R version 2.13.0 (2011-04-13) Copyright (C) 2011 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i486-pc-linux-gnu (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(158258 + ,0 + ,48 + ,18 + ,20465 + ,23975 + ,186930 + ,1 + ,53 + ,20 + ,33629 + ,85634 + ,7215 + ,0 + ,0 + ,0 + ,1423 + ,1929 + ,129098 + ,0 + ,51 + ,27 + ,25629 + ,36294 + ,230632 + ,0 + ,76 + ,31 + ,54002 + ,72255 + ,508313 + ,1 + ,128 + ,36 + ,151036 + ,189748 + ,180745 + ,1 + ,62 + ,23 + ,33287 + ,61834 + ,185559 + ,0 + ,83 + ,30 + ,31172 + ,68167 + ,154581 + ,0 + ,55 + ,30 + ,28113 + ,38462 + ,290658 + ,1 + ,67 + ,26 + ,57803 + ,101219 + ,121844 + ,2 + ,50 + ,24 + ,49830 + ,43270 + ,184039 + ,0 + ,77 + ,30 + ,52143 + ,76183 + ,100324 + ,0 + ,46 + ,22 + ,21055 + ,31476 + ,209427 + ,4 + ,79 + ,25 + ,47007 + ,62157 + ,168265 + ,4 + ,56 + ,18 + ,28735 + ,46261 + ,154593 + ,3 + ,54 + ,22 + ,59147 + ,50063 + ,142018 + ,0 + ,81 + ,33 + ,78950 + ,64483 + ,78604 + ,5 + ,6 + ,15 + ,13497 + ,2341 + ,167047 + ,0 + ,74 + ,34 + ,46154 + ,48149 + ,27997 + ,0 + ,13 + ,18 + ,53249 + ,12743 + ,73019 + ,0 + ,22 + ,15 + ,10726 + ,18743 + ,241082 + ,0 + ,99 + 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,8 + ,69 + ,36 + ,74990 + ,110600 + ,138708 + ,2 + ,93 + ,25 + ,29653 + ,52235 + ,114408 + ,0 + ,59 + ,24 + ,64622 + ,53986 + ,31970 + ,0 + ,5 + ,21 + ,4157 + ,4105 + ,225558 + ,3 + ,53 + ,19 + ,29245 + ,59331 + ,137011 + ,1 + ,40 + ,12 + ,50008 + ,47796 + ,113612 + ,2 + ,72 + ,30 + ,52338 + ,38302 + ,108641 + ,1 + ,51 + ,21 + ,13310 + ,14063 + ,162203 + ,0 + ,81 + ,34 + ,92901 + ,54414 + ,100098 + ,2 + ,27 + ,32 + ,10956 + ,9903 + ,174768 + ,1 + ,94 + ,28 + ,34241 + ,53987 + ,158459 + ,0 + ,71 + ,28 + ,75043 + ,88937 + ,80934 + ,0 + ,20 + ,21 + ,21152 + ,21928 + ,84971 + ,0 + ,34 + ,31 + ,42249 + ,29487 + ,80545 + ,0 + ,54 + ,26 + ,42005 + ,35334 + ,287191 + ,0 + ,49 + ,29 + ,41152 + ,57596 + ,62974 + ,1 + ,26 + ,23 + ,14399 + ,29750 + ,130982 + ,0 + ,47 + ,25 + ,28263 + ,41029 + ,75555 + ,0 + ,35 + ,22 + ,17215 + ,12416 + ,162154 + ,0 + ,32 + ,26 + ,48140 + ,51158 + ,226638 + ,0 + ,55 + ,33 + ,62897 + ,79935 + ,115019 + ,0 + ,58 + ,24 + ,22883 + ,26552 + ,105038 + ,7 + ,44 + ,24 + 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+ ,31032 + ,50848 + ,136540 + ,0 + ,59 + ,21 + ,32683 + ,39443 + ,76656 + ,0 + ,36 + ,21 + ,34545 + ,27023 + ,3616 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,183065 + ,0 + ,40 + ,23 + ,27525 + ,61022 + ,144636 + ,0 + ,68 + ,33 + ,66856 + ,63528 + ,159104 + ,2 + ,28 + ,30 + ,28549 + ,34835 + ,113273 + ,0 + ,36 + ,23 + ,38610 + ,37172 + ,43410 + ,0 + ,7 + ,1 + ,2781 + ,13 + ,175774 + ,1 + ,70 + ,29 + ,41211 + ,62548 + ,95401 + ,0 + ,30 + ,18 + ,22698 + ,31334 + ,118893 + ,8 + ,59 + ,32 + ,41194 + ,20839 + ,60493 + ,3 + ,3 + ,12 + ,32689 + ,5084 + ,19764 + ,1 + ,10 + ,2 + ,5752 + ,9927 + ,164062 + ,3 + ,46 + ,21 + ,26757 + ,53229 + ,132696 + ,0 + ,34 + ,28 + ,22527 + ,29877 + ,155367 + ,0 + ,54 + ,29 + ,44810 + ,37310 + ,11796 + ,0 + ,1 + ,2 + ,0 + ,0 + ,10674 + ,0 + ,0 + ,0 + ,0 + ,0 + ,142261 + ,0 + ,39 + ,18 + ,100674 + ,50067 + ,6836 + ,0 + ,0 + ,1 + ,0 + ,0 + ,154206 + ,6 + ,48 + ,21 + ,57786 + ,47708 + ,5118 + ,0 + ,5 + ,0 + ,0 + ,0 + ,40248 + ,1 + ,8 + ,4 + ,5444 + ,6012 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,122641 + ,0 + ,38 + ,25 + ,28470 + ,27749 + ,88837 + ,0 + ,21 + ,26 + ,61849 + ,47555 + ,7131 + ,1 + ,0 + ,0 + ,0 + ,0 + ,9056 + ,0 + ,0 + ,4 + ,2179 + ,1336 + ,76611 + ,1 + ,15 + ,17 + ,8019 + ,11017 + ,132697 + ,0 + ,50 + ,21 + ,39644 + ,55184 + ,100681 + ,1 + ,17 + ,22 + ,23494 + ,43485) + ,dim=c(6 + ,144) + ,dimnames=list(c('Time' + ,'shared' + ,'computations' + ,'reviewed' + ,'characters' + ,'seconds') + ,1:144)) > y <- array(NA,dim=c(6,144),dimnames=list(c('Time','shared','computations','reviewed','characters','seconds'),1:144)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par20 = '' > par19 = '' > par18 = '' > par17 = '' > par16 = '' > par15 = '' > par14 = '' > par13 = '' > par12 = '' > par11 = '' > par10 = '' > par9 = '' > par8 = '' > par7 = '' > par6 = '' > par5 = '' > par4 = '' > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '5' > library(lattice) > library(lmtest) Loading required package: zoo > 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 characters Time shared computations reviewed seconds 1 20465 158258 0 48 18 23975 2 33629 186930 1 53 20 85634 3 1423 7215 0 0 0 1929 4 25629 129098 0 51 27 36294 5 54002 230632 0 76 31 72255 6 151036 508313 1 128 36 189748 7 33287 180745 1 62 23 61834 8 31172 185559 0 83 30 68167 9 28113 154581 0 55 30 38462 10 57803 290658 1 67 26 101219 11 49830 121844 2 50 24 43270 12 52143 184039 0 77 30 76183 13 21055 100324 0 46 22 31476 14 47007 209427 4 79 25 62157 15 28735 168265 4 56 18 46261 16 59147 154593 3 54 22 50063 17 78950 142018 0 81 33 64483 18 13497 78604 5 6 15 2341 19 46154 167047 0 74 34 48149 20 53249 27997 0 13 18 12743 21 10726 73019 0 22 15 18743 22 83700 241082 0 99 30 97057 23 40400 195820 0 38 25 17675 24 33797 141899 1 59 34 33106 25 36205 145433 1 50 21 53311 26 30165 183744 0 50 21 42754 27 58534 202232 0 61 25 59056 28 44663 190230 0 81 31 101621 29 92556 354924 0 60 31 118120 30 40078 192399 0 52 20 79572 31 34711 182286 0 61 28 42744 32 31076 181590 2 60 22 65931 33 74608 133801 4 53 17 38575 34 58092 233686 0 76 25 28795 35 42009 219428 1 63 24 94440 36 0 0 0 0 0 0 37 36022 223044 0 54 28 38229 38 23333 100129 3 44 14 31972 39 53349 136733 9 36 35 40071 40 92596 249965 0 83 34 132480 41 49598 242379 2 105 22 62797 42 44093 145794 0 37 34 40429 43 84205 96404 2 25 23 45545 44 63369 195891 1 64 24 57568 45 60132 117156 2 55 26 39019 46 37403 157787 2 41 22 53866 47 24460 81293 1 23 35 38345 48 46456 224049 0 67 24 50210 49 66616 223789 1 54 31 80947 50 41554 160344 8 68 26 43461 51 22346 48188 0 12 22 14812 52 30874 152206 0 86 21 37819 53 68701 294283 0 74 27 102738 54 35728 235223 0 56 30 54509 55 29010 195583 1 67 33 62956 56 23110 145942 8 40 11 55411 57 38844 208834 0 53 26 50611 58 27084 93764 1 26 26 26692 59 35139 151985 0 67 23 60056 60 57476 190545 10 36 38 25155 61 33277 148922 6 50 31 42840 62 31141 132856 0 48 20 39358 63 61281 126107 11 46 19 47241 64 25820 112718 3 53 26 49611 65 23284 160930 0 27 26 41833 66 35378 99184 0 38 33 48930 67 74990 182022 8 69 36 110600 68 29653 138708 2 93 25 52235 69 64622 114408 0 59 24 53986 70 4157 31970 0 5 21 4105 71 29245 225558 3 53 19 59331 72 50008 137011 1 40 12 47796 73 52338 113612 2 72 30 38302 74 13310 108641 1 51 21 14063 75 92901 162203 0 81 34 54414 76 10956 100098 2 27 32 9903 77 34241 174768 1 94 28 53987 78 75043 158459 0 71 28 88937 79 21152 80934 0 20 21 21928 80 42249 84971 0 34 31 29487 81 42005 80545 0 54 26 35334 82 41152 287191 0 49 29 57596 83 14399 62974 1 26 23 29750 84 28263 130982 0 47 25 41029 85 17215 75555 0 35 22 12416 86 48140 162154 0 32 26 51158 87 62897 226638 0 55 33 79935 88 22883 115019 0 58 24 26552 89 41622 105038 7 44 24 25807 90 40715 155537 0 45 21 50620 91 65897 153133 5 49 28 61467 92 76542 165577 1 72 27 65292 93 37477 151517 0 39 25 55516 94 53216 133686 0 28 15 42006 95 40911 58128 0 24 13 26273 96 57021 245196 0 52 36 90248 97 73116 195576 0 96 24 61476 98 3895 19349 0 13 1 9604 99 46609 225371 3 38 24 45108 100 29351 152796 0 41 31 47232 101 2325 59117 0 24 4 3439 102 31747 91762 0 54 21 30553 103 32665 127987 0 59 23 24751 104 19249 113552 1 28 23 34458 105 15292 85338 1 36 12 24649 106 5842 27676 0 2 16 2342 107 33994 147984 0 83 29 52739 108 13018 122417 0 29 26 6245 109 0 0 0 0 0 0 110 98177 91529 0 46 25 35381 111 37941 107205 0 25 21 19595 112 31032 144664 0 51 23 50848 113 32683 136540 0 59 21 39443 114 34545 76656 0 36 21 27023 115 0 3616 0 0 0 0 116 0 0 0 0 0 0 117 27525 183065 0 40 23 61022 118 66856 144636 0 68 33 63528 119 28549 159104 2 28 30 34835 120 38610 113273 0 36 23 37172 121 2781 43410 0 7 1 13 122 41211 175774 1 70 29 62548 123 22698 95401 0 30 18 31334 124 41194 118893 8 59 32 20839 125 32689 60493 3 3 12 5084 126 5752 19764 1 10 2 9927 127 26757 164062 3 46 21 53229 128 22527 132696 0 34 28 29877 129 44810 155367 0 54 29 37310 130 0 11796 0 1 2 0 131 0 10674 0 0 0 0 132 100674 142261 0 39 18 50067 133 0 6836 0 0 1 0 134 57786 154206 6 48 21 47708 135 0 5118 0 5 0 0 136 5444 40248 1 8 4 6012 137 0 0 0 0 0 0 138 28470 122641 0 38 25 27749 139 61849 88837 0 21 26 47555 140 0 7131 1 0 0 0 141 2179 9056 0 0 4 1336 142 8019 76611 1 15 17 11017 143 39644 132697 0 50 21 55184 144 23494 100681 1 17 22 43485 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Time shared computations reviewed 1.166e+03 -6.489e-03 9.175e+02 1.063e+02 5.075e+02 seconds 4.786e-01 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -28253 -9917 -2901 6370 63185 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.166e+03 3.425e+03 0.340 0.7340 Time -6.489e-03 3.785e-02 -0.171 0.8641 shared 9.175e+02 6.019e+02 1.524 0.1297 computations 1.063e+02 9.104e+01 1.168 0.2449 reviewed 5.075e+02 2.010e+02 2.525 0.0127 * seconds 4.786e-01 9.101e-02 5.259 5.38e-07 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 15820 on 138 degrees of freedom Multiple R-squared: 0.6168, Adjusted R-squared: 0.6029 F-statistic: 44.43 on 5 and 138 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,] 0.20416275 0.4083255 0.795837249 [2,] 0.21898668 0.4379734 0.781013322 [3,] 0.60515915 0.7896817 0.394840845 [4,] 0.54058188 0.9188362 0.459418117 [5,] 0.43574317 0.8714863 0.564256831 [6,] 0.38530803 0.7706161 0.614691973 [7,] 0.31528261 0.6305652 0.684717388 [8,] 0.41515966 0.8303193 0.584840343 [9,] 0.66870802 0.6625840 0.331291982 [10,] 0.60003553 0.7999289 0.399964475 [11,] 0.51990231 0.9601954 0.480097692 [12,] 0.80396509 0.3920698 0.196034911 [13,] 0.75545794 0.4890841 0.244542058 [14,] 0.73970889 0.5205822 0.260291112 [15,] 0.75759028 0.4848194 0.242409724 [16,] 0.71306611 0.5738678 0.286933885 [17,] 0.65710800 0.6857840 0.342892000 [18,] 0.59559075 0.8088185 0.404409246 [19,] 0.56280809 0.8743838 0.437191910 [20,] 0.67629302 0.6474140 0.323706975 [21,] 0.63077588 0.7384482 0.369224119 [22,] 0.60415538 0.7916892 0.395844618 [23,] 0.55198061 0.8960388 0.448019391 [24,] 0.55529541 0.8894092 0.444704592 [25,] 0.82409213 0.3518157 0.175907869 [26,] 0.83981793 0.3203641 0.160182069 [27,] 0.85411382 0.2917724 0.145886177 [28,] 0.82156813 0.3568637 0.178431867 [29,] 0.79181562 0.4163688 0.208184384 [30,] 0.75533480 0.4893304 0.244665200 [31,] 0.71009105 0.5798179 0.289908953 [32,] 0.68969203 0.6206159 0.310307974 [33,] 0.64523934 0.7095213 0.354760661 [34,] 0.59450350 0.8109930 0.405496500 [35,] 0.88299665 0.2340067 0.117003353 [36,] 0.88158134 0.2368373 0.118418656 [37,] 0.89482998 0.2103400 0.105170016 [38,] 0.87433034 0.2513393 0.125669655 [39,] 0.87711536 0.2457693 0.122884635 [40,] 0.85030528 0.2993894 0.149694716 [41,] 0.82074620 0.3585076 0.179253796 [42,] 0.79699224 0.4060155 0.203007760 [43,] 0.75877898 0.4824420 0.241221018 [44,] 0.72083771 0.5583246 0.279162287 [45,] 0.67710931 0.6457814 0.322890691 [46,] 0.66204649 0.6759070 0.337953513 [47,] 0.72914995 0.5417001 0.270850048 [48,] 0.75916451 0.4816710 0.240835492 [49,] 0.72246340 0.5550732 0.277536601 [50,] 0.68020488 0.6395902 0.319795123 [51,] 0.65991358 0.6801728 0.340086415 [52,] 0.65055653 0.6988869 0.349443467 [53,] 0.63585896 0.7282821 0.364141043 [54,] 0.58992651 0.8201470 0.410073491 [55,] 0.58615384 0.8276923 0.413846162 [56,] 0.60645323 0.7870935 0.393546773 [57,] 0.59237983 0.8152403 0.407620172 [58,] 0.56245903 0.8750819 0.437540973 [59,] 0.56430332 0.8713934 0.435696683 [60,] 0.60571637 0.7885673 0.394283635 [61,] 0.63955506 0.7208899 0.360444944 [62,] 0.60586499 0.7882700 0.394135005 [63,] 0.61996383 0.7600723 0.380036173 [64,] 0.61337539 0.7732492 0.386624609 [65,] 0.58404349 0.8319130 0.415956508 [66,] 0.55244951 0.8951010 0.447550489 [67,] 0.78872432 0.4225514 0.211275678 [68,] 0.77812963 0.4437407 0.221870369 [69,] 0.79249222 0.4150156 0.207507780 [70,] 0.76979165 0.4604167 0.230208353 [71,] 0.73065249 0.5386950 0.269347512 [72,] 0.70054741 0.5989052 0.299452594 [73,] 0.66082785 0.6783443 0.339172147 [74,] 0.61878576 0.7624285 0.381214244 [75,] 0.62895457 0.7420909 0.371045432 [76,] 0.60107411 0.7978518 0.398925886 [77,] 0.55413392 0.8917322 0.445866081 [78,] 0.51382584 0.9723483 0.486174157 [79,] 0.46372733 0.9274547 0.536272667 [80,] 0.43128849 0.8625770 0.568711514 [81,] 0.38523171 0.7704634 0.614768290 [82,] 0.33794653 0.6758931 0.662053475 [83,] 0.30644594 0.6128919 0.693554057 [84,] 0.32757444 0.6551489 0.672425562 [85,] 0.29157774 0.5831555 0.708422263 [86,] 0.33809095 0.6761819 0.661909050 [87,] 0.34198216 0.6839643 0.658017836 [88,] 0.31350176 0.6270035 0.686498239 [89,] 0.34344317 0.6868863 0.656556831 [90,] 0.29848389 0.5969678 0.701516110 [91,] 0.28630863 0.5726173 0.713691367 [92,] 0.27876194 0.5575239 0.721238055 [93,] 0.23649568 0.4729914 0.763504318 [94,] 0.19834894 0.3966979 0.801651063 [95,] 0.16546581 0.3309316 0.834534187 [96,] 0.16089358 0.3217872 0.839106420 [97,] 0.13442636 0.2688527 0.865573642 [98,] 0.11674248 0.2334850 0.883257523 [99,] 0.13083370 0.2616674 0.869166304 [100,] 0.10429664 0.2085933 0.895703364 [101,] 0.08117069 0.1623414 0.918829309 [102,] 0.60253578 0.7949284 0.397464216 [103,] 0.60781583 0.7843683 0.392184172 [104,] 0.58064789 0.8387042 0.419352114 [105,] 0.52002297 0.9599541 0.479977030 [106,] 0.46175217 0.9235043 0.538247830 [107,] 0.39864625 0.7972925 0.601353752 [108,] 0.33781018 0.6756204 0.662189821 [109,] 0.38869294 0.7773859 0.611307065 [110,] 0.34715700 0.6943140 0.652843001 [111,] 0.32556634 0.6511327 0.674433657 [112,] 0.26781630 0.5356326 0.732183701 [113,] 0.21226298 0.4245260 0.787737023 [114,] 0.20283026 0.4056605 0.797169738 [115,] 0.16507263 0.3301453 0.834927365 [116,] 0.16565133 0.3313027 0.834348668 [117,] 0.24140633 0.4828127 0.758593668 [118,] 0.18321233 0.3664247 0.816787665 [119,] 0.47734956 0.9546991 0.522650443 [120,] 0.42960990 0.8592198 0.570390095 [121,] 0.34445307 0.6889061 0.655546934 [122,] 0.25709993 0.5141999 0.742900068 [123,] 0.18498850 0.3699770 0.815011495 [124,] 0.99011140 0.0197772 0.009888601 [125,] 0.97485455 0.0502909 0.025145451 [126,] 0.93531338 0.1293732 0.064686620 [127,] 0.85311386 0.2937723 0.146886138 > postscript(file="/var/wessaorg/rcomp/tmp/1v9tl1324549672.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2tz801324549672.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3etec1324549672.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/47u211324549672.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5fjk81324549672.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 = 144 Frequency = 1 1 2 3 4 5 6 -5388.1039 -24014.9097 -619.7531 -11196.2599 -4064.8552 29550.1733 7 8 9 10 11 12 -15484.6599 -25467.3251 -11532.3883 -11160.9608 9412.4444 -7705.1145 13 14 15 16 17 18 -10581.7473 -7308.0747 -12240.8403 15362.7538 22481.5738 -1117.8299 19 20 21 22 23 24 -2097.1404 35647.7984 -8889.2344 11891.8803 15316.6829 -6739.8717 25 26 27 28 29 30 -6425.5148 -6246.3483 11240.2599 -28253.4694 15043.6649 -13605.0438 31 32 33 34 35 36 -6427.0418 -19848.5660 37913.8411 23891.9035 -22732.1577 -1166.2651 37 38 39 40 41 42 -1946.2842 -7022.2857 4042.4182 3561.4980 -4216.2041 3332.7327 43 44 45 46 47 48 45698.8273 16017.3809 20172.1525 -5881.1943 -15657.9337 3407.5376 49 50 51 52 53 54 5765.7671 -7138.9561 1961.7821 -7207.2147 -1300.6910 -11181.2353 55 56 57 58 59 60 -25809.0722 -20806.7767 -4021.7373 -3126.7366 -12582.3041 13218.0163 61 62 63 64 65 66 -13981.6693 -3254.9404 13695.5286 -19943.3390 -12926.8558 -9352.4785 67 68 69 70 71 72 -10879.4036 -20025.2176 19905.2451 -9955.8960 -16886.0007 15593.2813 73 74 75 76 77 78 8860.9608 -10879.7270 40875.5160 -15246.5560 -16753.1326 10577.1716 79 80 81 82 83 84 -2768.7771 8172.8564 5512.7477 -5645.8850 -15952.7002 -9376.1416 85 86 87 88 89 90 -4290.0431 6942.1523 2345.8312 -8592.3404 5504.2506 887.1752 91 92 93 94 95 96 12296.3023 22923.5837 -6112.4981 22221.8302 18397.3328 -9549.5896 97 98 99 100 101 102 21407.2422 -3632.2137 6341.7280 -13522.7856 -4685.3064 153.4740 103 104 105 106 107 108 2537.0398 -13240.5931 -7953.5745 -4598.4240 -14997.1086 -6621.3892 109 110 111 112 113 114 -1166.2651 63091.5514 14775.7966 -10628.4143 -3406.6904 6456.7334 115 116 117 118 119 120 -1142.8013 -1166.2651 -17586.5020 12243.7589 -8295.5372 4886.5572 121 122 123 124 125 126 638.4839 -11830.2353 -5171.6561 971.7540 20320.2364 -3033.2070 127 128 129 130 131 132 -17123.1655 -9903.6082 6334.9334 -2211.0532 -1097.0027 63185.1320 133 134 135 136 137 138 -1629.4152 13519.2872 -1664.6287 -2136.7819 -1166.2651 -1910.0329 139 140 141 142 143 144 23069.4248 -2037.5128 -1598.0034 -9063.2515 -3048.1386 -11722.8658 > postscript(file="/var/wessaorg/rcomp/tmp/6zzmb1324549672.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 = 144 Frequency = 1 lag(myerror, k = 1) myerror 0 -5388.1039 NA 1 -24014.9097 -5388.1039 2 -619.7531 -24014.9097 3 -11196.2599 -619.7531 4 -4064.8552 -11196.2599 5 29550.1733 -4064.8552 6 -15484.6599 29550.1733 7 -25467.3251 -15484.6599 8 -11532.3883 -25467.3251 9 -11160.9608 -11532.3883 10 9412.4444 -11160.9608 11 -7705.1145 9412.4444 12 -10581.7473 -7705.1145 13 -7308.0747 -10581.7473 14 -12240.8403 -7308.0747 15 15362.7538 -12240.8403 16 22481.5738 15362.7538 17 -1117.8299 22481.5738 18 -2097.1404 -1117.8299 19 35647.7984 -2097.1404 20 -8889.2344 35647.7984 21 11891.8803 -8889.2344 22 15316.6829 11891.8803 23 -6739.8717 15316.6829 24 -6425.5148 -6739.8717 25 -6246.3483 -6425.5148 26 11240.2599 -6246.3483 27 -28253.4694 11240.2599 28 15043.6649 -28253.4694 29 -13605.0438 15043.6649 30 -6427.0418 -13605.0438 31 -19848.5660 -6427.0418 32 37913.8411 -19848.5660 33 23891.9035 37913.8411 34 -22732.1577 23891.9035 35 -1166.2651 -22732.1577 36 -1946.2842 -1166.2651 37 -7022.2857 -1946.2842 38 4042.4182 -7022.2857 39 3561.4980 4042.4182 40 -4216.2041 3561.4980 41 3332.7327 -4216.2041 42 45698.8273 3332.7327 43 16017.3809 45698.8273 44 20172.1525 16017.3809 45 -5881.1943 20172.1525 46 -15657.9337 -5881.1943 47 3407.5376 -15657.9337 48 5765.7671 3407.5376 49 -7138.9561 5765.7671 50 1961.7821 -7138.9561 51 -7207.2147 1961.7821 52 -1300.6910 -7207.2147 53 -11181.2353 -1300.6910 54 -25809.0722 -11181.2353 55 -20806.7767 -25809.0722 56 -4021.7373 -20806.7767 57 -3126.7366 -4021.7373 58 -12582.3041 -3126.7366 59 13218.0163 -12582.3041 60 -13981.6693 13218.0163 61 -3254.9404 -13981.6693 62 13695.5286 -3254.9404 63 -19943.3390 13695.5286 64 -12926.8558 -19943.3390 65 -9352.4785 -12926.8558 66 -10879.4036 -9352.4785 67 -20025.2176 -10879.4036 68 19905.2451 -20025.2176 69 -9955.8960 19905.2451 70 -16886.0007 -9955.8960 71 15593.2813 -16886.0007 72 8860.9608 15593.2813 73 -10879.7270 8860.9608 74 40875.5160 -10879.7270 75 -15246.5560 40875.5160 76 -16753.1326 -15246.5560 77 10577.1716 -16753.1326 78 -2768.7771 10577.1716 79 8172.8564 -2768.7771 80 5512.7477 8172.8564 81 -5645.8850 5512.7477 82 -15952.7002 -5645.8850 83 -9376.1416 -15952.7002 84 -4290.0431 -9376.1416 85 6942.1523 -4290.0431 86 2345.8312 6942.1523 87 -8592.3404 2345.8312 88 5504.2506 -8592.3404 89 887.1752 5504.2506 90 12296.3023 887.1752 91 22923.5837 12296.3023 92 -6112.4981 22923.5837 93 22221.8302 -6112.4981 94 18397.3328 22221.8302 95 -9549.5896 18397.3328 96 21407.2422 -9549.5896 97 -3632.2137 21407.2422 98 6341.7280 -3632.2137 99 -13522.7856 6341.7280 100 -4685.3064 -13522.7856 101 153.4740 -4685.3064 102 2537.0398 153.4740 103 -13240.5931 2537.0398 104 -7953.5745 -13240.5931 105 -4598.4240 -7953.5745 106 -14997.1086 -4598.4240 107 -6621.3892 -14997.1086 108 -1166.2651 -6621.3892 109 63091.5514 -1166.2651 110 14775.7966 63091.5514 111 -10628.4143 14775.7966 112 -3406.6904 -10628.4143 113 6456.7334 -3406.6904 114 -1142.8013 6456.7334 115 -1166.2651 -1142.8013 116 -17586.5020 -1166.2651 117 12243.7589 -17586.5020 118 -8295.5372 12243.7589 119 4886.5572 -8295.5372 120 638.4839 4886.5572 121 -11830.2353 638.4839 122 -5171.6561 -11830.2353 123 971.7540 -5171.6561 124 20320.2364 971.7540 125 -3033.2070 20320.2364 126 -17123.1655 -3033.2070 127 -9903.6082 -17123.1655 128 6334.9334 -9903.6082 129 -2211.0532 6334.9334 130 -1097.0027 -2211.0532 131 63185.1320 -1097.0027 132 -1629.4152 63185.1320 133 13519.2872 -1629.4152 134 -1664.6287 13519.2872 135 -2136.7819 -1664.6287 136 -1166.2651 -2136.7819 137 -1910.0329 -1166.2651 138 23069.4248 -1910.0329 139 -2037.5128 23069.4248 140 -1598.0034 -2037.5128 141 -9063.2515 -1598.0034 142 -3048.1386 -9063.2515 143 -11722.8658 -3048.1386 144 NA -11722.8658 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -24014.9097 -5388.1039 [2,] -619.7531 -24014.9097 [3,] -11196.2599 -619.7531 [4,] -4064.8552 -11196.2599 [5,] 29550.1733 -4064.8552 [6,] -15484.6599 29550.1733 [7,] -25467.3251 -15484.6599 [8,] -11532.3883 -25467.3251 [9,] -11160.9608 -11532.3883 [10,] 9412.4444 -11160.9608 [11,] -7705.1145 9412.4444 [12,] -10581.7473 -7705.1145 [13,] -7308.0747 -10581.7473 [14,] -12240.8403 -7308.0747 [15,] 15362.7538 -12240.8403 [16,] 22481.5738 15362.7538 [17,] -1117.8299 22481.5738 [18,] -2097.1404 -1117.8299 [19,] 35647.7984 -2097.1404 [20,] -8889.2344 35647.7984 [21,] 11891.8803 -8889.2344 [22,] 15316.6829 11891.8803 [23,] -6739.8717 15316.6829 [24,] -6425.5148 -6739.8717 [25,] -6246.3483 -6425.5148 [26,] 11240.2599 -6246.3483 [27,] -28253.4694 11240.2599 [28,] 15043.6649 -28253.4694 [29,] -13605.0438 15043.6649 [30,] -6427.0418 -13605.0438 [31,] -19848.5660 -6427.0418 [32,] 37913.8411 -19848.5660 [33,] 23891.9035 37913.8411 [34,] -22732.1577 23891.9035 [35,] -1166.2651 -22732.1577 [36,] -1946.2842 -1166.2651 [37,] -7022.2857 -1946.2842 [38,] 4042.4182 -7022.2857 [39,] 3561.4980 4042.4182 [40,] -4216.2041 3561.4980 [41,] 3332.7327 -4216.2041 [42,] 45698.8273 3332.7327 [43,] 16017.3809 45698.8273 [44,] 20172.1525 16017.3809 [45,] -5881.1943 20172.1525 [46,] -15657.9337 -5881.1943 [47,] 3407.5376 -15657.9337 [48,] 5765.7671 3407.5376 [49,] -7138.9561 5765.7671 [50,] 1961.7821 -7138.9561 [51,] -7207.2147 1961.7821 [52,] -1300.6910 -7207.2147 [53,] -11181.2353 -1300.6910 [54,] -25809.0722 -11181.2353 [55,] -20806.7767 -25809.0722 [56,] -4021.7373 -20806.7767 [57,] -3126.7366 -4021.7373 [58,] -12582.3041 -3126.7366 [59,] 13218.0163 -12582.3041 [60,] -13981.6693 13218.0163 [61,] -3254.9404 -13981.6693 [62,] 13695.5286 -3254.9404 [63,] -19943.3390 13695.5286 [64,] -12926.8558 -19943.3390 [65,] -9352.4785 -12926.8558 [66,] -10879.4036 -9352.4785 [67,] -20025.2176 -10879.4036 [68,] 19905.2451 -20025.2176 [69,] -9955.8960 19905.2451 [70,] -16886.0007 -9955.8960 [71,] 15593.2813 -16886.0007 [72,] 8860.9608 15593.2813 [73,] -10879.7270 8860.9608 [74,] 40875.5160 -10879.7270 [75,] -15246.5560 40875.5160 [76,] -16753.1326 -15246.5560 [77,] 10577.1716 -16753.1326 [78,] -2768.7771 10577.1716 [79,] 8172.8564 -2768.7771 [80,] 5512.7477 8172.8564 [81,] -5645.8850 5512.7477 [82,] -15952.7002 -5645.8850 [83,] -9376.1416 -15952.7002 [84,] -4290.0431 -9376.1416 [85,] 6942.1523 -4290.0431 [86,] 2345.8312 6942.1523 [87,] -8592.3404 2345.8312 [88,] 5504.2506 -8592.3404 [89,] 887.1752 5504.2506 [90,] 12296.3023 887.1752 [91,] 22923.5837 12296.3023 [92,] -6112.4981 22923.5837 [93,] 22221.8302 -6112.4981 [94,] 18397.3328 22221.8302 [95,] -9549.5896 18397.3328 [96,] 21407.2422 -9549.5896 [97,] -3632.2137 21407.2422 [98,] 6341.7280 -3632.2137 [99,] -13522.7856 6341.7280 [100,] -4685.3064 -13522.7856 [101,] 153.4740 -4685.3064 [102,] 2537.0398 153.4740 [103,] -13240.5931 2537.0398 [104,] -7953.5745 -13240.5931 [105,] -4598.4240 -7953.5745 [106,] -14997.1086 -4598.4240 [107,] -6621.3892 -14997.1086 [108,] -1166.2651 -6621.3892 [109,] 63091.5514 -1166.2651 [110,] 14775.7966 63091.5514 [111,] -10628.4143 14775.7966 [112,] -3406.6904 -10628.4143 [113,] 6456.7334 -3406.6904 [114,] -1142.8013 6456.7334 [115,] -1166.2651 -1142.8013 [116,] -17586.5020 -1166.2651 [117,] 12243.7589 -17586.5020 [118,] -8295.5372 12243.7589 [119,] 4886.5572 -8295.5372 [120,] 638.4839 4886.5572 [121,] -11830.2353 638.4839 [122,] -5171.6561 -11830.2353 [123,] 971.7540 -5171.6561 [124,] 20320.2364 971.7540 [125,] -3033.2070 20320.2364 [126,] -17123.1655 -3033.2070 [127,] -9903.6082 -17123.1655 [128,] 6334.9334 -9903.6082 [129,] -2211.0532 6334.9334 [130,] -1097.0027 -2211.0532 [131,] 63185.1320 -1097.0027 [132,] -1629.4152 63185.1320 [133,] 13519.2872 -1629.4152 [134,] -1664.6287 13519.2872 [135,] -2136.7819 -1664.6287 [136,] -1166.2651 -2136.7819 [137,] -1910.0329 -1166.2651 [138,] 23069.4248 -1910.0329 [139,] -2037.5128 23069.4248 [140,] -1598.0034 -2037.5128 [141,] -9063.2515 -1598.0034 [142,] -3048.1386 -9063.2515 [143,] -11722.8658 -3048.1386 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -24014.9097 -5388.1039 2 -619.7531 -24014.9097 3 -11196.2599 -619.7531 4 -4064.8552 -11196.2599 5 29550.1733 -4064.8552 6 -15484.6599 29550.1733 7 -25467.3251 -15484.6599 8 -11532.3883 -25467.3251 9 -11160.9608 -11532.3883 10 9412.4444 -11160.9608 11 -7705.1145 9412.4444 12 -10581.7473 -7705.1145 13 -7308.0747 -10581.7473 14 -12240.8403 -7308.0747 15 15362.7538 -12240.8403 16 22481.5738 15362.7538 17 -1117.8299 22481.5738 18 -2097.1404 -1117.8299 19 35647.7984 -2097.1404 20 -8889.2344 35647.7984 21 11891.8803 -8889.2344 22 15316.6829 11891.8803 23 -6739.8717 15316.6829 24 -6425.5148 -6739.8717 25 -6246.3483 -6425.5148 26 11240.2599 -6246.3483 27 -28253.4694 11240.2599 28 15043.6649 -28253.4694 29 -13605.0438 15043.6649 30 -6427.0418 -13605.0438 31 -19848.5660 -6427.0418 32 37913.8411 -19848.5660 33 23891.9035 37913.8411 34 -22732.1577 23891.9035 35 -1166.2651 -22732.1577 36 -1946.2842 -1166.2651 37 -7022.2857 -1946.2842 38 4042.4182 -7022.2857 39 3561.4980 4042.4182 40 -4216.2041 3561.4980 41 3332.7327 -4216.2041 42 45698.8273 3332.7327 43 16017.3809 45698.8273 44 20172.1525 16017.3809 45 -5881.1943 20172.1525 46 -15657.9337 -5881.1943 47 3407.5376 -15657.9337 48 5765.7671 3407.5376 49 -7138.9561 5765.7671 50 1961.7821 -7138.9561 51 -7207.2147 1961.7821 52 -1300.6910 -7207.2147 53 -11181.2353 -1300.6910 54 -25809.0722 -11181.2353 55 -20806.7767 -25809.0722 56 -4021.7373 -20806.7767 57 -3126.7366 -4021.7373 58 -12582.3041 -3126.7366 59 13218.0163 -12582.3041 60 -13981.6693 13218.0163 61 -3254.9404 -13981.6693 62 13695.5286 -3254.9404 63 -19943.3390 13695.5286 64 -12926.8558 -19943.3390 65 -9352.4785 -12926.8558 66 -10879.4036 -9352.4785 67 -20025.2176 -10879.4036 68 19905.2451 -20025.2176 69 -9955.8960 19905.2451 70 -16886.0007 -9955.8960 71 15593.2813 -16886.0007 72 8860.9608 15593.2813 73 -10879.7270 8860.9608 74 40875.5160 -10879.7270 75 -15246.5560 40875.5160 76 -16753.1326 -15246.5560 77 10577.1716 -16753.1326 78 -2768.7771 10577.1716 79 8172.8564 -2768.7771 80 5512.7477 8172.8564 81 -5645.8850 5512.7477 82 -15952.7002 -5645.8850 83 -9376.1416 -15952.7002 84 -4290.0431 -9376.1416 85 6942.1523 -4290.0431 86 2345.8312 6942.1523 87 -8592.3404 2345.8312 88 5504.2506 -8592.3404 89 887.1752 5504.2506 90 12296.3023 887.1752 91 22923.5837 12296.3023 92 -6112.4981 22923.5837 93 22221.8302 -6112.4981 94 18397.3328 22221.8302 95 -9549.5896 18397.3328 96 21407.2422 -9549.5896 97 -3632.2137 21407.2422 98 6341.7280 -3632.2137 99 -13522.7856 6341.7280 100 -4685.3064 -13522.7856 101 153.4740 -4685.3064 102 2537.0398 153.4740 103 -13240.5931 2537.0398 104 -7953.5745 -13240.5931 105 -4598.4240 -7953.5745 106 -14997.1086 -4598.4240 107 -6621.3892 -14997.1086 108 -1166.2651 -6621.3892 109 63091.5514 -1166.2651 110 14775.7966 63091.5514 111 -10628.4143 14775.7966 112 -3406.6904 -10628.4143 113 6456.7334 -3406.6904 114 -1142.8013 6456.7334 115 -1166.2651 -1142.8013 116 -17586.5020 -1166.2651 117 12243.7589 -17586.5020 118 -8295.5372 12243.7589 119 4886.5572 -8295.5372 120 638.4839 4886.5572 121 -11830.2353 638.4839 122 -5171.6561 -11830.2353 123 971.7540 -5171.6561 124 20320.2364 971.7540 125 -3033.2070 20320.2364 126 -17123.1655 -3033.2070 127 -9903.6082 -17123.1655 128 6334.9334 -9903.6082 129 -2211.0532 6334.9334 130 -1097.0027 -2211.0532 131 63185.1320 -1097.0027 132 -1629.4152 63185.1320 133 13519.2872 -1629.4152 134 -1664.6287 13519.2872 135 -2136.7819 -1664.6287 136 -1166.2651 -2136.7819 137 -1910.0329 -1166.2651 138 23069.4248 -1910.0329 139 -2037.5128 23069.4248 140 -1598.0034 -2037.5128 141 -9063.2515 -1598.0034 142 -3048.1386 -9063.2515 143 -11722.8658 -3048.1386 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/70dfs1324549672.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8c9t71324549672.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9intc1324549672.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10m1c01324549672.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/11vrd31324549672.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/12mg411324549672.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/130oa01324549672.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/14oxbo1324549672.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/15aqgm1324549672.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/wessaorg/rcomp/tmp/1609uj1324549672.tab") + } > > try(system("convert tmp/1v9tl1324549672.ps tmp/1v9tl1324549672.png",intern=TRUE)) character(0) > try(system("convert tmp/2tz801324549672.ps tmp/2tz801324549672.png",intern=TRUE)) character(0) > try(system("convert tmp/3etec1324549672.ps tmp/3etec1324549672.png",intern=TRUE)) character(0) > try(system("convert tmp/47u211324549672.ps tmp/47u211324549672.png",intern=TRUE)) character(0) > try(system("convert tmp/5fjk81324549672.ps tmp/5fjk81324549672.png",intern=TRUE)) character(0) > try(system("convert tmp/6zzmb1324549672.ps tmp/6zzmb1324549672.png",intern=TRUE)) character(0) > try(system("convert tmp/70dfs1324549672.ps tmp/70dfs1324549672.png",intern=TRUE)) character(0) > try(system("convert tmp/8c9t71324549672.ps tmp/8c9t71324549672.png",intern=TRUE)) character(0) > try(system("convert tmp/9intc1324549672.ps tmp/9intc1324549672.png",intern=TRUE)) character(0) > try(system("convert tmp/10m1c01324549672.ps tmp/10m1c01324549672.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.168 0.739 5.922