9282316 [145,] 0.09696926 0.19393853 0.9030307 [146,] 0.11968486 0.23936972 0.8803151 [147,] 0.10132976 0.20265952 0.8986702 [148,] 0.28131506 0.56263013 0.7186849 > postscript(file="/var/www/html/freestat/rcomp/tmp/1fn6g1291304774.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/2fn6g1291304774.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/38w5i1291304774.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/48w5i1291304774.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/58w5i1291304774.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 = 159 Frequency = 1 1 2 3 4 5 6 0.57723994 0.92682905 1.26607429 0.19957123 1.19957123 -0.42276006 7 8 9 10 11 12 0.57723994 -0.42276006 -0.72358184 1.19957123 -0.76200530 -0.72358184 13 14 15 16 17 18 -0.41241619 -2.07317095 0.57723994 0.22765083 -1.42276006 -0.10125054 19 20 21 22 23 24 -0.42276006 -0.07317095 -0.42276006 1.58758381 0.89874946 -1.42276006 25 26 27 28 29 30 -0.80042877 0.88840559 0.57723994 0.23799470 0.57723994 -1.77234917 31 32 33 34 35 36 0.57723994 0.57723994 1.57723994 1.57723994 0.57723994 0.26607429 37 38 39 40 41 42 0.57723994 -0.80042877 0.57723994 0.22765083 0.26607429 -0.42276006 43 44 45 46 47 48 -0.10125054 -0.42276006 0.57723994 -0.42276006 -0.80042877 0.26607429 49 50 51 52 53 54 0.57723994 -0.42276006 0.92682905 -0.42276006 0.57723994 -1.11159441 55 56 57 58 59 60 0.61566341 0.92682905 0.57723994 0.57723994 -0.77234917 -1.45083965 61 62 63 64 65 66 -0.42276006 -0.42276006 0.57723994 -1.42276006 -0.11159441 1.57723994 67 68 69 70 71 72 1.19957123 0.57723994 -0.42276006 0.57723994 -1.42276006 -0.42276006 73 74 75 76 77 78 0.57723994 0.23799470 0.57723994 0.57723994 -0.07317095 -0.42276006 79 80 81 82 83 84 -1.42276006 0.57723994 -0.42276006 -0.80042877 -0.41241619 -0.73392571 85 86 87 88 89 90 -0.76200530 -0.76200530 0.57723994 0.57723994 0.57723994 -1.07317095 91 92 93 94 95 96 -0.72358184 0.53881648 -0.72358184 -0.42276006 -0.42276006 1.26607429 97 98 99 100 101 102 -0.07317095 0.57723994 0.54916035 -1.11159441 0.88840559 0.23799470 103 104 105 106 107 108 0.27641816 -0.42276006 1.54916035 -1.41241619 0.23799470 -1.42276006 109 110 111 112 113 114 -0.42276006 -0.80042877 -0.41241619 -0.72358184 0.92682905 0.91648518 115 116 117 118 119 120 1.88840559 -0.11159441 0.57723994 0.88840559 -0.11159441 -0.45083965 121 122 123 124 125 126 0.57723994 -1.11159441 -0.07317095 -1.73392571 -1.07317095 -1.11159441 127 128 129 130 131 132 0.88840559 0.88840559 0.88840559 0.57723994 -0.42276006 -1.11159441 133 134 135 136 137 138 0.84998212 0.58758381 -0.80042877 0.57723994 -0.07317095 -0.07317095 139 140 141 142 143 144 -0.42276006 -0.42276006 -0.07317095 0.26607429 2.93717292 -1.07317095 145 146 147 148 149 150 -1.42276006 0.57723994 -0.73392571 -0.11159441 -1.45083965 -1.42276006 151 152 153 154 155 156 0.88840559 0.57723994 1.26607429 -1.11159441 1.23799470 -0.11159441 157 158 159 -1.73392571 0.92682905 -0.45083965 > postscript(file="/var/www/html/freestat/rcomp/tmp/60o531291304774.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 = 159 Frequency = 1 lag(myerror, k = 1) myerror 0 0.57723994 NA 1 0.92682905 0.57723994 2 1.26607429 0.92682905 3 0.19957123 1.26607429 4 1.19957123 0.19957123 5 -0.42276006 1.19957123 6 0.57723994 -0.42276006 7 -0.42276006 0.57723994 8 -0.72358184 -0.42276006 9 1.19957123 -0.72358184 10 -0.76200530 1.19957123 11 -0.72358184 -0.76200530 12 -0.41241619 -0.72358184 13 -2.07317095 -0.41241619 14 0.57723994 -2.07317095 15 0.22765083 0.57723994 16 -1.42276006 0.22765083 17 -0.10125054 -1.42276006 18 -0.42276006 -0.10125054 19 -0.07317095 -0.42276006 20 -0.42276006 -0.07317095 21 1.58758381 -0.42276006 22 0.89874946 1.58758381 23 -1.42276006 0.89874946 24 -0.80042877 -1.42276006 25 0.88840559 -0.80042877 26 0.57723994 0.88840559 27 0.23799470 0.57723994 28 0.57723994 0.23799470 29 -1.77234917 0.57723994 30 0.57723994 -1.77234917 31 0.57723994 0.57723994 32 1.57723994 0.57723994 33 1.57723994 1.57723994 34 0.57723994 1.57723994 35 0.26607429 0.57723994 36 0.57723994 0.26607429 37 -0.80042877 0.57723994 38 0.57723994 -0.80042877 39 0.22765083 0.57723994 40 0.26607429 0.22765083 41 -0.42276006 0.26607429 42 -0.10125054 -0.42276006 43 -0.42276006 -0.10125054 44 0.57723994 -0.42276006 45 -0.42276006 0.57723994 46 -0.80042877 -0.42276006 47 0.26607429 -0.80042877 48 0.57723994 0.26607429 49 -0.42276006 0.57723994 50 0.92682905 -0.42276006 51 -0.42276006 0.92682905 52 0.57723994 -0.42276006 53 -1.11159441 0.57723994 54 0.61566341 -1.11159441 55 0.92682905 0.61566341 56 0.57723994 0.92682905 57 0.57723994 0.57723994 58 -0.77234917 0.57723994 59 -1.45083965 -0.77234917 60 -0.42276006 -1.45083965 61 -0.42276006 -0.42276006 62 0.57723994 -0.42276006 63 -1.42276006 0.57723994 64 -0.11159441 -1.42276006 65 1.57723994 -0.11159441 66 1.19957123 1.57723994 67 0.57723994 1.19957123 68 -0.42276006 0.57723994 69 0.57723994 -0.42276006 70 -1.42276006 0.57723994 71 -0.42276006 -1.42276006 72 0.57723994 -0.42276006 73 0.23799470 0.57723994 74 0.57723994 0.23799470 75 0.57723994 0.57723994 76 -0.07317095 0.57723994 77 -0.42276006 -0.07317095 78 -1.42276006 -0.42276006 79 0.57723994 -1.42276006 80 -0.42276006 0.57723994 81 -0.80042877 -0.42276006 82 -0.41241619 -0.80042877 83 -0.73392571 -0.41241619 84 -0.76200530 -0.73392571 85 -0.76200530 -0.76200530 86 0.57723994 -0.76200530 87 0.57723994 0.57723994 88 0.57723994 0.57723994 89 -1.07317095 0.57723994 90 -0.72358184 -1.07317095 91 0.53881648 -0.72358184 92 -0.72358184 0.53881648 93 -0.42276006 -0.72358184 94 -0.42276006 -0.42276006 95 1.26607429 -0.42276006 96 -0.07317095 1.26607429 97 0.57723994 -0.07317095 98 0.54916035 0.57723994 99 -1.11159441 0.54916035 100 0.88840559 -1.11159441 101 0.23799470 0.88840559 102 0.27641816 0.23799470 103 -0.42276006 0.27641816 104 1.54916035 -0.42276006 105 -1.41241619 1.54916035 106 0.23799470 -1.41241619 107 -1.42276006 0.23799470 108 -0.42276006 -1.42276006 109 -0.80042877 -0.42276006 110 -0.41241619 -0.80042877 111 -0.72358184 -0.41241619 112 0.92682905 -0.72358184 113 0.91648518 0.92682905 114 1.88840559 0.91648518 115 -0.11159441 1.88840559 116 0.57723994 -0.11159441 117 0.88840559 0.57723994 118 -0.11159441 0.88840559 119 -0.45083965 -0.11159441 120 0.57723994 -0.45083965 121 -1.11159441 0.57723994 122 -0.07317095 -1.11159441 123 -1.73392571 -0.07317095 124 -1.07317095 -1.73392571 125 -1.11159441 -1.07317095 126 0.88840559 -1.11159441 127 0.88840559 0.88840559 128 0.88840559 0.88840559 129 0.57723994 0.88840559 130 -0.42276006 0.57723994 131 -1.11159441 -0.42276006 132 0.84998212 -1.11159441 133 0.58758381 0.84998212 134 -0.80042877 0.58758381 135 0.57723994 -0.80042877 136 -0.07317095 0.57723994 137 -0.07317095 -0.07317095 138 -0.42276006 -0.07317095 139 -0.42276006 -0.42276006 140 -0.07317095 -0.42276006 141 0.26607429 -0.07317095 142 2.93717292 0.26607429 143 -1.07317095 2.93717292 144 -1.42276006 -1.07317095 145 0.57723994 -1.42276006 146 -0.73392571 0.57723994 147 -0.11159441 -0.73392571 148 -1.45083965 -0.11159441 149 -1.42276006 -1.45083965 150 0.88840559 -1.42276006 151 0.57723994 0.88840559 152 1.26607429 0.57723994 153 -1.11159441 1.26607429 154 1.23799470 -1.11159441 155 -0.11159441 1.23799470 156 -1.73392571 -0.11159441 157 0.92682905 -1.73392571 158 -0.45083965 0.92682905 159 NA -0.45083965 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 0.92682905 0.57723994 [2,] 1.26607429 0.92682905 [3,] 0.19957123 1.26607429 [4,] 1.19957123 0.19957123 [5,] -0.42276006 1.19957123 [6,] 0.57723994 -0.42276006 [7,] -0.42276006 0.57723994 [8,] -0.72358184 -0.42276006 [9,] 1.19957123 -0.72358184 [10,] -0.76200530 1.19957123 [11,] -0.72358184 -0.76200530 [12,] -0.41241619 -0.72358184 [13,] -2.07317095 -0.41241619 [14,] 0.57723994 -2.07317095 [15,] 0.22765083 0.57723994 [16,] -1.42276006 0.22765083 [17,] -0.10125054 -1.42276006 [18,] -0.42276006 -0.10125054 [19,] -0.07317095 -0.42276006 [20,] -0.42276006 -0.07317095 [21,] 1.58758381 -0.42276006 [22,] 0.89874946 1.58758381 [23,] -1.42276006 0.89874946 [24,] -0.80042877 -1.42276006 [25,] 0.88840559 -0.80042877 [26,] 0.57723994 0.88840559 [27,] 0.23799470 0.57723994 [28,] 0.57723994 0.23799470 [29,] -1.77234917 0.57723994 [30,] 0.57723994 -1.77234917 [31,] 0.57723994 0.57723994 [32,] 1.57723994 0.57723994 [33,] 1.57723994 1.57723994 [34,] 0.57723994 1.57723994 [35,] 0.26607429 0.57723994 [36,] 0.57723994 0.26607429 [37,] -0.80042877 0.57723994 [38,] 0.57723994 -0.80042877 [39,] 0.22765083 0.57723994 [40,] 0.26607429 0.22765083 [41,] -0.42276006 0.26607429 [42,] -0.10125054 -0.42276006 [43,] -0.42276006 -0.10125054 [44,] 0.57723994 -0.42276006 [45,] -0.42276006 0.57723994 [46,] -0.80042877 -0.42276006 [47,] 0.26607429 -0.80042877 [48,] 0.57723994 0.26607429 [49,] -0.42276006 0.57723994 [50,] 0.92682905 -0.42276006 [51,] -0.42276006 0.92682905 [52,] 0.57723994 -0.42276006 [53,] -1.11159441 0.57723994 [54,] 0.61566341 -1.11159441 [55,] 0.92682905 0.61566341 [56,] 0.57723994 0.92682905 [57,] 0.57723994 0.57723994 [58,] -0.77234917 0.57723994 [59,] -1.45083965 -0.77234917 [60,] -0.42276006 -1.45083965 [61,] -0.42276006 -0.42276006 [62,] 0.57723994 -0.42276006 [63,] -1.42276006 0.57723994 [64,] -0.11159441 -1.42276006 [65,] 1.57723994 -0.11159441 [66,] 1.19957123 1.57723994 [67,] 0.57723994 1.19957123 [68,] -0.42276006 0.57723994 [69,] 0.57723994 -0.42276006 [70,] -1.42276006 0.57723994 [71,] -0.42276006 -1.42276006 [72,] 0.57723994 -0.42276006 [73,] 0.23799470 0.57723994 [74,] 0.57723994 0.23799470 [75,] 0.57723994 0.57723994 [76,] -0.07317095 0.57723994 [77,] -0.42276006 -0.07317095 [78,] -1.42276006 -0.42276006 [79,] 0.57723994 -1.42276006 [80,] -0.42276006 0.57723994 [81,] -0.80042877 -0.42276006 [82,] -0.41241619 -0.80042877 [83,] -0.73392571 -0.41241619 [84,] -0.76200530 -0.73392571 [85,] -0.76200530 -0.76200530 [86,] 0.57723994 -0.76200530 [87,] 0.57723994 0.57723994 [88,] 0.57723994 0.57723994 [89,] -1.07317095 0.57723994 [90,] -0.72358184 -1.07317095 [91,] 0.53881648 -0.72358184 [92,] -0.72358184 0.53881648 [93,] -0.42276006 -0.72358184 [94,] -0.42276006 -0.42276006 [95,] 1.26607429 -0.42276006 [96,] -0.07317095 1.26607429 [97,] 0.57723994 -0.07317095 [98,] 0.54916035 0.57723994 [99,] -1.11159441 0.54916035 [100,] 0.88840559 -1.11159441 [101,] 0.23799470 0.88840559 [102,] 0.27641816 0.23799470 [103,] -0.42276006 0.27641816 [104,] 1.54916035 -0.42276006 [105,] -1.41241619 1.54916035 [106,] 0.23799470 -1.41241619 [107,] -1.42276006 0.23799470 [108,] -0.42276006 -1.42276006 [109,] -0.80042877 -0.42276006 [110,] -0.41241619 -0.80042877 [111,] -0.72358184 -0.41241619 [112,] 0.92682905 -0.72358184 [113,] 0.91648518 0.92682905 [114,] 1.88840559 0.91648518 [115,] -0.11159441 1.88840559 [116,] 0.57723994 -0.11159441 [117,] 0.88840559 0.57723994 [118,] -0.11159441 0.88840559 [119,] -0.45083965 -0.11159441 [120,] 0.57723994 -0.45083965 [121,] -1.11159441 0.57723994 [122,] -0.07317095 -1.11159441 [123,] -1.73392571 -0.07317095 [124,] -1.07317095 -1.73392571 [125,] -1.11159441 -1.07317095 [126,] 0.88840559 -1.11159441 [127,] 0.88840559 0.88840559 [128,] 0.88840559 0.88840559 [129,] 0.57723994 0.88840559 [130,] -0.42276006 0.57723994 [131,] -1.11159441 -0.42276006 [132,] 0.84998212 -1.11159441 [133,] 0.58758381 0.84998212 [134,] -0.80042877 0.58758381 [135,] 0.57723994 -0.80042877 [136,] -0.07317095 0.57723994 [137,] -0.07317095 -0.07317095 [138,] -0.42276006 -0.07317095 [139,] -0.42276006 -0.42276006 [140,] -0.07317095 -0.42276006 [141,] 0.26607429 -0.07317095 [142,] 2.93717292 0.26607429 [143,] -1.07317095 2.93717292 [144,] -1.42276006 -1.07317095 [145,] 0.57723994 -1.42276006 [146,] -0.73392571 0.57723994 [147,] -0.11159441 -0.73392571 [148,] -1.45083965 -0.11159441 [149,] -1.42276006 -1.45083965 [150,] 0.88840559 -1.42276006 [151,] 0.57723994 0.88840559 [152,] 1.26607429 0.57723994 [153,] -1.11159441 1.26607429 [154,] 1.23799470 -1.11159441 [155,] -0.11159441 1.23799470 [156,] -1.73392571 -0.11159441 [157,] 0.92682905 -1.73392571 [158,] -0.45083965 0.92682905 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 0.92682905 0.57723994 2 1.26607429 0.92682905 3 0.19957123 1.26607429 4 1.19957123 0.19957123 5 -0.42276006 1.19957123 6 0.57723994 -0.42276006 7 -0.42276006 0.57723994 8 -0.72358184 -0.42276006 9 1.19957123 -0.72358184 10 -0.76200530 1.19957123 11 -0.72358184 -0.76200530 12 -0.41241619 -0.72358184 13 -2.07317095 -0.41241619 14 0.57723994 -2.07317095 15 0.22765083 0.57723994 16 -1.42276006 0.22765083 17 -0.10125054 -1.42276006 18 -0.42276006 -0.10125054 19 -0.07317095 -0.42276006 20 -0.42276006 -0.07317095 21 1.58758381 -0.42276006 22 0.89874946 1.58758381 23 -1.42276006 0.89874946 24 -0.80042877 -1.42276006 25 0.88840559 -0.80042877 26 0.57723994 0.88840559 27 0.23799470 0.57723994 28 0.57723994 0.23799470 29 -1.77234917 0.57723994 30 0.57723994 -1.77234917 31 0.57723994 0.57723994 32 1.57723994 0.57723994 33 1.57723994 1.57723994 34 0.57723994 1.57723994 35 0.26607429 0.57723994 36 0.57723994 0.26607429 37 -0.80042877 0.57723994 38 0.57723994 -0.80042877 39 0.22765083 0.57723994 40 0.26607429 0.22765083 41 -0.42276006 0.26607429 42 -0.10125054 -0.42276006 43 -0.42276006 -0.10125054 44 0.57723994 -0.42276006 45 -0.42276006 0.57723994 46 -0.80042877 -0.42276006 47 0.26607429 -0.80042877 48 0.57723994 0.26607429 49 -0.42276006 0.57723994 50 0.92682905 -0.42276006 51 -0.42276006 0.92682905 52 0.57723994 -0.42276006 53 -1.11159441 0.57723994 54 0.61566341 -1.11159441 55 0.92682905 0.61566341 56 0.57723994 0.92682905 57 0.57723994 0.57723994 58 -0.77234917 0.57723994 59 -1.45083965 -0.77234917 60 -0.42276006 -1.45083965 61 -0.42276006 -0.42276006 62 0.57723994 -0.42276006 63 -1.42276006 0.57723994 64 -0.11159441 -1.42276006 65 1.57723994 -0.11159441 66 1.19957123 1.57723994 67 0.57723994 1.19957123 68 -0.42276006 0.57723994 69 0.57723994 -0.42276006 70 -1.42276006 0.57723994 71 -0.42276006 -1.42276006 72 0.57723994 -0.42276006 73 0.23799470 0.57723994 74 0.57723994 0.23799470 75 0.57723994 0.57723994 76 -0.07317095 0.57723994 77 -0.42276006 -0.07317095 78 -1.42276006 -0.42276006 79 0.57723994 -1.42276006 80 -0.42276006 0.57723994 81 -0.80042877 -0.42276006 82 -0.41241619 -0.80042877 83 -0.73392571 -0.41241619 84 -0.76200530 -0.73392571 85 -0.76200530 -0.76200530 86 0.57723994 -0.76200530 87 0.57723994 0.57723994 88 0.57723994 0.57723994 89 -1.07317095 0.57723994 90 -0.72358184 -1.07317095 91 0.53881648 -0.72358184 92 -0.72358184 0.53881648 93 -0.42276006 -0.72358184 94 -0.42276006 -0.42276006 95 1.26607429 -0.42276006 96 -0.07317095 1.26607429 97 0.57723994 -0.07317095 98 0.54916035 0.57723994 99 -1.11159441 0.54916035 100 0.88840559 -1.11159441 101 0.23799470 0.88840559 102 0.27641816 0.23799470 103 -0.42276006 0.27641816 104 1.54916035 -0.42276006 105 -1.41241619 1.54916035 106 0.23799470 -1.41241619 107 -1.42276006 0.23799470 108 -0.42276006 -1.42276006 109 -0.80042877 -0.42276006 110 -0.41241619 -0.80042877 111 -0.72358184 -0.41241619 112 0.92682905 -0.72358184 113 0.91648518 0.92682905 114 1.88840559 0.91648518 115 -0.11159441 1.88840559 116 0.57723994 -0.11159441 117 0.88840559 0.57723994 118 -0.11159441 0.88840559 119 -0.45083965 -0.11159441 120 0.57723994 -0.45083965 121 -1.11159441 0.57723994 122 -0.07317095 -1.11159441 123 -1.73392571 -0.07317095 124 -1.07317095 -1.73392571 125 -1.11159441 -1.07317095 126 0.88840559 -1.11159441 127 0.88840559 0.88840559 128 0.88840559 0.88840559 129 0.57723994 0.88840559 130 -0.42276006 0.57723994 131 -1.11159441 -0.42276006 132 0.84998212 -1.11159441 133 0.58758381 0.84998212 134 -0.80042877 0.58758381 135 0.57723994 -0.80042877 136 -0.07317095 0.57723994 137 -0.07317095 -0.07317095 138 -0.42276006 -0.07317095 139 -0.42276006 -0.42276006 140 -0.07317095 -0.42276006 141 0.26607429 -0.07317095 142 2.93717292 0.26607429 143 -1.07317095 2.93717292 144 -1.42276006 -1.07317095 145 0.57723994 -1.42276006 146 -0.73392571 0.57723994 147 -0.11159441 -0.73392571 148 -1.45083965 -0.11159441 149 -1.42276006 -1.45083965 150 0.88840559 -1.42276006 151 0.57723994 0.88840559 152 1.26607429 0.57723994 153 -1.11159441 1.26607429 154 1.23799470 -1.11159441 155 -0.11159441 1.23799470 156 -1.73392571 -0.11159441 157 0.92682905 -1.73392571 158 -0.45083965 0.92682905 > 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/7bxm61291304774.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/8bxm61291304774.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/9bxm61291304774.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/freestat/rcomp/tmp/104olr1291304774.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/1177kf1291304774.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/12t8i31291304774.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/137zyu1291304774.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/14aiwi1291304774.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/1539wl1291304774.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/16h1bt1291304774.tab") + } > > try(system("convert tmp/1fn6g1291304774.ps tmp/1fn6g1291304774.png",intern=TRUE)) character(0) > try(system("convert tmp/2fn6g1291304774.ps tmp/2fn6g1291304774.png",intern=TRUE)) character(0) > try(system("convert tmp/38w5i1291304774.ps tmp/38w5i1291304774.png",intern=TRUE)) character(0) > try(system("convert tmp/48w5i1291304774.ps tmp/48w5i1291304774.png",intern=TRUE)) character(0) > try(system("convert tmp/58w5i1291304774.ps tmp/58w5i1291304774.png",intern=TRUE)) character(0) > try(system("convert tmp/60o531291304774.ps tmp/60o531291304774.png",intern=TRUE)) character(0) > try(system("convert tmp/7bxm61291304774.ps tmp/7bxm61291304774.png",intern=TRUE)) character(0) > try(system("convert tmp/8bxm61291304774.ps tmp/8bxm61291304774.png",intern=TRUE)) character(0) > try(system("convert tmp/9bxm61291304774.ps tmp/9bxm61291304774.png",intern=TRUE)) character(0) > try(system("convert tmp/104olr1291304774.ps tmp/104olr1291304774.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.360 2.624 5.685