R version 2.9.0 (2009-04-17) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(4 + ,4 + ,5 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,5 + ,5 + ,4 + ,4 + ,5 + ,5 + ,4 + ,3 + ,3 + ,2 + ,3 + ,4 + ,4 + ,3 + ,2 + ,3 + ,2 + ,3 + ,2 + ,4 + ,3 + ,5 + ,4 + ,3 + ,3 + ,4 + ,5 + ,4 + ,4 + ,3 + ,3 + ,3 + ,3 + ,4 + ,4 + ,2 + ,3 + ,4 + ,4 + ,2 + ,4 + ,2 + ,4 + ,4 + ,3 + ,4 + ,4 + ,5 + ,3 + ,4 + ,3 + ,2 + ,3 + ,2 + ,2 + ,3 + ,4 + ,3 + ,2 + ,4 + ,4 + ,4 + ,4 + ,2 + ,3 + ,2 + ,4 + ,2 + ,3 + ,2 + ,5 + ,4 + ,2 + ,5 + ,5 + ,5 + ,4 + ,3 + ,4 + ,2 + ,3 + ,3 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,5 + ,4 + ,3 + ,2 + ,3 + ,3 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,3 + ,2 + ,2 + ,2 + ,4 + ,2 + ,4 + ,2 + ,4 + ,4 + ,3 + ,4 + ,4 + ,3 + ,3 + ,2 + ,4 + ,4 + ,4 + ,3 + ,3 + ,2 + ,4 + ,4 + ,2 + ,3 + ,4 + ,4 + ,4 + ,2 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,3 + ,4 + ,3 + ,5 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,3 + 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,3 + ,3 + ,1 + ,4 + ,3 + ,3 + ,3 + ,4 + ,3 + ,2 + ,4 + ,4 + ,4 + ,3 + ,3 + ,4 + ,3 + ,4 + ,3 + ,4 + ,3 + ,3 + ,3 + ,3 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,5 + ,4 + ,4 + ,3 + ,3 + ,3 + ,3 + ,4 + ,3 + ,3 + ,2 + ,3 + ,2 + ,4 + ,3 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,2 + ,3 + ,2 + ,3 + ,4 + ,4 + ,3 + ,3 + ,4 + ,3 + ,4 + ,4 + ,4 + ,3 + ,4 + ,3 + ,3 + ,5 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,5 + ,4 + ,2 + ,2 + ,3 + ,2 + ,3 + ,3 + ,4 + ,5 + ,4 + ,4 + ,3 + ,3 + ,5 + ,4 + ,5 + ,3 + ,2 + ,4 + ,3 + ,4 + ,4 + ,3 + ,3 + ,2 + ,3 + ,4 + ,4 + ,2 + ,3 + ,4 + ,3 + ,4 + ,4 + ,3 + ,5 + ,3 + ,4 + ,3 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,5 + ,1 + ,5 + ,5 + ,4 + ,2 + ,2 + ,4 + ,2 + ,2 + ,2 + ,1 + ,5 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,4 + ,4 + ,4 + ,4 + ,4 + ,2 + ,3 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,5 + ,4 + ,3 + ,3 + ,3 + ,4 + ,4 + ,4 + ,2 + ,2 + ,3 + ,2 + ,2 + ,3 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,2 + ,4 + ,4 + ,3 + ,3 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,2 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,4 + ,4 + ,3 + ,5 + ,4 + ,2 + ,2 + ,2 + ,2 + ,4 + ,3 + ,3 + ,5 + ,2 + ,4 + ,4 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,3 + ,4 + ,4 + ,2 + ,4 + ,4 + ,2 + ,4 + ,4 + ,4 + ,4 + ,3 + ,3 + ,3 + ,3 + ,3 + ,4 + ,4 + ,3 + ,4 + ,2 + ,4 + ,3 + ,4 + ,4 + ,5 + ,3 + ,5 + ,5 + ,5 + ,5 + ,5) + ,dim=c(7 + ,152) + ,dimnames=list(c('y' + ,'x1' + ,'x2' + ,'x3' + ,'x4' + ,'x5' + ,'x6') + ,1:152)) > y <- array(NA,dim=c(7,152),dimnames=list(c('y','x1','x2','x3','x4','x5','x6'),1:152)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '1' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x y x1 x2 x3 x4 x5 x6 1 4 4 5 4 4 4 4 2 4 4 4 4 3 4 4 3 5 5 4 4 5 5 4 4 3 3 2 3 4 4 3 5 2 3 2 3 2 4 3 6 5 4 3 3 4 5 4 7 4 3 3 3 3 4 4 8 2 3 4 4 2 4 2 9 4 4 3 4 4 5 3 10 4 3 2 3 2 2 3 11 4 3 2 4 4 4 4 12 2 3 2 4 2 3 2 13 5 4 2 5 5 5 4 14 3 4 2 3 3 4 4 15 4 3 4 4 4 4 4 16 4 3 3 4 4 5 4 17 3 2 3 3 3 3 3 18 4 4 4 4 4 4 4 19 2 3 2 2 2 4 2 20 4 2 4 4 3 4 4 21 3 3 2 4 4 4 3 22 3 2 4 4 2 3 4 23 4 4 2 4 4 4 4 24 4 4 3 4 4 4 4 25 4 4 4 4 4 4 4 26 4 3 3 4 3 4 3 27 5 4 4 4 4 4 4 28 3 4 3 2 4 4 4 29 1 4 4 4 4 4 4 30 4 2 4 4 4 3 4 31 4 2 4 4 4 4 4 32 3 4 3 2 4 4 4 33 3 2 4 4 4 3 4 34 4 5 4 4 5 4 4 35 4 4 4 4 4 4 4 36 4 4 4 4 4 4 5 37 3 2 3 3 5 4 4 38 4 2 4 4 4 4 4 39 3 3 3 3 4 4 4 40 4 3 4 3 4 4 3 41 3 4 4 3 3 3 4 42 4 4 4 3 4 4 2 43 3 2 3 2 3 2 2 44 2 4 2 2 5 2 4 45 3 4 4 4 5 4 4 46 4 4 4 2 4 4 5 47 4 4 4 4 5 5 4 48 3 2 4 4 4 4 4 49 3 3 4 3 4 3 4 50 4 2 4 4 4 4 5 51 4 2 4 4 4 4 3 52 3 4 3 3 4 3 2 53 2 4 2 1 4 4 4 54 4 4 4 4 4 4 4 55 4 3 4 4 4 3 2 56 3 4 4 2 4 3 2 57 2 5 2 2 4 2 4 58 4 4 4 4 4 4 4 59 3 4 4 4 4 4 4 60 3 4 4 3 4 4 3 61 4 4 4 3 4 4 2 62 3 2 3 1 4 3 4 63 4 4 4 4 4 4 5 64 3 4 4 2 4 4 4 65 4 3 4 4 4 4 5 66 4 4 5 5 5 5 4 67 4 2 4 3 4 4 3 68 3 2 3 3 4 3 3 69 3 2 3 2 3 2 4 70 3 4 4 4 4 4 3 71 4 4 3 2 4 2 2 72 3 3 3 2 2 2 4 73 2 2 2 2 4 2 3 74 4 2 4 4 5 4 5 75 4 2 4 5 4 4 5 76 4 5 4 4 5 5 4 77 3 4 2 2 3 2 5 78 5 4 4 5 4 5 4 79 3 2 4 2 4 4 3 80 2 2 3 3 3 3 3 81 3 4 3 4 4 3 4 82 3 4 3 3 4 4 4 83 4 4 4 2 4 4 3 84 4 4 3 3 4 3 4 85 3 2 3 4 4 4 3 86 2 2 2 1 4 2 3 87 4 4 4 2 5 4 3 88 4 3 4 2 4 3 2 89 3 2 2 3 4 2 5 90 4 2 4 3 4 4 3 91 3 4 3 2 4 4 4 92 2 4 2 2 5 4 4 93 3 3 4 4 4 3 3 94 3 4 3 3 4 3 3 95 3 3 3 3 3 2 4 96 4 3 3 4 4 3 4 97 4 4 5 4 4 3 3 98 4 4 4 2 4 2 3 99 3 4 2 2 5 4 4 100 4 4 4 4 5 4 2 101 4 3 3 3 4 3 4 102 3 4 2 2 4 2 4 103 4 2 4 4 5 4 4 104 3 3 4 3 5 4 5 105 4 4 3 3 4 5 5 106 4 3 4 4 5 5 5 107 3 3 4 3 4 4 4 108 3 2 4 4 4 3 4 109 3 2 4 3 4 4 3 110 3 2 4 3 4 4 2 111 3 2 4 3 2 3 2 112 2 4 2 2 4 2 4 113 4 2 4 2 5 5 2 114 2 3 3 1 4 3 3 115 3 4 3 2 4 4 4 116 3 3 4 3 4 3 4 117 3 3 3 3 4 3 4 118 4 4 4 3 4 5 4 119 4 3 3 3 3 4 3 120 3 2 3 2 4 3 4 121 4 3 4 4 4 4 3 122 3 2 3 2 3 4 4 123 3 3 4 3 4 4 4 124 3 4 3 3 5 4 4 125 4 3 4 4 5 4 2 126 2 3 2 3 3 4 5 127 4 4 3 3 5 4 5 128 3 2 4 3 4 4 3 129 3 2 3 4 4 2 3 130 4 3 4 4 3 5 3 131 4 3 3 3 3 4 4 132 4 3 4 4 4 4 3 133 3 5 1 5 5 4 2 134 2 4 2 2 2 1 5 135 4 4 4 4 4 4 4 136 2 4 4 4 4 4 2 137 3 3 3 3 4 4 4 138 4 4 4 3 5 4 3 139 3 3 4 4 4 2 2 140 3 2 2 3 4 4 3 141 3 4 4 2 4 4 3 142 3 4 4 4 4 3 4 143 4 4 4 4 4 4 4 144 3 2 4 4 4 4 4 145 3 4 4 3 5 4 2 146 2 2 2 4 3 3 5 147 2 4 4 4 4 4 4 148 3 3 3 4 4 2 4 149 4 2 4 4 4 4 3 150 3 3 3 3 4 4 3 151 4 2 4 3 4 4 5 152 3 5 5 5 5 5 4 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) x1 x2 x3 x4 x5 0.65346 0.02618 0.22870 0.16452 0.10109 0.19702 x6 0.05404 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -2.73966 -0.40608 0.01056 0.38399 1.55870 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.65346 0.41279 1.583 0.11559 x1 0.02618 0.06187 0.423 0.67286 x2 0.22870 0.07276 3.143 0.00203 ** x3 0.16452 0.06564 2.507 0.01329 * x4 0.10109 0.08143 1.242 0.21642 x5 0.19702 0.07394 2.664 0.00858 ** x6 0.05404 0.06232 0.867 0.38724 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.6439 on 145 degrees of freedom Multiple R-squared: 0.3097, Adjusted R-squared: 0.2811 F-statistic: 10.84 on 6 and 145 DF, p-value: 5.976e-10 > 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,] 0.82749950 0.345000991 0.172500496 [2,] 0.73394804 0.532103916 0.266051958 [3,] 0.63740794 0.725184121 0.362592060 [4,] 0.58520277 0.829594467 0.414797234 [5,] 0.80070896 0.398582084 0.199291042 [6,] 0.72772006 0.544559883 0.272279942 [7,] 0.64886446 0.702271078 0.351135539 [8,] 0.55549229 0.889015425 0.444507712 [9,] 0.51261247 0.974775055 0.487387527 [10,] 0.43282696 0.865653916 0.567173042 [11,] 0.41312677 0.826253534 0.586873233 [12,] 0.38637051 0.772741014 0.613629493 [13,] 0.33131591 0.662631813 0.668684093 [14,] 0.29355365 0.587107304 0.706446348 [15,] 0.25298364 0.505967281 0.747016360 [16,] 0.21362114 0.427242282 0.786378859 [17,] 0.29933220 0.598664403 0.700667798 [18,] 0.35026174 0.700523481 0.649738259 [19,] 0.44610368 0.892207351 0.553896324 [20,] 0.99926043 0.001479144 0.000739572 [21,] 0.99888502 0.002229960 0.001114980 [22,] 0.99827066 0.003458675 0.001729337 [23,] 0.99770702 0.004585966 0.002292983 [24,] 0.99777570 0.004448602 0.002224301 [25,] 0.99668618 0.006627640 0.003313820 [26,] 0.99516026 0.009679485 0.004839742 [27,] 0.99383256 0.012334873 0.006167436 [28,] 0.99325564 0.013488726 0.006744363 [29,] 0.99087746 0.018245071 0.009122536 [30,] 0.98893145 0.022137107 0.011068554 [31,] 0.99097983 0.018040332 0.009020166 [32,] 0.98794825 0.024103510 0.012051755 [33,] 0.99024479 0.019510412 0.009755206 [34,] 0.98950033 0.020999347 0.010499673 [35,] 0.99265417 0.014691667 0.007345833 [36,] 0.99494635 0.010107301 0.005053651 [37,] 0.99391736 0.012165288 0.006082644 [38,] 0.99176228 0.016475440 0.008237720 [39,] 0.99229012 0.015419754 0.007709877 [40,] 0.99010219 0.019795613 0.009897806 [41,] 0.98669387 0.026612254 0.013306127 [42,] 0.98389716 0.032205678 0.016102839 [43,] 0.97819343 0.043613142 0.021806571 [44,] 0.98057120 0.038857598 0.019428799 [45,] 0.97503923 0.049921546 0.024960773 [46,] 0.97426640 0.051467204 0.025733602 [47,] 0.96686991 0.066260181 0.033130091 [48,] 0.96417818 0.071643642 0.035821821 [49,] 0.95535648 0.089287040 0.044643520 [50,] 0.95966886 0.080662288 0.040331144 [51,] 0.95493554 0.090128914 0.045064457 [52,] 0.95171993 0.096560130 0.048280065 [53,] 0.94186623 0.116267539 0.058133769 [54,] 0.92855711 0.142885778 0.071442889 [55,] 0.91756985 0.164860310 0.082430155 [56,] 0.90112803 0.197743942 0.098871971 [57,] 0.89317777 0.213644463 0.106822231 [58,] 0.88499467 0.230010658 0.115005329 [59,] 0.86019964 0.279600717 0.139800359 [60,] 0.84248349 0.315033013 0.157516506 [61,] 0.84378168 0.312436645 0.156218322 [62,] 0.91600439 0.167991215 0.083995607 [63,] 0.90614740 0.187705199 0.093852599 [64,] 0.89855758 0.202884833 0.101442417 [65,] 0.87815886 0.243682271 0.121841135 [66,] 0.85631534 0.287369319 0.143684660 [67,] 0.82832265 0.343354704 0.171677352 [68,] 0.81362173 0.372756536 0.186378268 [69,] 0.86113034 0.277739314 0.138869657 [70,] 0.84071174 0.318576525 0.159288263 [71,] 0.87255981 0.254880371 0.127440185 [72,] 0.85288713 0.294225732 0.147112866 [73,] 0.83030866 0.339382687 0.169691343 [74,] 0.83014061 0.339718785 0.169859392 [75,] 0.85878900 0.282422000 0.141211000 [76,] 0.83992146 0.320157079 0.160078540 [77,] 0.82639908 0.347201834 0.173600917 [78,] 0.81649160 0.367016798 0.183508399 [79,] 0.83972198 0.320556048 0.160278024 [80,] 0.81330990 0.373380194 0.186690097 [81,] 0.80194438 0.396111241 0.198055620 [82,] 0.76772578 0.464548430 0.232274215 [83,] 0.82384677 0.352306460 0.176153230 [84,] 0.80520619 0.389587629 0.194793815 [85,] 0.76939644 0.461207123 0.230603562 [86,] 0.73392589 0.532148215 0.266074108 [87,] 0.76108058 0.477838848 0.238919424 [88,] 0.74264267 0.514714663 0.257357331 [89,] 0.82519590 0.349608196 0.174804098 [90,] 0.79024213 0.419515737 0.209757868 [91,] 0.77287157 0.454256861 0.227128431 [92,] 0.82737191 0.345256182 0.172628091 [93,] 0.83099169 0.338016612 0.169008306 [94,] 0.80591779 0.388164426 0.194082213 [95,] 0.79893464 0.402130718 0.201065359 [96,] 0.78977000 0.420459993 0.210229996 [97,] 0.75129692 0.497406170 0.248703085 [98,] 0.72637473 0.547250533 0.273625266 [99,] 0.69612252 0.607754952 0.303877476 [100,] 0.67397005 0.652059890 0.326029945 [101,] 0.65259218 0.694815646 0.347407823 [102,] 0.59931930 0.801361409 0.400680704 [103,] 0.56435481 0.871290382 0.435645191 [104,] 0.52071554 0.958568912 0.479284456 [105,] 0.56073695 0.878526101 0.439263051 [106,] 0.50452150 0.990957010 0.495478505 [107,] 0.45391806 0.907836117 0.546081941 [108,] 0.39629044 0.792580884 0.603709558 [109,] 0.36605876 0.732117511 0.633941245 [110,] 0.43363315 0.867266296 0.566366852 [111,] 0.37650130 0.753002606 0.623498697 [112,] 0.36515409 0.730308187 0.634845906 [113,] 0.30799982 0.615999642 0.692000179 [114,] 0.27653520 0.553070392 0.723464804 [115,] 0.24126398 0.482527958 0.758736021 [116,] 0.20917943 0.418358865 0.790820567 [117,] 0.26869741 0.537394824 0.731302588 [118,] 0.25798389 0.515967776 0.742016112 [119,] 0.24016617 0.480332343 0.759833829 [120,] 0.18866480 0.377329606 0.811335197 [121,] 0.17650207 0.353004148 0.823497926 [122,] 0.29869017 0.597380336 0.701309832 [123,] 0.37102037 0.742040739 0.628979630 [124,] 0.40360620 0.807212405 0.596393797 [125,] 0.32462560 0.649251199 0.675374401 [126,] 0.51813512 0.963729760 0.481864880 [127,] 0.51260380 0.974792409 0.487396204 [128,] 0.41153931 0.823078613 0.588460694 [129,] 0.36773971 0.735479421 0.632260289 [130,] 0.27732674 0.554653476 0.722673262 [131,] 0.20818049 0.416360986 0.791819507 [132,] 0.14326164 0.286523276 0.856738362 [133,] 0.08228316 0.164566319 0.917716841 > postscript(file="/var/www/html/rcomp/tmp/1p2cn1291375857.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2itt81291375857.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/rcomp/tmp/3itt81291375857.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4bkaa1291375857.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5bkaa1291375857.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 = 152 Frequency = 1 1 2 3 4 5 6 0.03164538 0.36143219 0.93605365 -0.03752181 -0.83533980 1.45654206 7 8 9 10 11 12 0.78082961 -1.40321137 0.34606211 1.55869752 0.74391068 -0.74880109 13 14 15 16 17 18 1.25509941 -0.01665246 0.28651906 0.31819621 0.05806992 0.26034119 19 20 21 22 23 24 -0.61677229 0.41378794 -0.20204554 -0.28810239 0.71773281 0.48903700 25 26 27 28 29 30 0.26034119 0.67034966 1.26034119 -0.18191555 -2.73965881 0.50971559 31 32 33 34 35 36 0.31269693 -0.18191555 -0.49028441 0.13307231 0.26034119 0.20629741 37 38 39 40 41 42 -0.39517454 0.31269693 -0.32026140 0.50508656 -0.27702542 0.53295247 43 44 45 46 47 48 0.47365608 -0.66027342 -0.84074982 0.53534487 -0.03776848 -0.68730307 49 50 51 52 53 54 -0.35193855 0.25865316 0.36674071 -0.04133306 -0.78869601 0.26034119 55 56 57 58 59 60 0.59162527 -0.10550514 -0.58536029 0.26034119 -0.73965881 -0.52109131 61 62 63 64 65 66 0.53295247 0.23198259 0.20629741 -0.41061136 0.23247528 -0.43098802 67 68 69 70 71 72 0.53126444 -0.04302109 0.36556853 -0.68561504 1.32020933 0.44048166 73 74 75 76 77 78 -0.45278289 0.15756215 0.09412943 -0.06394635 0.48786482 0.89879880 79 80 81 82 83 84 -0.30421184 -0.94193008 -0.31394434 -0.34643927 0.64343242 0.85057939 85 86 87 88 89 90 -0.40456348 -0.28825916 0.54234141 0.92067273 0.27460583 0.53126444 91 92 93 94 95 96 -0.18191555 -1.05431074 -0.46241850 -0.09537684 0.17486693 0.71223353 97 98 99 100 101 102 0.28270781 1.03746974 -0.05431074 0.26733773 0.87675726 0.44081759 103 104 105 106 107 108 0.21160592 -0.70409200 0.40249829 -0.06563439 -0.54895721 -0.49028441 109 110 111 112 113 114 -0.46873556 -0.41469179 -0.01549111 -0.55918241 0.45172227 -0.74015151 115 116 117 118 119 120 -0.18191555 -0.35193855 -0.12324274 0.22784625 0.83487338 0.06745886 121 122 123 124 125 126 0.34056284 -0.02846879 -0.54895721 -0.44753028 0.29351560 -1.04451836 127 128 129 130 131 132 0.49842594 -0.46873556 -0.01052616 0.24463518 0.78082961 0.34056284 133 134 135 136 137 138 -0.23727643 -0.21402551 0.26034119 -1.63157126 -0.32026140 0.37781768 139 140 141 142 143 144 -0.21135607 -0.01134394 -0.35656758 -0.54264015 0.26034119 -0.68730307 145 146 147 148 149 150 -0.56813854 -0.98584555 -1.73965881 -0.09074781 0.36674071 -0.26621763 151 152 0.42317688 -1.45716589 > postscript(file="/var/www/html/rcomp/tmp/6bkaa1291375857.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 = 152 Frequency = 1 lag(myerror, k = 1) myerror 0 0.03164538 NA 1 0.36143219 0.03164538 2 0.93605365 0.36143219 3 -0.03752181 0.93605365 4 -0.83533980 -0.03752181 5 1.45654206 -0.83533980 6 0.78082961 1.45654206 7 -1.40321137 0.78082961 8 0.34606211 -1.40321137 9 1.55869752 0.34606211 10 0.74391068 1.55869752 11 -0.74880109 0.74391068 12 1.25509941 -0.74880109 13 -0.01665246 1.25509941 14 0.28651906 -0.01665246 15 0.31819621 0.28651906 16 0.05806992 0.31819621 17 0.26034119 0.05806992 18 -0.61677229 0.26034119 19 0.41378794 -0.61677229 20 -0.20204554 0.41378794 21 -0.28810239 -0.20204554 22 0.71773281 -0.28810239 23 0.48903700 0.71773281 24 0.26034119 0.48903700 25 0.67034966 0.26034119 26 1.26034119 0.67034966 27 -0.18191555 1.26034119 28 -2.73965881 -0.18191555 29 0.50971559 -2.73965881 30 0.31269693 0.50971559 31 -0.18191555 0.31269693 32 -0.49028441 -0.18191555 33 0.13307231 -0.49028441 34 0.26034119 0.13307231 35 0.20629741 0.26034119 36 -0.39517454 0.20629741 37 0.31269693 -0.39517454 38 -0.32026140 0.31269693 39 0.50508656 -0.32026140 40 -0.27702542 0.50508656 41 0.53295247 -0.27702542 42 0.47365608 0.53295247 43 -0.66027342 0.47365608 44 -0.84074982 -0.66027342 45 0.53534487 -0.84074982 46 -0.03776848 0.53534487 47 -0.68730307 -0.03776848 48 -0.35193855 -0.68730307 49 0.25865316 -0.35193855 50 0.36674071 0.25865316 51 -0.04133306 0.36674071 52 -0.78869601 -0.04133306 53 0.26034119 -0.78869601 54 0.59162527 0.26034119 55 -0.10550514 0.59162527 56 -0.58536029 -0.10550514 57 0.26034119 -0.58536029 58 -0.73965881 0.26034119 59 -0.52109131 -0.73965881 60 0.53295247 -0.52109131 61 0.23198259 0.53295247 62 0.20629741 0.23198259 63 -0.41061136 0.20629741 64 0.23247528 -0.41061136 65 -0.43098802 0.23247528 66 0.53126444 -0.43098802 67 -0.04302109 0.53126444 68 0.36556853 -0.04302109 69 -0.68561504 0.36556853 70 1.32020933 -0.68561504 71 0.44048166 1.32020933 72 -0.45278289 0.44048166 73 0.15756215 -0.45278289 74 0.09412943 0.15756215 75 -0.06394635 0.09412943 76 0.48786482 -0.06394635 77 0.89879880 0.48786482 78 -0.30421184 0.89879880 79 -0.94193008 -0.30421184 80 -0.31394434 -0.94193008 81 -0.34643927 -0.31394434 82 0.64343242 -0.34643927 83 0.85057939 0.64343242 84 -0.40456348 0.85057939 85 -0.28825916 -0.40456348 86 0.54234141 -0.28825916 87 0.92067273 0.54234141 88 0.27460583 0.92067273 89 0.53126444 0.27460583 90 -0.18191555 0.53126444 91 -1.05431074 -0.18191555 92 -0.46241850 -1.05431074 93 -0.09537684 -0.46241850 94 0.17486693 -0.09537684 95 0.71223353 0.17486693 96 0.28270781 0.71223353 97 1.03746974 0.28270781 98 -0.05431074 1.03746974 99 0.26733773 -0.05431074 100 0.87675726 0.26733773 101 0.44081759 0.87675726 102 0.21160592 0.44081759 103 -0.70409200 0.21160592 104 0.40249829 -0.70409200 105 -0.06563439 0.40249829 106 -0.54895721 -0.06563439 107 -0.49028441 -0.54895721 108 -0.46873556 -0.49028441 109 -0.41469179 -0.46873556 110 -0.01549111 -0.41469179 111 -0.55918241 -0.01549111 112 0.45172227 -0.55918241 113 -0.74015151 0.45172227 114 -0.18191555 -0.74015151 115 -0.35193855 -0.18191555 116 -0.12324274 -0.35193855 117 0.22784625 -0.12324274 118 0.83487338 0.22784625 119 0.06745886 0.83487338 120 0.34056284 0.06745886 121 -0.02846879 0.34056284 122 -0.54895721 -0.02846879 123 -0.44753028 -0.54895721 124 0.29351560 -0.44753028 125 -1.04451836 0.29351560 126 0.49842594 -1.04451836 127 -0.46873556 0.49842594 128 -0.01052616 -0.46873556 129 0.24463518 -0.01052616 130 0.78082961 0.24463518 131 0.34056284 0.78082961 132 -0.23727643 0.34056284 133 -0.21402551 -0.23727643 134 0.26034119 -0.21402551 135 -1.63157126 0.26034119 136 -0.32026140 -1.63157126 137 0.37781768 -0.32026140 138 -0.21135607 0.37781768 139 -0.01134394 -0.21135607 140 -0.35656758 -0.01134394 141 -0.54264015 -0.35656758 142 0.26034119 -0.54264015 143 -0.68730307 0.26034119 144 -0.56813854 -0.68730307 145 -0.98584555 -0.56813854 146 -1.73965881 -0.98584555 147 -0.09074781 -1.73965881 148 0.36674071 -0.09074781 149 -0.26621763 0.36674071 150 0.42317688 -0.26621763 151 -1.45716589 0.42317688 152 NA -1.45716589 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 0.36143219 0.03164538 [2,] 0.93605365 0.36143219 [3,] -0.03752181 0.93605365 [4,] -0.83533980 -0.03752181 [5,] 1.45654206 -0.83533980 [6,] 0.78082961 1.45654206 [7,] -1.40321137 0.78082961 [8,] 0.34606211 -1.40321137 [9,] 1.55869752 0.34606211 [10,] 0.74391068 1.55869752 [11,] -0.74880109 0.74391068 [12,] 1.25509941 -0.74880109 [13,] -0.01665246 1.25509941 [14,] 0.28651906 -0.01665246 [15,] 0.31819621 0.28651906 [16,] 0.05806992 0.31819621 [17,] 0.26034119 0.05806992 [18,] -0.61677229 0.26034119 [19,] 0.41378794 -0.61677229 [20,] -0.20204554 0.41378794 [21,] -0.28810239 -0.20204554 [22,] 0.71773281 -0.28810239 [23,] 0.48903700 0.71773281 [24,] 0.26034119 0.48903700 [25,] 0.67034966 0.26034119 [26,] 1.26034119 0.67034966 [27,] -0.18191555 1.26034119 [28,] -2.73965881 -0.18191555 [29,] 0.50971559 -2.73965881 [30,] 0.31269693 0.50971559 [31,] -0.18191555 0.31269693 [32,] -0.49028441 -0.18191555 [33,] 0.13307231 -0.49028441 [34,] 0.26034119 0.13307231 [35,] 0.20629741 0.26034119 [36,] -0.39517454 0.20629741 [37,] 0.31269693 -0.39517454 [38,] -0.32026140 0.31269693 [39,] 0.50508656 -0.32026140 [40,] -0.27702542 0.50508656 [41,] 0.53295247 -0.27702542 [42,] 0.47365608 0.53295247 [43,] -0.66027342 0.47365608 [44,] -0.84074982 -0.66027342 [45,] 0.53534487 -0.84074982 [46,] -0.03776848 0.53534487 [47,] -0.68730307 -0.03776848 [48,] -0.35193855 -0.68730307 [49,] 0.25865316 -0.35193855 [50,] 0.36674071 0.25865316 [51,] -0.04133306 0.36674071 [52,] -0.78869601 -0.04133306 [53,] 0.26034119 -0.78869601 [54,] 0.59162527 0.26034119 [55,] -0.10550514 0.59162527 [56,] -0.58536029 -0.10550514 [57,] 0.26034119 -0.58536029 [58,] -0.73965881 0.26034119 [59,] -0.52109131 -0.73965881 [60,] 0.53295247 -0.52109131 [61,] 0.23198259 0.53295247 [62,] 0.20629741 0.23198259 [63,] -0.41061136 0.20629741 [64,] 0.23247528 -0.41061136 [65,] -0.43098802 0.23247528 [66,] 0.53126444 -0.43098802 [67,] -0.04302109 0.53126444 [68,] 0.36556853 -0.04302109 [69,] -0.68561504 0.36556853 [70,] 1.32020933 -0.68561504 [71,] 0.44048166 1.32020933 [72,] -0.45278289 0.44048166 [73,] 0.15756215 -0.45278289 [74,] 0.09412943 0.15756215 [75,] -0.06394635 0.09412943 [76,] 0.48786482 -0.06394635 [77,] 0.89879880 0.48786482 [78,] -0.30421184 0.89879880 [79,] -0.94193008 -0.30421184 [80,] -0.31394434 -0.94193008 [81,] -0.34643927 -0.31394434 [82,] 0.64343242 -0.34643927 [83,] 0.85057939 0.64343242 [84,] -0.40456348 0.85057939 [85,] -0.28825916 -0.40456348 [86,] 0.54234141 -0.28825916 [87,] 0.92067273 0.54234141 [88,] 0.27460583 0.92067273 [89,] 0.53126444 0.27460583 [90,] -0.18191555 0.53126444 [91,] -1.05431074 -0.18191555 [92,] -0.46241850 -1.05431074 [93,] -0.09537684 -0.46241850 [94,] 0.17486693 -0.09537684 [95,] 0.71223353 0.17486693 [96,] 0.28270781 0.71223353 [97,] 1.03746974 0.28270781 [98,] -0.05431074 1.03746974 [99,] 0.26733773 -0.05431074 [100,] 0.87675726 0.26733773 [101,] 0.44081759 0.87675726 [102,] 0.21160592 0.44081759 [103,] -0.70409200 0.21160592 [104,] 0.40249829 -0.70409200 [105,] -0.06563439 0.40249829 [106,] -0.54895721 -0.06563439 [107,] -0.49028441 -0.54895721 [108,] -0.46873556 -0.49028441 [109,] -0.41469179 -0.46873556 [110,] -0.01549111 -0.41469179 [111,] -0.55918241 -0.01549111 [112,] 0.45172227 -0.55918241 [113,] -0.74015151 0.45172227 [114,] -0.18191555 -0.74015151 [115,] -0.35193855 -0.18191555 [116,] -0.12324274 -0.35193855 [117,] 0.22784625 -0.12324274 [118,] 0.83487338 0.22784625 [119,] 0.06745886 0.83487338 [120,] 0.34056284 0.06745886 [121,] -0.02846879 0.34056284 [122,] -0.54895721 -0.02846879 [123,] -0.44753028 -0.54895721 [124,] 0.29351560 -0.44753028 [125,] -1.04451836 0.29351560 [126,] 0.49842594 -1.04451836 [127,] -0.46873556 0.49842594 [128,] -0.01052616 -0.46873556 [129,] 0.24463518 -0.01052616 [130,] 0.78082961 0.24463518 [131,] 0.34056284 0.78082961 [132,] -0.23727643 0.34056284 [133,] -0.21402551 -0.23727643 [134,] 0.26034119 -0.21402551 [135,] -1.63157126 0.26034119 [136,] -0.32026140 -1.63157126 [137,] 0.37781768 -0.32026140 [138,] -0.21135607 0.37781768 [139,] -0.01134394 -0.21135607 [140,] -0.35656758 -0.01134394 [141,] -0.54264015 -0.35656758 [142,] 0.26034119 -0.54264015 [143,] -0.68730307 0.26034119 [144,] -0.56813854 -0.68730307 [145,] -0.98584555 -0.56813854 [146,] -1.73965881 -0.98584555 [147,] -0.09074781 -1.73965881 [148,] 0.36674071 -0.09074781 [149,] -0.26621763 0.36674071 [150,] 0.42317688 -0.26621763 [151,] -1.45716589 0.42317688 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 0.36143219 0.03164538 2 0.93605365 0.36143219 3 -0.03752181 0.93605365 4 -0.83533980 -0.03752181 5 1.45654206 -0.83533980 6 0.78082961 1.45654206 7 -1.40321137 0.78082961 8 0.34606211 -1.40321137 9 1.55869752 0.34606211 10 0.74391068 1.55869752 11 -0.74880109 0.74391068 12 1.25509941 -0.74880109 13 -0.01665246 1.25509941 14 0.28651906 -0.01665246 15 0.31819621 0.28651906 16 0.05806992 0.31819621 17 0.26034119 0.05806992 18 -0.61677229 0.26034119 19 0.41378794 -0.61677229 20 -0.20204554 0.41378794 21 -0.28810239 -0.20204554 22 0.71773281 -0.28810239 23 0.48903700 0.71773281 24 0.26034119 0.48903700 25 0.67034966 0.26034119 26 1.26034119 0.67034966 27 -0.18191555 1.26034119 28 -2.73965881 -0.18191555 29 0.50971559 -2.73965881 30 0.31269693 0.50971559 31 -0.18191555 0.31269693 32 -0.49028441 -0.18191555 33 0.13307231 -0.49028441 34 0.26034119 0.13307231 35 0.20629741 0.26034119 36 -0.39517454 0.20629741 37 0.31269693 -0.39517454 38 -0.32026140 0.31269693 39 0.50508656 -0.32026140 40 -0.27702542 0.50508656 41 0.53295247 -0.27702542 42 0.47365608 0.53295247 43 -0.66027342 0.47365608 44 -0.84074982 -0.66027342 45 0.53534487 -0.84074982 46 -0.03776848 0.53534487 47 -0.68730307 -0.03776848 48 -0.35193855 -0.68730307 49 0.25865316 -0.35193855 50 0.36674071 0.25865316 51 -0.04133306 0.36674071 52 -0.78869601 -0.04133306 53 0.26034119 -0.78869601 54 0.59162527 0.26034119 55 -0.10550514 0.59162527 56 -0.58536029 -0.10550514 57 0.26034119 -0.58536029 58 -0.73965881 0.26034119 59 -0.52109131 -0.73965881 60 0.53295247 -0.52109131 61 0.23198259 0.53295247 62 0.20629741 0.23198259 63 -0.41061136 0.20629741 64 0.23247528 -0.41061136 65 -0.43098802 0.23247528 66 0.53126444 -0.43098802 67 -0.04302109 0.53126444 68 0.36556853 -0.04302109 69 -0.68561504 0.36556853 70 1.32020933 -0.68561504 71 0.44048166 1.32020933 72 -0.45278289 0.44048166 73 0.15756215 -0.45278289 74 0.09412943 0.15756215 75 -0.06394635 0.09412943 76 0.48786482 -0.06394635 77 0.89879880 0.48786482 78 -0.30421184 0.89879880 79 -0.94193008 -0.30421184 80 -0.31394434 -0.94193008 81 -0.34643927 -0.31394434 82 0.64343242 -0.34643927 83 0.85057939 0.64343242 84 -0.40456348 0.85057939 85 -0.28825916 -0.40456348 86 0.54234141 -0.28825916 87 0.92067273 0.54234141 88 0.27460583 0.92067273 89 0.53126444 0.27460583 90 -0.18191555 0.53126444 91 -1.05431074 -0.18191555 92 -0.46241850 -1.05431074 93 -0.09537684 -0.46241850 94 0.17486693 -0.09537684 95 0.71223353 0.17486693 96 0.28270781 0.71223353 97 1.03746974 0.28270781 98 -0.05431074 1.03746974 99 0.26733773 -0.05431074 100 0.87675726 0.26733773 101 0.44081759 0.87675726 102 0.21160592 0.44081759 103 -0.70409200 0.21160592 104 0.40249829 -0.70409200 105 -0.06563439 0.40249829 106 -0.54895721 -0.06563439 107 -0.49028441 -0.54895721 108 -0.46873556 -0.49028441 109 -0.41469179 -0.46873556 110 -0.01549111 -0.41469179 111 -0.55918241 -0.01549111 112 0.45172227 -0.55918241 113 -0.74015151 0.45172227 114 -0.18191555 -0.74015151 115 -0.35193855 -0.18191555 116 -0.12324274 -0.35193855 117 0.22784625 -0.12324274 118 0.83487338 0.22784625 119 0.06745886 0.83487338 120 0.34056284 0.06745886 121 -0.02846879 0.34056284 122 -0.54895721 -0.02846879 123 -0.44753028 -0.54895721 124 0.29351560 -0.44753028 125 -1.04451836 0.29351560 126 0.49842594 -1.04451836 127 -0.46873556 0.49842594 128 -0.01052616 -0.46873556 129 0.24463518 -0.01052616 130 0.78082961 0.24463518 131 0.34056284 0.78082961 132 -0.23727643 0.34056284 133 -0.21402551 -0.23727643 134 0.26034119 -0.21402551 135 -1.63157126 0.26034119 136 -0.32026140 -1.63157126 137 0.37781768 -0.32026140 138 -0.21135607 0.37781768 139 -0.01134394 -0.21135607 140 -0.35656758 -0.01134394 141 -0.54264015 -0.35656758 142 0.26034119 -0.54264015 143 -0.68730307 0.26034119 144 -0.56813854 -0.68730307 145 -0.98584555 -0.56813854 146 -1.73965881 -0.98584555 147 -0.09074781 -1.73965881 148 0.36674071 -0.09074781 149 -0.26621763 0.36674071 150 0.42317688 -0.26621763 151 -1.45716589 0.42317688 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/73uaw1291375857.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8e39z1291375857.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9e39z1291375857.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10e39z1291375857.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/11i3q51291375857.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/12lmoa1291375857.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/13anlm1291375857.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/14vo2a1291375857.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/15of1v1291375857.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/16kphm1291375857.tab") + } > > try(system("convert tmp/1p2cn1291375857.ps tmp/1p2cn1291375857.png",intern=TRUE)) character(0) > try(system("convert tmp/2itt81291375857.ps tmp/2itt81291375857.png",intern=TRUE)) character(0) > try(system("convert tmp/3itt81291375857.ps tmp/3itt81291375857.png",intern=TRUE)) character(0) > try(system("convert tmp/4bkaa1291375857.ps tmp/4bkaa1291375857.png",intern=TRUE)) character(0) > try(system("convert tmp/5bkaa1291375857.ps tmp/5bkaa1291375857.png",intern=TRUE)) character(0) > try(system("convert tmp/6bkaa1291375857.ps tmp/6bkaa1291375857.png",intern=TRUE)) character(0) > try(system("convert tmp/73uaw1291375857.ps tmp/73uaw1291375857.png",intern=TRUE)) character(0) > try(system("convert tmp/8e39z1291375857.ps tmp/8e39z1291375857.png",intern=TRUE)) character(0) > try(system("convert tmp/9e39z1291375857.ps tmp/9e39z1291375857.png",intern=TRUE)) character(0) > try(system("convert tmp/10e39z1291375857.ps tmp/10e39z1291375857.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.916 1.673 15.560