R version 2.12.1 (2010-12-16) Copyright (C) 2010 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(129988 + ,81 + ,18158 + ,22622 + ,130358 + ,46 + ,30461 + ,73570 + ,7215 + ,18 + ,1423 + ,1929 + ,112976 + ,87 + ,25629 + ,36294 + ,220191 + ,127 + ,48758 + ,62378 + ,402036 + ,218 + ,129230 + ,167760 + ,125071 + ,51 + ,27376 + ,52443 + ,131822 + ,50 + ,26706 + ,57283 + ,99738 + ,39 + ,26505 + ,36614 + ,269166 + ,88 + ,49801 + ,93268 + ,113066 + ,69 + ,46580 + ,35439 + ,165392 + ,62 + ,48352 + ,72405 + ,78240 + ,90 + ,13899 + ,24044 + ,170854 + ,86 + ,39342 + ,55909 + ,134368 + ,47 + ,27465 + ,44689 + ,125769 + ,68 + ,55211 + ,49319 + ,123467 + ,50 + ,74098 + ,62075 + ,57396 + ,49 + ,13497 + ,2341 + ,108458 + ,79 + ,38338 + ,40551 + ,22762 + ,21 + ,52505 + ,11621 + ,48633 + ,50 + ,10663 + ,18741 + ,182081 + ,83 + ,74484 + ,84202 + ,149507 + ,62 + ,28895 + ,15334 + ,93773 + ,46 + ,32827 + ,28024 + ,133428 + ,79 + ,36188 + ,53306 + ,126660 + ,24 + ,28173 + ,37918 + ,153851 + ,140 + ,54926 + ,54819 + ,140711 + ,75 + ,38900 + ,89058 + ,303952 + ,108 + ,88530 + ,103354 + ,163810 + ,38 + ,35482 + ,70239 + ,134521 + ,41 + ,26730 + ,33045 + ,157640 + ,39 + ,29806 + ,63852 + ,103274 + ,90 + ,41799 + ,30905 + ,193500 + ,105 + ,54289 + ,24242 + ,182027 + ,44 + ,36805 + ,78907 + ,0 + ,1 + ,0 + ,0 + ,181496 + ,56 + ,33146 + ,36005 + ,92342 + ,47 + ,23333 + ,31972 + ,115762 + ,42 + ,47686 + ,35853 + ,179089 + ,51 + ,77783 + ,115301 + ,145067 + ,58 + ,36042 + ,47689 + ,114146 + ,50 + ,34541 + ,34223 + ,86039 + ,26 + ,75620 + ,43431 + ,125481 + ,66 + ,60610 + ,52220 + ,95535 + ,42 + ,55041 + ,33863 + ,129236 + ,79 + ,32087 + ,46879 + ,61554 + ,26 + ,16356 + ,23228 + ,170811 + ,83 + ,40161 + ,42827 + ,161746 + ,76 + ,55459 + ,65765 + ,137317 + ,52 + ,36679 + ,38167 + ,48188 + ,28 + ,22346 + ,14812 + ,97793 + ,57 + ,27377 + ,32615 + ,249356 + ,65 + ,50273 + ,82188 + ,196791 + ,69 + ,32104 + ,51763 + ,161082 + ,51 + ,27016 + ,59325 + ,111388 + ,47 + ,19715 + ,48976 + ,172614 + ,58 + ,33629 + ,43384 + ,63681 + ,19 + ,27084 + ,26692 + ,109102 + ,56 + ,32352 + ,53279 + ,142391 + ,76 + ,51845 + ,20652 + ,125777 + ,51 + ,26591 + ,38338 + ,88650 + ,66 + ,29677 + ,36735 + ,95845 + ,50 + ,54237 + ,42764 + ,83419 + ,29 + ,20284 + ,44331 + ,101723 + ,25 + ,22741 + ,41354 + ,94982 + ,37 + ,34178 + ,47879 + ,145568 + ,62 + ,69551 + ,103793 + ,113325 + ,63 + ,29653 + ,52235 + ,92480 + ,34 + ,38071 + ,49825 + ,31970 + ,15 + ,4157 + ,4105 + ,196420 + ,104 + ,28321 + ,58687 + ,98324 + ,56 + ,40195 + ,40745 + ,80820 + ,56 + ,48158 + ,33187 + ,89319 + ,61 + ,13310 + ,14063 + ,118147 + ,55 + ,78474 + ,37407 + ,56544 + ,32 + ,6386 + ,7190 + ,118838 + ,52 + ,31588 + ,49562 + ,118781 + ,80 + ,61254 + ,76324 + ,60138 + ,23 + ,21152 + ,21928 + ,73422 + ,66 + ,41272 + ,27860 + ,70248 + ,60 + ,34165 + ,28078 + ,225857 + ,54 + ,37054 + ,49577 + ,51185 + ,24 + ,12368 + ,28145 + ,97181 + ,32 + ,23168 + ,36241 + ,45100 + ,40 + ,16380 + ,10824 + ,115801 + ,43 + ,41242 + ,46892 + ,187201 + ,191 + ,48450 + ,61264 + ,71960 + ,86 + ,20790 + ,22933 + ,81701 + ,49 + ,34585 + ,20787 + ,110416 + ,43 + ,35672 + ,43978 + ,98707 + ,34 + ,52168 + ,51305 + ,136234 + ,67 + ,53933 + ,55593 + ,136781 + ,53 + ,34474 + ,51648 + ,116132 + ,54 + ,43753 + ,30552 + ,49164 + ,33 + ,36456 + ,23470 + ,189493 + ,93 + ,51183 + ,77530 + ,169406 + ,50 + ,52742 + ,57299 + ,19349 + ,12 + ,3895 + ,9604 + ,160902 + ,88 + ,37076 + ,34684 + ,109510 + ,53 + ,24079 + ,41094 + ,43803 + ,25 + ,2325 + ,3439 + ,47062 + ,19 + ,29354 + ,25171 + ,110845 + ,44 + ,30341 + ,23437 + ,92517 + ,52 + ,18992 + ,34086 + ,58660 + ,36 + ,15292 + ,24649 + ,27676 + ,22 + ,5842 + ,2342 + ,98550 + ,33 + ,28918 + ,45571 + ,43863 + ,25 + ,3738 + ,3255 + ,0 + ,0 + ,0 + ,0 + ,75566 + ,28 + ,95352 + ,30002 + ,57359 + ,49 + ,37478 + ,19360 + ,104330 + ,36 + ,26839 + ,43320 + ,70369 + ,47 + ,26783 + ,35513 + ,65494 + ,56 + ,33392 + ,23536 + ,3616 + ,5 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,148117 + ,38 + ,25446 + ,54438 + ,117946 + ,66 + ,59847 + ,56812 + ,138702 + ,86 + ,28162 + ,33838 + ,84336 + ,33 + ,33298 + ,32366 + ,43410 + ,19 + ,2781 + ,13 + ,139695 + ,61 + ,37121 + ,55082 + ,79015 + ,34 + ,22698 + ,31334 + ,106116 + ,47 + ,27615 + ,16612 + ,57586 + ,38 + ,32689 + ,5084 + ,19764 + ,12 + ,5752 + ,9927 + ,112195 + ,43 + ,23164 + ,47413 + ,103651 + ,25 + ,20304 + ,27389 + ,113402 + ,35 + ,34409 + ,30425 + ,11796 + ,9 + ,0 + ,0 + ,7627 + ,9 + ,0 + ,0 + ,121085 + ,50 + ,92538 + ,33510 + ,6836 + ,3 + ,0 + ,0 + ,139563 + ,46 + ,46037 + ,40389 + ,5118 + ,3 + ,0 + ,0 + ,40248 + ,16 + ,5444 + ,6012 + ,0 + ,0 + ,0 + ,0 + ,95079 + ,42 + ,23924 + ,22205 + ,80763 + ,32 + ,52230 + ,17231 + ,7131 + ,4 + ,0 + ,0 + ,4194 + ,11 + ,0 + ,0 + ,60378 + ,20 + ,8019 + ,11017 + ,109214 + ,45 + ,34542 + ,46741 + ,83484 + ,16 + ,21157 + ,39869) + ,dim=c(4 + ,144) + ,dimnames=list(c('A' + ,'B' + ,'C' + ,'D') + ,1:144)) > y <- array(NA,dim=c(4,144),dimnames=list(c('A','B','C','D'),1:144)) > 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 > 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 A B C D 1 129988 81 18158 22622 2 130358 46 30461 73570 3 7215 18 1423 1929 4 112976 87 25629 36294 5 220191 127 48758 62378 6 402036 218 129230 167760 7 125071 51 27376 52443 8 131822 50 26706 57283 9 99738 39 26505 36614 10 269166 88 49801 93268 11 113066 69 46580 35439 12 165392 62 48352 72405 13 78240 90 13899 24044 14 170854 86 39342 55909 15 134368 47 27465 44689 16 125769 68 55211 49319 17 123467 50 74098 62075 18 57396 49 13497 2341 19 108458 79 38338 40551 20 22762 21 52505 11621 21 48633 50 10663 18741 22 182081 83 74484 84202 23 149507 62 28895 15334 24 93773 46 32827 28024 25 133428 79 36188 53306 26 126660 24 28173 37918 27 153851 140 54926 54819 28 140711 75 38900 89058 29 303952 108 88530 103354 30 163810 38 35482 70239 31 134521 41 26730 33045 32 157640 39 29806 63852 33 103274 90 41799 30905 34 193500 105 54289 24242 35 182027 44 36805 78907 36 0 1 0 0 37 181496 56 33146 36005 38 92342 47 23333 31972 39 115762 42 47686 35853 40 179089 51 77783 115301 41 145067 58 36042 47689 42 114146 50 34541 34223 43 86039 26 75620 43431 44 125481 66 60610 52220 45 95535 42 55041 33863 46 129236 79 32087 46879 47 61554 26 16356 23228 48 170811 83 40161 42827 49 161746 76 55459 65765 50 137317 52 36679 38167 51 48188 28 22346 14812 52 97793 57 27377 32615 53 249356 65 50273 82188 54 196791 69 32104 51763 55 161082 51 27016 59325 56 111388 47 19715 48976 57 172614 58 33629 43384 58 63681 19 27084 26692 59 109102 56 32352 53279 60 142391 76 51845 20652 61 125777 51 26591 38338 62 88650 66 29677 36735 63 95845 50 54237 42764 64 83419 29 20284 44331 65 101723 25 22741 41354 66 94982 37 34178 47879 67 145568 62 69551 103793 68 113325 63 29653 52235 69 92480 34 38071 49825 70 31970 15 4157 4105 71 196420 104 28321 58687 72 98324 56 40195 40745 73 80820 56 48158 33187 74 89319 61 13310 14063 75 118147 55 78474 37407 76 56544 32 6386 7190 77 118838 52 31588 49562 78 118781 80 61254 76324 79 60138 23 21152 21928 80 73422 66 41272 27860 81 70248 60 34165 28078 82 225857 54 37054 49577 83 51185 24 12368 28145 84 97181 32 23168 36241 85 45100 40 16380 10824 86 115801 43 41242 46892 87 187201 191 48450 61264 88 71960 86 20790 22933 89 81701 49 34585 20787 90 110416 43 35672 43978 91 98707 34 52168 51305 92 136234 67 53933 55593 93 136781 53 34474 51648 94 116132 54 43753 30552 95 49164 33 36456 23470 96 189493 93 51183 77530 97 169406 50 52742 57299 98 19349 12 3895 9604 99 160902 88 37076 34684 100 109510 53 24079 41094 101 43803 25 2325 3439 102 47062 19 29354 25171 103 110845 44 30341 23437 104 92517 52 18992 34086 105 58660 36 15292 24649 106 27676 22 5842 2342 107 98550 33 28918 45571 108 43863 25 3738 3255 109 0 0 0 0 110 75566 28 95352 30002 111 57359 49 37478 19360 112 104330 36 26839 43320 113 70369 47 26783 35513 114 65494 56 33392 23536 115 3616 5 0 0 116 0 0 0 0 117 148117 38 25446 54438 118 117946 66 59847 56812 119 138702 86 28162 33838 120 84336 33 33298 32366 121 43410 19 2781 13 122 139695 61 37121 55082 123 79015 34 22698 31334 124 106116 47 27615 16612 125 57586 38 32689 5084 126 19764 12 5752 9927 127 112195 43 23164 47413 128 103651 25 20304 27389 129 113402 35 34409 30425 130 11796 9 0 0 131 7627 9 0 0 132 121085 50 92538 33510 133 6836 3 0 0 134 139563 46 46037 40389 135 5118 3 0 0 136 40248 16 5444 6012 137 0 0 0 0 138 95079 42 23924 22205 139 80763 32 52230 17231 140 7131 4 0 0 141 4194 11 0 0 142 60378 20 8019 11017 143 109214 45 34542 46741 144 83484 16 21157 39869 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) B C D 1.410e+04 7.247e+02 1.153e-01 1.384e+00 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -66032 -17250 -4575 15287 99708 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.410e+04 4.580e+03 3.079 0.0025 ** B 7.247e+02 9.619e+01 7.535 5.52e-12 *** C 1.153e-01 1.568e-01 0.735 0.4634 D 1.385e+00 1.357e-01 10.202 < 2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 27300 on 140 degrees of freedom Multiple R-squared: 0.8107, Adjusted R-squared: 0.8066 F-statistic: 199.8 on 3 and 140 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,] 0.3431924 6.863849e-01 6.568076e-01 [2,] 0.2242419 4.484838e-01 7.757581e-01 [3,] 0.2076736 4.153473e-01 7.923264e-01 [4,] 0.6165743 7.668515e-01 3.834257e-01 [5,] 0.5524402 8.951195e-01 4.475598e-01 [6,] 0.4478277 8.956554e-01 5.521723e-01 [7,] 0.5541773 8.916454e-01 4.458227e-01 [8,] 0.4803062 9.606125e-01 5.196938e-01 [9,] 0.4393463 8.786925e-01 5.606537e-01 [10,] 0.3576256 7.152511e-01 6.423744e-01 [11,] 0.2898340 5.796679e-01 7.101660e-01 [12,] 0.2319754 4.639508e-01 7.680246e-01 [13,] 0.2025476 4.050952e-01 7.974524e-01 [14,] 0.1560019 3.120038e-01 8.439981e-01 [15,] 0.1596201 3.192402e-01 8.403799e-01 [16,] 0.1241365 2.482730e-01 8.758635e-01 [17,] 0.5349127 9.301747e-01 4.650873e-01 [18,] 0.4711939 9.423879e-01 5.288061e-01 [19,] 0.4268442 8.536884e-01 5.731558e-01 [20,] 0.5092621 9.814757e-01 4.907379e-01 [21,] 0.5621988 8.756023e-01 4.378012e-01 [22,] 0.7540436 4.919128e-01 2.459564e-01 [23,] 0.8883349 2.233301e-01 1.116651e-01 [24,] 0.8701598 2.596804e-01 1.298402e-01 [25,] 0.8994015 2.011970e-01 1.005985e-01 [26,] 0.8842649 2.314702e-01 1.157351e-01 [27,] 0.8691791 2.616418e-01 1.308209e-01 [28,] 0.9570935 8.581308e-02 4.290654e-02 [29,] 0.9502321 9.953588e-02 4.976794e-02 [30,] 0.9401853 1.196294e-01 5.981468e-02 [31,] 0.9875943 2.481131e-02 1.240566e-02 [32,] 0.9826898 3.462045e-02 1.731023e-02 [33,] 0.9773515 4.529699e-02 2.264849e-02 [34,] 0.9852063 2.958745e-02 1.479372e-02 [35,] 0.9816980 3.660392e-02 1.830196e-02 [36,] 0.9758882 4.822363e-02 2.411181e-02 [37,] 0.9717564 5.648714e-02 2.824357e-02 [38,] 0.9657870 6.842597e-02 3.421299e-02 [39,] 0.9549238 9.015238e-02 4.507619e-02 [40,] 0.9438895 1.122210e-01 5.611048e-02 [41,] 0.9290386 1.419228e-01 7.096139e-02 [42,] 0.9333845 1.332311e-01 6.661554e-02 [43,] 0.9159658 1.680685e-01 8.403423e-02 [44,] 0.9145926 1.708148e-01 8.540739e-02 [45,] 0.8970677 2.058647e-01 1.029323e-01 [46,] 0.8745940 2.508119e-01 1.254060e-01 [47,] 0.9618571 7.628573e-02 3.814286e-02 [48,] 0.9852143 2.957142e-02 1.478571e-02 [49,] 0.9846366 3.072672e-02 1.536336e-02 [50,] 0.9799787 4.004257e-02 2.002129e-02 [51,] 0.9916319 1.673611e-02 8.368056e-03 [52,] 0.9886063 2.278747e-02 1.139373e-02 [53,] 0.9874611 2.507786e-02 1.253893e-02 [54,] 0.9909698 1.806033e-02 9.030165e-03 [55,] 0.9895255 2.094902e-02 1.047451e-02 [56,] 0.9895580 2.088396e-02 1.044198e-02 [57,] 0.9878348 2.433032e-02 1.216516e-02 [58,] 0.9849873 3.002539e-02 1.501269e-02 [59,] 0.9806218 3.875632e-02 1.937816e-02 [60,] 0.9764213 4.715734e-02 2.357867e-02 [61,] 0.9942731 1.145390e-02 5.726948e-03 [62,] 0.9935861 1.282783e-02 6.413915e-03 [63,] 0.9927386 1.452287e-02 7.261437e-03 [64,] 0.9899448 2.011033e-02 1.005516e-02 [65,] 0.9900958 1.980842e-02 9.904208e-03 [66,] 0.9879477 2.410462e-02 1.205231e-02 [67,] 0.9872372 2.552567e-02 1.276283e-02 [68,] 0.9846035 3.079295e-02 1.539647e-02 [69,] 0.9793026 4.139483e-02 2.069742e-02 [70,] 0.9739966 5.200676e-02 2.600338e-02 [71,] 0.9659793 6.804130e-02 3.402065e-02 [72,] 0.9944496 1.110081e-02 5.550406e-03 [73,] 0.9921990 1.560206e-02 7.801028e-03 [74,] 0.9927706 1.445887e-02 7.229434e-03 [75,] 0.9931334 1.373320e-02 6.866600e-03 [76,] 0.9999917 1.665394e-05 8.326972e-06 [77,] 0.9999903 1.936297e-05 9.681484e-06 [78,] 0.9999834 3.311170e-05 1.655585e-05 [79,] 0.9999743 5.146744e-05 2.573372e-05 [80,] 0.9999554 8.921703e-05 4.460851e-05 [81,] 0.9999922 1.564696e-05 7.823480e-06 [82,] 0.9999985 2.991626e-06 1.495813e-06 [83,] 0.9999972 5.623800e-06 2.811900e-06 [84,] 0.9999947 1.062858e-05 5.314289e-06 [85,] 0.9999926 1.477871e-05 7.389353e-06 [86,] 0.9999897 2.054951e-05 1.027475e-05 [87,] 0.9999818 3.642837e-05 1.821419e-05 [88,] 0.9999715 5.694966e-05 2.847483e-05 [89,] 0.9999759 4.826497e-05 2.413249e-05 [90,] 0.9999694 6.122223e-05 3.061112e-05 [91,] 0.9999809 3.819422e-05 1.909711e-05 [92,] 0.9999714 5.717682e-05 2.858841e-05 [93,] 0.9999688 6.230703e-05 3.115352e-05 [94,] 0.9999443 1.113423e-04 5.567114e-05 [95,] 0.9999072 1.856995e-04 9.284973e-05 [96,] 0.9998809 2.382284e-04 1.191142e-04 [97,] 0.9999141 1.718697e-04 8.593485e-05 [98,] 0.9998606 2.787954e-04 1.393977e-04 [99,] 0.9998225 3.550043e-04 1.775021e-04 [100,] 0.9996883 6.234607e-04 3.117303e-04 [101,] 0.9994824 1.035155e-03 5.175773e-04 [102,] 0.9991829 1.634168e-03 8.170841e-04 [103,] 0.9987228 2.554351e-03 1.277175e-03 [104,] 0.9983775 3.244992e-03 1.622496e-03 [105,] 0.9986252 2.749626e-03 1.374813e-03 [106,] 0.9976590 4.682032e-03 2.341016e-03 [107,] 0.9987583 2.483395e-03 1.241697e-03 [108,] 0.9994305 1.138918e-03 5.694589e-04 [109,] 0.9990811 1.837738e-03 9.188688e-04 [110,] 0.9985175 2.965013e-03 1.482507e-03 [111,] 0.9990392 1.921522e-03 9.607612e-04 [112,] 0.9999237 1.526932e-04 7.634661e-05 [113,] 0.9998986 2.028082e-04 1.014041e-04 [114,] 0.9998058 3.884453e-04 1.942226e-04 [115,] 0.9997196 5.607211e-04 2.803606e-04 [116,] 0.9997305 5.390957e-04 2.695479e-04 [117,] 0.9996304 7.391254e-04 3.695627e-04 [118,] 0.9995018 9.964031e-04 4.982016e-04 [119,] 0.9989852 2.029631e-03 1.014816e-03 [120,] 0.9985158 2.968449e-03 1.484225e-03 [121,] 0.9984824 3.035289e-03 1.517645e-03 [122,] 0.9993962 1.207616e-03 6.038080e-04 [123,] 0.9994691 1.061760e-03 5.308801e-04 [124,] 0.9985820 2.836090e-03 1.418045e-03 [125,] 0.9969090 6.182085e-03 3.091042e-03 [126,] 0.9946551 1.068988e-02 5.344938e-03 [127,] 0.9863432 2.731351e-02 1.365676e-02 [128,] 0.9820113 3.597730e-02 1.798865e-02 [129,] 0.9560484 8.790322e-02 4.395161e-02 [130,] 0.9088855 1.822290e-01 9.111449e-02 [131,] 0.8066603 3.866795e-01 1.933397e-01 > postscript(file="/var/www/rcomp/tmp/1zmib1323964202.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/2k63i1323964203.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/rcomp/tmp/3obgp1323964203.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/49t4w1323964203.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/5xzcl1323964203.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 23767.9224 -22451.6230 -22767.8788 -17382.5500 22063.4900 -17220.0176 7 8 9 10 11 12 -1756.4448 -904.4451 3623.0880 56416.0821 -5478.3827 537.2014 13 14 15 16 17 18 -35980.5988 12482.6102 21164.6669 -12262.3408 -21356.6694 2983.9560 19 20 21 22 23 24 -23461.3389 -28701.7060 -28882.8931 -17338.4653 65909.6415 3749.0144 25 26 27 28 29 30 -15902.7913 39418.5787 -43943.7067 -55532.0050 58279.0229 20831.3296 31 32 33 34 35 36 41871.9419 23433.6297 -23661.5759 63478.5169 22546.5447 -14827.5311 37 38 39 40 41 42 73138.1365 -2778.3876 16085.0039 -40575.4736 18749.3616 12442.9720 43 44 45 46 47 48 -15753.6939 -15739.6085 -2234.6294 -10723.9132 -5436.5234 32631.4414 49 50 51 52 53 54 -4881.3271 28457.5857 -9290.5176 -5931.1849 68560.9998 57314.6650 55 56 57 58 59 60 24767.9341 -6857.3620 52534.7646 -4268.8050 -23080.1649 38639.1160 61 62 63 64 65 66 18568.3874 -27566.1152 -19953.3161 -15415.5851 9625.8274 -16164.2391 67 68 69 70 71 72 -65186.9640 -22173.8436 -19634.9769 833.5426 22427.4567 -17408.8987 73 74 75 76 77 78 -25366.7277 10002.5094 3348.0140 8558.8101 -5210.9504 -66032.1844 79 80 81 82 83 84 -3431.2654 -31843.2078 -30151.3733 99707.7501 -20703.9332 7040.3492 85 86 87 88 89 90 -14866.3715 858.5620 -55732.2114 -38617.7516 -680.2383 150.0242 91 92 93 94 95 96 -17081.9458 -9611.6296 8786.5845 15550.6595 -25551.6271 -5250.6961 97 98 99 100 101 102 33656.3251 -17196.3854 30728.2942 -2674.2259 6552.3593 -19043.6380 103 104 105 106 107 108 28907.7458 -8653.5588 -17422.6791 -6287.0101 -5895.5445 6704.2355 109 110 111 112 113 114 -14102.7884 -11358.1902 -23380.0252 1066.3719 -30051.5653 -25628.9103 115 116 117 118 119 120 -14110.5020 -14102.7884 28171.6009 -29544.2762 12176.5505 -2332.1121 121 122 123 124 125 126 15198.5452 843.1652 -5727.2281 31767.9347 5136.2531 -17442.6281 127 128 129 130 131 132 -1384.9743 31169.2501 27843.6525 -8829.4730 -12998.4730 13684.0098 133 134 135 136 137 138 -9441.0166 30897.0233 -11159.0166 5598.2137 -14102.7884 17036.5981 139 140 141 142 143 144 13591.7870 -9870.7593 -17880.9584 15603.0179 -6196.5789 148.0740 > postscript(file="/var/www/rcomp/tmp/6ek5m1323964203.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 23767.9224 NA 1 -22451.6230 23767.9224 2 -22767.8788 -22451.6230 3 -17382.5500 -22767.8788 4 22063.4900 -17382.5500 5 -17220.0176 22063.4900 6 -1756.4448 -17220.0176 7 -904.4451 -1756.4448 8 3623.0880 -904.4451 9 56416.0821 3623.0880 10 -5478.3827 56416.0821 11 537.2014 -5478.3827 12 -35980.5988 537.2014 13 12482.6102 -35980.5988 14 21164.6669 12482.6102 15 -12262.3408 21164.6669 16 -21356.6694 -12262.3408 17 2983.9560 -21356.6694 18 -23461.3389 2983.9560 19 -28701.7060 -23461.3389 20 -28882.8931 -28701.7060 21 -17338.4653 -28882.8931 22 65909.6415 -17338.4653 23 3749.0144 65909.6415 24 -15902.7913 3749.0144 25 39418.5787 -15902.7913 26 -43943.7067 39418.5787 27 -55532.0050 -43943.7067 28 58279.0229 -55532.0050 29 20831.3296 58279.0229 30 41871.9419 20831.3296 31 23433.6297 41871.9419 32 -23661.5759 23433.6297 33 63478.5169 -23661.5759 34 22546.5447 63478.5169 35 -14827.5311 22546.5447 36 73138.1365 -14827.5311 37 -2778.3876 73138.1365 38 16085.0039 -2778.3876 39 -40575.4736 16085.0039 40 18749.3616 -40575.4736 41 12442.9720 18749.3616 42 -15753.6939 12442.9720 43 -15739.6085 -15753.6939 44 -2234.6294 -15739.6085 45 -10723.9132 -2234.6294 46 -5436.5234 -10723.9132 47 32631.4414 -5436.5234 48 -4881.3271 32631.4414 49 28457.5857 -4881.3271 50 -9290.5176 28457.5857 51 -5931.1849 -9290.5176 52 68560.9998 -5931.1849 53 57314.6650 68560.9998 54 24767.9341 57314.6650 55 -6857.3620 24767.9341 56 52534.7646 -6857.3620 57 -4268.8050 52534.7646 58 -23080.1649 -4268.8050 59 38639.1160 -23080.1649 60 18568.3874 38639.1160 61 -27566.1152 18568.3874 62 -19953.3161 -27566.1152 63 -15415.5851 -19953.3161 64 9625.8274 -15415.5851 65 -16164.2391 9625.8274 66 -65186.9640 -16164.2391 67 -22173.8436 -65186.9640 68 -19634.9769 -22173.8436 69 833.5426 -19634.9769 70 22427.4567 833.5426 71 -17408.8987 22427.4567 72 -25366.7277 -17408.8987 73 10002.5094 -25366.7277 74 3348.0140 10002.5094 75 8558.8101 3348.0140 76 -5210.9504 8558.8101 77 -66032.1844 -5210.9504 78 -3431.2654 -66032.1844 79 -31843.2078 -3431.2654 80 -30151.3733 -31843.2078 81 99707.7501 -30151.3733 82 -20703.9332 99707.7501 83 7040.3492 -20703.9332 84 -14866.3715 7040.3492 85 858.5620 -14866.3715 86 -55732.2114 858.5620 87 -38617.7516 -55732.2114 88 -680.2383 -38617.7516 89 150.0242 -680.2383 90 -17081.9458 150.0242 91 -9611.6296 -17081.9458 92 8786.5845 -9611.6296 93 15550.6595 8786.5845 94 -25551.6271 15550.6595 95 -5250.6961 -25551.6271 96 33656.3251 -5250.6961 97 -17196.3854 33656.3251 98 30728.2942 -17196.3854 99 -2674.2259 30728.2942 100 6552.3593 -2674.2259 101 -19043.6380 6552.3593 102 28907.7458 -19043.6380 103 -8653.5588 28907.7458 104 -17422.6791 -8653.5588 105 -6287.0101 -17422.6791 106 -5895.5445 -6287.0101 107 6704.2355 -5895.5445 108 -14102.7884 6704.2355 109 -11358.1902 -14102.7884 110 -23380.0252 -11358.1902 111 1066.3719 -23380.0252 112 -30051.5653 1066.3719 113 -25628.9103 -30051.5653 114 -14110.5020 -25628.9103 115 -14102.7884 -14110.5020 116 28171.6009 -14102.7884 117 -29544.2762 28171.6009 118 12176.5505 -29544.2762 119 -2332.1121 12176.5505 120 15198.5452 -2332.1121 121 843.1652 15198.5452 122 -5727.2281 843.1652 123 31767.9347 -5727.2281 124 5136.2531 31767.9347 125 -17442.6281 5136.2531 126 -1384.9743 -17442.6281 127 31169.2501 -1384.9743 128 27843.6525 31169.2501 129 -8829.4730 27843.6525 130 -12998.4730 -8829.4730 131 13684.0098 -12998.4730 132 -9441.0166 13684.0098 133 30897.0233 -9441.0166 134 -11159.0166 30897.0233 135 5598.2137 -11159.0166 136 -14102.7884 5598.2137 137 17036.5981 -14102.7884 138 13591.7870 17036.5981 139 -9870.7593 13591.7870 140 -17880.9584 -9870.7593 141 15603.0179 -17880.9584 142 -6196.5789 15603.0179 143 148.0740 -6196.5789 144 NA 148.0740 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -22451.6230 23767.9224 [2,] -22767.8788 -22451.6230 [3,] -17382.5500 -22767.8788 [4,] 22063.4900 -17382.5500 [5,] -17220.0176 22063.4900 [6,] -1756.4448 -17220.0176 [7,] -904.4451 -1756.4448 [8,] 3623.0880 -904.4451 [9,] 56416.0821 3623.0880 [10,] -5478.3827 56416.0821 [11,] 537.2014 -5478.3827 [12,] -35980.5988 537.2014 [13,] 12482.6102 -35980.5988 [14,] 21164.6669 12482.6102 [15,] -12262.3408 21164.6669 [16,] -21356.6694 -12262.3408 [17,] 2983.9560 -21356.6694 [18,] -23461.3389 2983.9560 [19,] -28701.7060 -23461.3389 [20,] -28882.8931 -28701.7060 [21,] -17338.4653 -28882.8931 [22,] 65909.6415 -17338.4653 [23,] 3749.0144 65909.6415 [24,] -15902.7913 3749.0144 [25,] 39418.5787 -15902.7913 [26,] -43943.7067 39418.5787 [27,] -55532.0050 -43943.7067 [28,] 58279.0229 -55532.0050 [29,] 20831.3296 58279.0229 [30,] 41871.9419 20831.3296 [31,] 23433.6297 41871.9419 [32,] -23661.5759 23433.6297 [33,] 63478.5169 -23661.5759 [34,] 22546.5447 63478.5169 [35,] -14827.5311 22546.5447 [36,] 73138.1365 -14827.5311 [37,] -2778.3876 73138.1365 [38,] 16085.0039 -2778.3876 [39,] -40575.4736 16085.0039 [40,] 18749.3616 -40575.4736 [41,] 12442.9720 18749.3616 [42,] -15753.6939 12442.9720 [43,] -15739.6085 -15753.6939 [44,] -2234.6294 -15739.6085 [45,] -10723.9132 -2234.6294 [46,] -5436.5234 -10723.9132 [47,] 32631.4414 -5436.5234 [48,] -4881.3271 32631.4414 [49,] 28457.5857 -4881.3271 [50,] -9290.5176 28457.5857 [51,] -5931.1849 -9290.5176 [52,] 68560.9998 -5931.1849 [53,] 57314.6650 68560.9998 [54,] 24767.9341 57314.6650 [55,] -6857.3620 24767.9341 [56,] 52534.7646 -6857.3620 [57,] -4268.8050 52534.7646 [58,] -23080.1649 -4268.8050 [59,] 38639.1160 -23080.1649 [60,] 18568.3874 38639.1160 [61,] -27566.1152 18568.3874 [62,] -19953.3161 -27566.1152 [63,] -15415.5851 -19953.3161 [64,] 9625.8274 -15415.5851 [65,] -16164.2391 9625.8274 [66,] -65186.9640 -16164.2391 [67,] -22173.8436 -65186.9640 [68,] -19634.9769 -22173.8436 [69,] 833.5426 -19634.9769 [70,] 22427.4567 833.5426 [71,] -17408.8987 22427.4567 [72,] -25366.7277 -17408.8987 [73,] 10002.5094 -25366.7277 [74,] 3348.0140 10002.5094 [75,] 8558.8101 3348.0140 [76,] -5210.9504 8558.8101 [77,] -66032.1844 -5210.9504 [78,] -3431.2654 -66032.1844 [79,] -31843.2078 -3431.2654 [80,] -30151.3733 -31843.2078 [81,] 99707.7501 -30151.3733 [82,] -20703.9332 99707.7501 [83,] 7040.3492 -20703.9332 [84,] -14866.3715 7040.3492 [85,] 858.5620 -14866.3715 [86,] -55732.2114 858.5620 [87,] -38617.7516 -55732.2114 [88,] -680.2383 -38617.7516 [89,] 150.0242 -680.2383 [90,] -17081.9458 150.0242 [91,] -9611.6296 -17081.9458 [92,] 8786.5845 -9611.6296 [93,] 15550.6595 8786.5845 [94,] -25551.6271 15550.6595 [95,] -5250.6961 -25551.6271 [96,] 33656.3251 -5250.6961 [97,] -17196.3854 33656.3251 [98,] 30728.2942 -17196.3854 [99,] -2674.2259 30728.2942 [100,] 6552.3593 -2674.2259 [101,] -19043.6380 6552.3593 [102,] 28907.7458 -19043.6380 [103,] -8653.5588 28907.7458 [104,] -17422.6791 -8653.5588 [105,] -6287.0101 -17422.6791 [106,] -5895.5445 -6287.0101 [107,] 6704.2355 -5895.5445 [108,] -14102.7884 6704.2355 [109,] -11358.1902 -14102.7884 [110,] -23380.0252 -11358.1902 [111,] 1066.3719 -23380.0252 [112,] -30051.5653 1066.3719 [113,] -25628.9103 -30051.5653 [114,] -14110.5020 -25628.9103 [115,] -14102.7884 -14110.5020 [116,] 28171.6009 -14102.7884 [117,] -29544.2762 28171.6009 [118,] 12176.5505 -29544.2762 [119,] -2332.1121 12176.5505 [120,] 15198.5452 -2332.1121 [121,] 843.1652 15198.5452 [122,] -5727.2281 843.1652 [123,] 31767.9347 -5727.2281 [124,] 5136.2531 31767.9347 [125,] -17442.6281 5136.2531 [126,] -1384.9743 -17442.6281 [127,] 31169.2501 -1384.9743 [128,] 27843.6525 31169.2501 [129,] -8829.4730 27843.6525 [130,] -12998.4730 -8829.4730 [131,] 13684.0098 -12998.4730 [132,] -9441.0166 13684.0098 [133,] 30897.0233 -9441.0166 [134,] -11159.0166 30897.0233 [135,] 5598.2137 -11159.0166 [136,] -14102.7884 5598.2137 [137,] 17036.5981 -14102.7884 [138,] 13591.7870 17036.5981 [139,] -9870.7593 13591.7870 [140,] -17880.9584 -9870.7593 [141,] 15603.0179 -17880.9584 [142,] -6196.5789 15603.0179 [143,] 148.0740 -6196.5789 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -22451.6230 23767.9224 2 -22767.8788 -22451.6230 3 -17382.5500 -22767.8788 4 22063.4900 -17382.5500 5 -17220.0176 22063.4900 6 -1756.4448 -17220.0176 7 -904.4451 -1756.4448 8 3623.0880 -904.4451 9 56416.0821 3623.0880 10 -5478.3827 56416.0821 11 537.2014 -5478.3827 12 -35980.5988 537.2014 13 12482.6102 -35980.5988 14 21164.6669 12482.6102 15 -12262.3408 21164.6669 16 -21356.6694 -12262.3408 17 2983.9560 -21356.6694 18 -23461.3389 2983.9560 19 -28701.7060 -23461.3389 20 -28882.8931 -28701.7060 21 -17338.4653 -28882.8931 22 65909.6415 -17338.4653 23 3749.0144 65909.6415 24 -15902.7913 3749.0144 25 39418.5787 -15902.7913 26 -43943.7067 39418.5787 27 -55532.0050 -43943.7067 28 58279.0229 -55532.0050 29 20831.3296 58279.0229 30 41871.9419 20831.3296 31 23433.6297 41871.9419 32 -23661.5759 23433.6297 33 63478.5169 -23661.5759 34 22546.5447 63478.5169 35 -14827.5311 22546.5447 36 73138.1365 -14827.5311 37 -2778.3876 73138.1365 38 16085.0039 -2778.3876 39 -40575.4736 16085.0039 40 18749.3616 -40575.4736 41 12442.9720 18749.3616 42 -15753.6939 12442.9720 43 -15739.6085 -15753.6939 44 -2234.6294 -15739.6085 45 -10723.9132 -2234.6294 46 -5436.5234 -10723.9132 47 32631.4414 -5436.5234 48 -4881.3271 32631.4414 49 28457.5857 -4881.3271 50 -9290.5176 28457.5857 51 -5931.1849 -9290.5176 52 68560.9998 -5931.1849 53 57314.6650 68560.9998 54 24767.9341 57314.6650 55 -6857.3620 24767.9341 56 52534.7646 -6857.3620 57 -4268.8050 52534.7646 58 -23080.1649 -4268.8050 59 38639.1160 -23080.1649 60 18568.3874 38639.1160 61 -27566.1152 18568.3874 62 -19953.3161 -27566.1152 63 -15415.5851 -19953.3161 64 9625.8274 -15415.5851 65 -16164.2391 9625.8274 66 -65186.9640 -16164.2391 67 -22173.8436 -65186.9640 68 -19634.9769 -22173.8436 69 833.5426 -19634.9769 70 22427.4567 833.5426 71 -17408.8987 22427.4567 72 -25366.7277 -17408.8987 73 10002.5094 -25366.7277 74 3348.0140 10002.5094 75 8558.8101 3348.0140 76 -5210.9504 8558.8101 77 -66032.1844 -5210.9504 78 -3431.2654 -66032.1844 79 -31843.2078 -3431.2654 80 -30151.3733 -31843.2078 81 99707.7501 -30151.3733 82 -20703.9332 99707.7501 83 7040.3492 -20703.9332 84 -14866.3715 7040.3492 85 858.5620 -14866.3715 86 -55732.2114 858.5620 87 -38617.7516 -55732.2114 88 -680.2383 -38617.7516 89 150.0242 -680.2383 90 -17081.9458 150.0242 91 -9611.6296 -17081.9458 92 8786.5845 -9611.6296 93 15550.6595 8786.5845 94 -25551.6271 15550.6595 95 -5250.6961 -25551.6271 96 33656.3251 -5250.6961 97 -17196.3854 33656.3251 98 30728.2942 -17196.3854 99 -2674.2259 30728.2942 100 6552.3593 -2674.2259 101 -19043.6380 6552.3593 102 28907.7458 -19043.6380 103 -8653.5588 28907.7458 104 -17422.6791 -8653.5588 105 -6287.0101 -17422.6791 106 -5895.5445 -6287.0101 107 6704.2355 -5895.5445 108 -14102.7884 6704.2355 109 -11358.1902 -14102.7884 110 -23380.0252 -11358.1902 111 1066.3719 -23380.0252 112 -30051.5653 1066.3719 113 -25628.9103 -30051.5653 114 -14110.5020 -25628.9103 115 -14102.7884 -14110.5020 116 28171.6009 -14102.7884 117 -29544.2762 28171.6009 118 12176.5505 -29544.2762 119 -2332.1121 12176.5505 120 15198.5452 -2332.1121 121 843.1652 15198.5452 122 -5727.2281 843.1652 123 31767.9347 -5727.2281 124 5136.2531 31767.9347 125 -17442.6281 5136.2531 126 -1384.9743 -17442.6281 127 31169.2501 -1384.9743 128 27843.6525 31169.2501 129 -8829.4730 27843.6525 130 -12998.4730 -8829.4730 131 13684.0098 -12998.4730 132 -9441.0166 13684.0098 133 30897.0233 -9441.0166 134 -11159.0166 30897.0233 135 5598.2137 -11159.0166 136 -14102.7884 5598.2137 137 17036.5981 -14102.7884 138 13591.7870 17036.5981 139 -9870.7593 13591.7870 140 -17880.9584 -9870.7593 141 15603.0179 -17880.9584 142 -6196.5789 15603.0179 143 148.0740 -6196.5789 > 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/rcomp/tmp/7g56b1323964203.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/8grgg1323964203.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/9ezsz1323964203.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/rcomp/tmp/105vht1323964203.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/rcomp/tmp/117yjg1323964203.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/rcomp/tmp/12rodp1323964203.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/rcomp/tmp/13npa21323964203.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/rcomp/tmp/149goq1323964203.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/rcomp/tmp/15lv211323964203.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/rcomp/tmp/16nii21323964203.tab") + } > > try(system("convert tmp/1zmib1323964202.ps tmp/1zmib1323964202.png",intern=TRUE)) character(0) > try(system("convert tmp/2k63i1323964203.ps tmp/2k63i1323964203.png",intern=TRUE)) character(0) > try(system("convert tmp/3obgp1323964203.ps tmp/3obgp1323964203.png",intern=TRUE)) character(0) > try(system("convert tmp/49t4w1323964203.ps tmp/49t4w1323964203.png",intern=TRUE)) character(0) > try(system("convert tmp/5xzcl1323964203.ps tmp/5xzcl1323964203.png",intern=TRUE)) character(0) > try(system("convert tmp/6ek5m1323964203.ps tmp/6ek5m1323964203.png",intern=TRUE)) character(0) > try(system("convert tmp/7g56b1323964203.ps tmp/7g56b1323964203.png",intern=TRUE)) character(0) > try(system("convert tmp/8grgg1323964203.ps tmp/8grgg1323964203.png",intern=TRUE)) character(0) > try(system("convert tmp/9ezsz1323964203.ps tmp/9ezsz1323964203.png",intern=TRUE)) character(0) > try(system("convert tmp/105vht1323964203.ps tmp/105vht1323964203.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.620 0.760 7.181