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Type 'q()' to quit R. > x <- array(list(142773 + ,0 + ,142773 + ,149657 + ,133639 + ,0 + ,133639 + ,142773 + ,128332 + ,0 + ,128332 + ,133639 + ,120297 + ,0 + ,120297 + ,128332 + ,118632 + ,0 + ,118632 + ,120297 + ,155276 + ,0 + ,155276 + ,118632 + ,169316 + ,0 + ,169316 + ,155276 + ,167395 + ,0 + ,167395 + ,169316 + ,157939 + ,0 + ,157939 + ,167395 + ,149601 + ,0 + ,149601 + ,157939 + ,146310 + ,0 + ,146310 + ,149601 + ,141579 + ,0 + ,141579 + ,146310 + ,136473 + ,0 + ,136473 + ,141579 + ,129818 + ,0 + ,129818 + ,136473 + ,124226 + ,0 + ,124226 + ,129818 + ,116428 + ,0 + ,116428 + ,124226 + ,116440 + ,0 + ,116440 + ,116428 + ,147747 + ,0 + ,147747 + ,116440 + ,160069 + ,0 + ,160069 + ,147747 + ,163129 + ,0 + ,163129 + ,160069 + ,151108 + ,0 + ,151108 + ,163129 + ,141481 + ,0 + ,141481 + ,151108 + ,139174 + ,0 + ,139174 + ,141481 + ,134066 + ,0 + ,134066 + ,139174 + ,130104 + ,0 + ,130104 + ,134066 + ,123090 + ,0 + ,123090 + ,130104 + ,116598 + ,0 + ,116598 + ,123090 + ,109627 + ,0 + ,109627 + ,116598 + ,105428 + ,0 + ,105428 + ,109627 + ,137272 + ,0 + ,137272 + ,105428 + ,159836 + ,0 + ,159836 + ,137272 + ,155283 + ,0 + ,155283 + ,159836 + ,141514 + ,0 + ,141514 + ,155283 + ,131852 + ,0 + ,131852 + ,141514 + ,130691 + ,0 + ,130691 + ,131852 + ,128461 + ,0 + ,128461 + ,130691 + ,123066 + ,0 + ,123066 + ,128461 + ,117599 + ,0 + ,117599 + ,123066 + ,111599 + ,0 + ,111599 + ,117599 + ,105395 + ,0 + ,105395 + ,111599 + ,102334 + ,0 + ,102334 + ,105395 + ,131305 + ,0 + ,131305 + ,102334 + ,149033 + ,0 + ,149033 + ,131305 + ,144954 + ,0 + ,144954 + ,149033 + ,132404 + ,0 + ,132404 + ,144954 + ,122104 + ,0 + ,122104 + ,132404 + ,118755 + ,0 + ,118755 + ,122104 + ,116222 + ,1 + ,116222 + ,118755 + ,110924 + ,1 + ,110924 + ,116222 + ,103753 + ,1 + ,103753 + ,110924 + ,99983 + ,1 + ,99983 + ,103753 + ,93302 + ,1 + ,93302 + ,99983 + ,91496 + ,1 + ,91496 + ,93302 + ,119321 + ,1 + ,119321 + ,91496 + ,139261 + ,1 + ,139261 + ,119321 + ,133739 + ,1 + ,133739 + ,139261 + ,123913 + ,1 + ,123913 + ,133739 + ,113438 + ,1 + ,113438 + ,123913 + ,109416 + ,1 + ,109416 + ,113438 + ,109406 + ,1 + ,109406 + ,109416 + ,105645 + ,1 + ,105645 + ,109406 + ,101328 + ,1 + ,101328 + ,105645 + ,97686 + ,1 + ,97686 + ,101328 + ,93093 + ,1 + ,93093 + ,97686 + ,91382 + ,1 + ,91382 + ,93093 + ,122257 + ,1 + ,122257 + ,91382 + ,139183 + ,1 + ,139183 + ,122257 + ,139887 + ,1 + ,139887 + ,139183 + ,131822 + ,1 + ,131822 + ,139887 + ,116805 + ,1 + ,116805 + ,131822 + ,113706 + ,1 + ,113706 + ,116805 + ,113012 + ,1 + ,113012 + ,113706 + ,110452 + ,1 + ,110452 + ,113012 + ,107005 + ,1 + ,107005 + ,110452 + ,102841 + ,1 + ,102841 + ,107005 + ,98173 + ,1 + ,98173 + ,102841 + ,98181 + ,1 + ,98181 + ,98173 + ,137277 + ,1 + ,137277 + ,98181 + ,147579 + ,1 + ,147579 + ,137277 + ,146571 + ,1 + ,146571 + ,147579 + ,138920 + ,1 + ,138920 + ,146571 + ,130340 + ,1 + ,130340 + ,138920 + ,128140 + ,1 + ,128140 + ,130340 + ,127059 + ,1 + ,127059 + ,128140 + ,122860 + ,1 + ,122860 + ,127059 + ,117702 + ,1 + ,117702 + ,122860 + ,113537 + ,1 + ,113537 + ,117702 + ,108366 + ,1 + ,108366 + ,113537 + ,111078 + ,1 + ,111078 + ,108366 + ,150739 + ,1 + ,150739 + ,111078 + ,159129 + ,1 + ,159129 + ,150739 + ,157928 + ,1 + ,157928 + ,159129 + ,147768 + ,1 + ,147768 + ,157928 + ,137507 + ,1 + ,137507 + ,147768 + ,136919 + ,1 + ,136919 + ,137507) + ,dim=c(4 + ,95) + ,dimnames=list(c('Y' + ,'X' + ,'Y1' + ,'Y2') + ,1:95)) > y <- array(NA,dim=c(4,95),dimnames=list(c('Y','X','Y1','Y2'),1:95)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'Linear Trend' > par2 = 'Include Monthly 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 X Y1 Y2 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 142773 0 142773 149657 1 0 0 0 0 0 0 0 0 0 0 1 2 133639 0 133639 142773 0 1 0 0 0 0 0 0 0 0 0 2 3 128332 0 128332 133639 0 0 1 0 0 0 0 0 0 0 0 3 4 120297 0 120297 128332 0 0 0 1 0 0 0 0 0 0 0 4 5 118632 0 118632 120297 0 0 0 0 1 0 0 0 0 0 0 5 6 155276 0 155276 118632 0 0 0 0 0 1 0 0 0 0 0 6 7 169316 0 169316 155276 0 0 0 0 0 0 1 0 0 0 0 7 8 167395 0 167395 169316 0 0 0 0 0 0 0 1 0 0 0 8 9 157939 0 157939 167395 0 0 0 0 0 0 0 0 1 0 0 9 10 149601 0 149601 157939 0 0 0 0 0 0 0 0 0 1 0 10 11 146310 0 146310 149601 0 0 0 0 0 0 0 0 0 0 1 11 12 141579 0 141579 146310 0 0 0 0 0 0 0 0 0 0 0 12 13 136473 0 136473 141579 1 0 0 0 0 0 0 0 0 0 0 13 14 129818 0 129818 136473 0 1 0 0 0 0 0 0 0 0 0 14 15 124226 0 124226 129818 0 0 1 0 0 0 0 0 0 0 0 15 16 116428 0 116428 124226 0 0 0 1 0 0 0 0 0 0 0 16 17 116440 0 116440 116428 0 0 0 0 1 0 0 0 0 0 0 17 18 147747 0 147747 116440 0 0 0 0 0 1 0 0 0 0 0 18 19 160069 0 160069 147747 0 0 0 0 0 0 1 0 0 0 0 19 20 163129 0 163129 160069 0 0 0 0 0 0 0 1 0 0 0 20 21 151108 0 151108 163129 0 0 0 0 0 0 0 0 1 0 0 21 22 141481 0 141481 151108 0 0 0 0 0 0 0 0 0 1 0 22 23 139174 0 139174 141481 0 0 0 0 0 0 0 0 0 0 1 23 24 134066 0 134066 139174 0 0 0 0 0 0 0 0 0 0 0 24 25 130104 0 130104 134066 1 0 0 0 0 0 0 0 0 0 0 25 26 123090 0 123090 130104 0 1 0 0 0 0 0 0 0 0 0 26 27 116598 0 116598 123090 0 0 1 0 0 0 0 0 0 0 0 27 28 109627 0 109627 116598 0 0 0 1 0 0 0 0 0 0 0 28 29 105428 0 105428 109627 0 0 0 0 1 0 0 0 0 0 0 29 30 137272 0 137272 105428 0 0 0 0 0 1 0 0 0 0 0 30 31 159836 0 159836 137272 0 0 0 0 0 0 1 0 0 0 0 31 32 155283 0 155283 159836 0 0 0 0 0 0 0 1 0 0 0 32 33 141514 0 141514 155283 0 0 0 0 0 0 0 0 1 0 0 33 34 131852 0 131852 141514 0 0 0 0 0 0 0 0 0 1 0 34 35 130691 0 130691 131852 0 0 0 0 0 0 0 0 0 0 1 35 36 128461 0 128461 130691 0 0 0 0 0 0 0 0 0 0 0 36 37 123066 0 123066 128461 1 0 0 0 0 0 0 0 0 0 0 37 38 117599 0 117599 123066 0 1 0 0 0 0 0 0 0 0 0 38 39 111599 0 111599 117599 0 0 1 0 0 0 0 0 0 0 0 39 40 105395 0 105395 111599 0 0 0 1 0 0 0 0 0 0 0 40 41 102334 0 102334 105395 0 0 0 0 1 0 0 0 0 0 0 41 42 131305 0 131305 102334 0 0 0 0 0 1 0 0 0 0 0 42 43 149033 0 149033 131305 0 0 0 0 0 0 1 0 0 0 0 43 44 144954 0 144954 149033 0 0 0 0 0 0 0 1 0 0 0 44 45 132404 0 132404 144954 0 0 0 0 0 0 0 0 1 0 0 45 46 122104 0 122104 132404 0 0 0 0 0 0 0 0 0 1 0 46 47 118755 0 118755 122104 0 0 0 0 0 0 0 0 0 0 1 47 48 116222 1 116222 118755 0 0 0 0 0 0 0 0 0 0 0 48 49 110924 1 110924 116222 1 0 0 0 0 0 0 0 0 0 0 49 50 103753 1 103753 110924 0 1 0 0 0 0 0 0 0 0 0 50 51 99983 1 99983 103753 0 0 1 0 0 0 0 0 0 0 0 51 52 93302 1 93302 99983 0 0 0 1 0 0 0 0 0 0 0 52 53 91496 1 91496 93302 0 0 0 0 1 0 0 0 0 0 0 53 54 119321 1 119321 91496 0 0 0 0 0 1 0 0 0 0 0 54 55 139261 1 139261 119321 0 0 0 0 0 0 1 0 0 0 0 55 56 133739 1 133739 139261 0 0 0 0 0 0 0 1 0 0 0 56 57 123913 1 123913 133739 0 0 0 0 0 0 0 0 1 0 0 57 58 113438 1 113438 123913 0 0 0 0 0 0 0 0 0 1 0 58 59 109416 1 109416 113438 0 0 0 0 0 0 0 0 0 0 1 59 60 109406 1 109406 109416 0 0 0 0 0 0 0 0 0 0 0 60 61 105645 1 105645 109406 1 0 0 0 0 0 0 0 0 0 0 61 62 101328 1 101328 105645 0 1 0 0 0 0 0 0 0 0 0 62 63 97686 1 97686 101328 0 0 1 0 0 0 0 0 0 0 0 63 64 93093 1 93093 97686 0 0 0 1 0 0 0 0 0 0 0 64 65 91382 1 91382 93093 0 0 0 0 1 0 0 0 0 0 0 65 66 122257 1 122257 91382 0 0 0 0 0 1 0 0 0 0 0 66 67 139183 1 139183 122257 0 0 0 0 0 0 1 0 0 0 0 67 68 139887 1 139887 139183 0 0 0 0 0 0 0 1 0 0 0 68 69 131822 1 131822 139887 0 0 0 0 0 0 0 0 1 0 0 69 70 116805 1 116805 131822 0 0 0 0 0 0 0 0 0 1 0 70 71 113706 1 113706 116805 0 0 0 0 0 0 0 0 0 0 1 71 72 113012 1 113012 113706 0 0 0 0 0 0 0 0 0 0 0 72 73 110452 1 110452 113012 1 0 0 0 0 0 0 0 0 0 0 73 74 107005 1 107005 110452 0 1 0 0 0 0 0 0 0 0 0 74 75 102841 1 102841 107005 0 0 1 0 0 0 0 0 0 0 0 75 76 98173 1 98173 102841 0 0 0 1 0 0 0 0 0 0 0 76 77 98181 1 98181 98173 0 0 0 0 1 0 0 0 0 0 0 77 78 137277 1 137277 98181 0 0 0 0 0 1 0 0 0 0 0 78 79 147579 1 147579 137277 0 0 0 0 0 0 1 0 0 0 0 79 80 146571 1 146571 147579 0 0 0 0 0 0 0 1 0 0 0 80 81 138920 1 138920 146571 0 0 0 0 0 0 0 0 1 0 0 81 82 130340 1 130340 138920 0 0 0 0 0 0 0 0 0 1 0 82 83 128140 1 128140 130340 0 0 0 0 0 0 0 0 0 0 1 83 84 127059 1 127059 128140 0 0 0 0 0 0 0 0 0 0 0 84 85 122860 1 122860 127059 1 0 0 0 0 0 0 0 0 0 0 85 86 117702 1 117702 122860 0 1 0 0 0 0 0 0 0 0 0 86 87 113537 1 113537 117702 0 0 1 0 0 0 0 0 0 0 0 87 88 108366 1 108366 113537 0 0 0 1 0 0 0 0 0 0 0 88 89 111078 1 111078 108366 0 0 0 0 1 0 0 0 0 0 0 89 90 150739 1 150739 111078 0 0 0 0 0 1 0 0 0 0 0 90 91 159129 1 159129 150739 0 0 0 0 0 0 1 0 0 0 0 91 92 157928 1 157928 159129 0 0 0 0 0 0 0 1 0 0 0 92 93 147768 1 147768 157928 0 0 0 0 0 0 0 0 1 0 0 93 94 137507 1 137507 147768 0 0 0 0 0 0 0 0 0 1 0 94 95 136919 1 136919 137507 0 0 0 0 0 0 0 0 0 0 1 95 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) X Y1 Y2 M1 M2 4.928e-11 -2.986e-12 1.000e+00 8.761e-18 -3.600e-13 1.910e-13 M3 M4 M5 M6 M7 M8 9.581e-12 1.626e-12 2.274e-12 -4.420e-14 -1.805e-12 -1.533e-12 M9 M10 M11 t -7.360e-13 1.809e-13 1.873e-13 -5.195e-14 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -1.073e-11 -9.406e-13 2.211e-13 1.044e-12 5.442e-11 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 4.928e-11 1.183e-11 4.166e+00 7.87e-05 *** X -2.986e-12 3.103e-12 -9.620e-01 0.3388 Y1 1.000e+00 2.977e-16 3.359e+15 < 2e-16 *** Y2 8.761e-18 3.044e-16 2.900e-02 0.9771 M1 -3.600e-13 3.571e-12 -1.010e-01 0.9200 M2 1.910e-13 3.701e-12 5.200e-02 0.9590 M3 9.581e-12 3.715e-12 2.579e+00 0.0118 * M4 1.626e-12 3.953e-12 4.110e-01 0.6820 M5 2.274e-12 3.983e-12 5.710e-01 0.5697 M6 -4.420e-14 1.123e-11 -4.000e-03 0.9969 M7 -1.805e-12 6.415e-12 -2.810e-01 0.7792 M8 -1.533e-12 4.129e-12 -3.710e-01 0.7115 M9 -7.360e-13 4.652e-12 -1.580e-01 0.8747 M10 1.809e-13 4.360e-12 4.100e-02 0.9670 M11 1.873e-13 3.544e-12 5.300e-02 0.9580 t -5.195e-14 5.235e-14 -9.920e-01 0.3241 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 6.776e-12 on 79 degrees of freedom Multiple R-squared: 1, Adjusted R-squared: 1 F-statistic: 5.041e+31 on 15 and 79 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,] 0.000000e+00 0.000000e+00 1.000000e+00 [2,] 9.999805e-01 3.896189e-05 1.948094e-05 [3,] 5.746774e-11 1.149355e-10 1.000000e+00 [4,] 2.414253e-04 4.828506e-04 9.997586e-01 [5,] 6.349603e-01 7.300794e-01 3.650397e-01 [6,] 9.999997e-01 5.840708e-07 2.920354e-07 [7,] 1.840840e-01 3.681680e-01 8.159160e-01 [8,] 1.000000e+00 1.886755e-18 9.433773e-19 [9,] 3.980916e-01 7.961833e-01 6.019084e-01 [10,] 2.033823e-02 4.067646e-02 9.796618e-01 [11,] 5.931477e-02 1.186295e-01 9.406852e-01 [12,] 3.838635e-03 7.677269e-03 9.961614e-01 [13,] 1.664840e-01 3.329680e-01 8.335160e-01 [14,] 1.000000e+00 1.424648e-33 7.123242e-34 [15,] 9.086852e-04 1.817370e-03 9.990913e-01 [16,] 9.980287e-01 3.942636e-03 1.971318e-03 [17,] 1.418215e-01 2.836430e-01 8.581785e-01 [18,] 9.998451e-01 3.098964e-04 1.549482e-04 [19,] 9.170982e-13 1.834196e-12 1.000000e+00 [20,] 9.379760e-01 1.240479e-01 6.202397e-02 [21,] 2.095625e-11 4.191250e-11 1.000000e+00 [22,] 8.029441e-03 1.605888e-02 9.919706e-01 [23,] 2.179955e-03 4.359910e-03 9.978200e-01 [24,] 1.000000e+00 9.037487e-09 4.518743e-09 [25,] 8.244533e-01 3.510934e-01 1.755467e-01 [26,] 9.621504e-01 7.569919e-02 3.784959e-02 [27,] 2.280859e-15 4.561718e-15 1.000000e+00 [28,] 9.992858e-01 1.428342e-03 7.141711e-04 [29,] 1.037877e-01 2.075755e-01 8.962123e-01 [30,] 9.999998e-01 4.829024e-07 2.414512e-07 [31,] 1.573604e-08 3.147208e-08 1.000000e+00 [32,] 2.938091e-07 5.876181e-07 9.999997e-01 [33,] 9.970312e-01 5.937602e-03 2.968801e-03 [34,] 9.999997e-01 6.148928e-07 3.074464e-07 [35,] 1.000000e+00 5.627748e-10 2.813874e-10 [36,] 3.131959e-01 6.263919e-01 6.868041e-01 [37,] 1.991428e-01 3.982856e-01 8.008572e-01 [38,] 1.000000e+00 5.229425e-11 2.614713e-11 [39,] 9.841354e-01 3.172929e-02 1.586465e-02 [40,] 1.000000e+00 2.145182e-14 1.072591e-14 [41,] 7.568237e-04 1.513647e-03 9.992432e-01 [42,] 1.000000e+00 4.508933e-22 2.254467e-22 [43,] 8.521772e-01 2.956456e-01 1.478228e-01 [44,] 1.000000e+00 2.693181e-14 1.346591e-14 [45,] 2.394010e-01 4.788021e-01 7.605990e-01 [46,] 9.999978e-01 4.302135e-06 2.151068e-06 [47,] 9.659380e-01 6.812402e-02 3.406201e-02 [48,] 7.921269e-01 4.157461e-01 2.078731e-01 [49,] 4.555207e-08 9.110413e-08 1.000000e+00 [50,] 3.183252e-01 6.366505e-01 6.816748e-01 [51,] 2.979205e-01 5.958411e-01 7.020795e-01 [52,] 8.885234e-01 2.229533e-01 1.114766e-01 [53,] 9.990117e-06 1.998023e-05 9.999900e-01 [54,] 9.893809e-01 2.123827e-02 1.061914e-02 [55,] 6.939402e-11 1.387880e-10 1.000000e+00 [56,] 9.636668e-01 7.266639e-02 3.633320e-02 [57,] 1.642973e-07 3.285947e-07 9.999998e-01 [58,] 9.476808e-01 1.046384e-01 5.231922e-02 > postscript(file="/var/www/html/rcomp/tmp/1p0k91258645334.ps",horizontal=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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2qhxc1258645334.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3ji0c1258645334.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4ucep1258645334.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/516b71258645334.ps",horizontal=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 = 95 Frequency = 1 1 2 3 4 5 -6.970760e-12 -4.625257e-12 5.441831e-11 -3.400531e-12 -3.183944e-12 6 7 8 9 10 -2.576766e-12 -6.573865e-14 -3.190903e-12 -3.343013e-12 -2.228580e-12 11 12 13 14 15 -2.462519e-12 -1.905206e-12 -5.408049e-13 -3.033226e-13 -1.072901e-11 16 17 18 19 20 -1.017147e-12 -1.549925e-12 -3.982031e-13 -2.531827e-12 -5.855712e-13 21 22 23 24 25 -1.457316e-12 -1.565009e-12 -4.071462e-13 8.216688e-14 7.127185e-13 26 27 28 29 30 -2.640893e-13 -8.466594e-12 -9.343540e-13 4.020905e-13 4.419167e-13 31 32 33 34 35 -1.712887e-12 -1.019012e-13 7.814730e-13 7.046905e-13 4.426948e-13 36 37 38 39 40 7.763677e-13 8.833980e-13 1.048774e-12 -5.567535e-12 1.618611e-12 41 42 43 44 45 2.441230e-12 1.477590e-12 1.386895e-13 1.580823e-12 1.916845e-12 46 47 48 49 50 1.204188e-12 1.013284e-12 -3.665830e-13 6.093722e-13 -2.857702e-13 51 52 53 54 55 -7.880863e-12 -5.016976e-13 -2.341411e-13 2.113893e-13 6.253208e-13 56 57 58 59 60 -9.468865e-13 4.616693e-13 2.578772e-13 1.277897e-12 -2.621163e-13 61 62 63 64 65 1.825821e-12 1.464428e-12 -6.212706e-12 2.349018e-13 4.418327e-13 66 67 68 69 70 4.369118e-13 1.257700e-12 5.755019e-13 -2.194504e-13 2.210532e-13 71 72 73 74 75 8.695660e-13 1.445253e-12 2.094509e-12 1.334913e-12 -7.936224e-12 76 77 78 79 80 2.187357e-12 1.628940e-12 1.128822e-12 1.646084e-12 1.784804e-12 81 82 83 84 85 8.203668e-13 2.078343e-13 -5.101454e-13 2.301176e-13 1.385747e-12 86 87 88 89 90 1.630324e-12 -7.625378e-12 1.812860e-12 5.391682e-14 -7.216607e-13 91 92 93 94 95 6.426593e-13 8.841329e-13 1.039425e-12 1.197946e-12 -2.236319e-13 > postscript(file="/var/www/html/rcomp/tmp/6pucb1258645334.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 95 Frequency = 1 lag(myerror, k = 1) myerror 0 -6.970760e-12 NA 1 -4.625257e-12 -6.970760e-12 2 5.441831e-11 -4.625257e-12 3 -3.400531e-12 5.441831e-11 4 -3.183944e-12 -3.400531e-12 5 -2.576766e-12 -3.183944e-12 6 -6.573865e-14 -2.576766e-12 7 -3.190903e-12 -6.573865e-14 8 -3.343013e-12 -3.190903e-12 9 -2.228580e-12 -3.343013e-12 10 -2.462519e-12 -2.228580e-12 11 -1.905206e-12 -2.462519e-12 12 -5.408049e-13 -1.905206e-12 13 -3.033226e-13 -5.408049e-13 14 -1.072901e-11 -3.033226e-13 15 -1.017147e-12 -1.072901e-11 16 -1.549925e-12 -1.017147e-12 17 -3.982031e-13 -1.549925e-12 18 -2.531827e-12 -3.982031e-13 19 -5.855712e-13 -2.531827e-12 20 -1.457316e-12 -5.855712e-13 21 -1.565009e-12 -1.457316e-12 22 -4.071462e-13 -1.565009e-12 23 8.216688e-14 -4.071462e-13 24 7.127185e-13 8.216688e-14 25 -2.640893e-13 7.127185e-13 26 -8.466594e-12 -2.640893e-13 27 -9.343540e-13 -8.466594e-12 28 4.020905e-13 -9.343540e-13 29 4.419167e-13 4.020905e-13 30 -1.712887e-12 4.419167e-13 31 -1.019012e-13 -1.712887e-12 32 7.814730e-13 -1.019012e-13 33 7.046905e-13 7.814730e-13 34 4.426948e-13 7.046905e-13 35 7.763677e-13 4.426948e-13 36 8.833980e-13 7.763677e-13 37 1.048774e-12 8.833980e-13 38 -5.567535e-12 1.048774e-12 39 1.618611e-12 -5.567535e-12 40 2.441230e-12 1.618611e-12 41 1.477590e-12 2.441230e-12 42 1.386895e-13 1.477590e-12 43 1.580823e-12 1.386895e-13 44 1.916845e-12 1.580823e-12 45 1.204188e-12 1.916845e-12 46 1.013284e-12 1.204188e-12 47 -3.665830e-13 1.013284e-12 48 6.093722e-13 -3.665830e-13 49 -2.857702e-13 6.093722e-13 50 -7.880863e-12 -2.857702e-13 51 -5.016976e-13 -7.880863e-12 52 -2.341411e-13 -5.016976e-13 53 2.113893e-13 -2.341411e-13 54 6.253208e-13 2.113893e-13 55 -9.468865e-13 6.253208e-13 56 4.616693e-13 -9.468865e-13 57 2.578772e-13 4.616693e-13 58 1.277897e-12 2.578772e-13 59 -2.621163e-13 1.277897e-12 60 1.825821e-12 -2.621163e-13 61 1.464428e-12 1.825821e-12 62 -6.212706e-12 1.464428e-12 63 2.349018e-13 -6.212706e-12 64 4.418327e-13 2.349018e-13 65 4.369118e-13 4.418327e-13 66 1.257700e-12 4.369118e-13 67 5.755019e-13 1.257700e-12 68 -2.194504e-13 5.755019e-13 69 2.210532e-13 -2.194504e-13 70 8.695660e-13 2.210532e-13 71 1.445253e-12 8.695660e-13 72 2.094509e-12 1.445253e-12 73 1.334913e-12 2.094509e-12 74 -7.936224e-12 1.334913e-12 75 2.187357e-12 -7.936224e-12 76 1.628940e-12 2.187357e-12 77 1.128822e-12 1.628940e-12 78 1.646084e-12 1.128822e-12 79 1.784804e-12 1.646084e-12 80 8.203668e-13 1.784804e-12 81 2.078343e-13 8.203668e-13 82 -5.101454e-13 2.078343e-13 83 2.301176e-13 -5.101454e-13 84 1.385747e-12 2.301176e-13 85 1.630324e-12 1.385747e-12 86 -7.625378e-12 1.630324e-12 87 1.812860e-12 -7.625378e-12 88 5.391682e-14 1.812860e-12 89 -7.216607e-13 5.391682e-14 90 6.426593e-13 -7.216607e-13 91 8.841329e-13 6.426593e-13 92 1.039425e-12 8.841329e-13 93 1.197946e-12 1.039425e-12 94 -2.236319e-13 1.197946e-12 95 NA -2.236319e-13 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -4.625257e-12 -6.970760e-12 [2,] 5.441831e-11 -4.625257e-12 [3,] -3.400531e-12 5.441831e-11 [4,] -3.183944e-12 -3.400531e-12 [5,] -2.576766e-12 -3.183944e-12 [6,] -6.573865e-14 -2.576766e-12 [7,] -3.190903e-12 -6.573865e-14 [8,] -3.343013e-12 -3.190903e-12 [9,] -2.228580e-12 -3.343013e-12 [10,] -2.462519e-12 -2.228580e-12 [11,] -1.905206e-12 -2.462519e-12 [12,] -5.408049e-13 -1.905206e-12 [13,] -3.033226e-13 -5.408049e-13 [14,] -1.072901e-11 -3.033226e-13 [15,] -1.017147e-12 -1.072901e-11 [16,] -1.549925e-12 -1.017147e-12 [17,] -3.982031e-13 -1.549925e-12 [18,] -2.531827e-12 -3.982031e-13 [19,] -5.855712e-13 -2.531827e-12 [20,] -1.457316e-12 -5.855712e-13 [21,] -1.565009e-12 -1.457316e-12 [22,] -4.071462e-13 -1.565009e-12 [23,] 8.216688e-14 -4.071462e-13 [24,] 7.127185e-13 8.216688e-14 [25,] -2.640893e-13 7.127185e-13 [26,] -8.466594e-12 -2.640893e-13 [27,] -9.343540e-13 -8.466594e-12 [28,] 4.020905e-13 -9.343540e-13 [29,] 4.419167e-13 4.020905e-13 [30,] -1.712887e-12 4.419167e-13 [31,] -1.019012e-13 -1.712887e-12 [32,] 7.814730e-13 -1.019012e-13 [33,] 7.046905e-13 7.814730e-13 [34,] 4.426948e-13 7.046905e-13 [35,] 7.763677e-13 4.426948e-13 [36,] 8.833980e-13 7.763677e-13 [37,] 1.048774e-12 8.833980e-13 [38,] -5.567535e-12 1.048774e-12 [39,] 1.618611e-12 -5.567535e-12 [40,] 2.441230e-12 1.618611e-12 [41,] 1.477590e-12 2.441230e-12 [42,] 1.386895e-13 1.477590e-12 [43,] 1.580823e-12 1.386895e-13 [44,] 1.916845e-12 1.580823e-12 [45,] 1.204188e-12 1.916845e-12 [46,] 1.013284e-12 1.204188e-12 [47,] -3.665830e-13 1.013284e-12 [48,] 6.093722e-13 -3.665830e-13 [49,] -2.857702e-13 6.093722e-13 [50,] -7.880863e-12 -2.857702e-13 [51,] -5.016976e-13 -7.880863e-12 [52,] -2.341411e-13 -5.016976e-13 [53,] 2.113893e-13 -2.341411e-13 [54,] 6.253208e-13 2.113893e-13 [55,] -9.468865e-13 6.253208e-13 [56,] 4.616693e-13 -9.468865e-13 [57,] 2.578772e-13 4.616693e-13 [58,] 1.277897e-12 2.578772e-13 [59,] -2.621163e-13 1.277897e-12 [60,] 1.825821e-12 -2.621163e-13 [61,] 1.464428e-12 1.825821e-12 [62,] -6.212706e-12 1.464428e-12 [63,] 2.349018e-13 -6.212706e-12 [64,] 4.418327e-13 2.349018e-13 [65,] 4.369118e-13 4.418327e-13 [66,] 1.257700e-12 4.369118e-13 [67,] 5.755019e-13 1.257700e-12 [68,] -2.194504e-13 5.755019e-13 [69,] 2.210532e-13 -2.194504e-13 [70,] 8.695660e-13 2.210532e-13 [71,] 1.445253e-12 8.695660e-13 [72,] 2.094509e-12 1.445253e-12 [73,] 1.334913e-12 2.094509e-12 [74,] -7.936224e-12 1.334913e-12 [75,] 2.187357e-12 -7.936224e-12 [76,] 1.628940e-12 2.187357e-12 [77,] 1.128822e-12 1.628940e-12 [78,] 1.646084e-12 1.128822e-12 [79,] 1.784804e-12 1.646084e-12 [80,] 8.203668e-13 1.784804e-12 [81,] 2.078343e-13 8.203668e-13 [82,] -5.101454e-13 2.078343e-13 [83,] 2.301176e-13 -5.101454e-13 [84,] 1.385747e-12 2.301176e-13 [85,] 1.630324e-12 1.385747e-12 [86,] -7.625378e-12 1.630324e-12 [87,] 1.812860e-12 -7.625378e-12 [88,] 5.391682e-14 1.812860e-12 [89,] -7.216607e-13 5.391682e-14 [90,] 6.426593e-13 -7.216607e-13 [91,] 8.841329e-13 6.426593e-13 [92,] 1.039425e-12 8.841329e-13 [93,] 1.197946e-12 1.039425e-12 [94,] -2.236319e-13 1.197946e-12 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -4.625257e-12 -6.970760e-12 2 5.441831e-11 -4.625257e-12 3 -3.400531e-12 5.441831e-11 4 -3.183944e-12 -3.400531e-12 5 -2.576766e-12 -3.183944e-12 6 -6.573865e-14 -2.576766e-12 7 -3.190903e-12 -6.573865e-14 8 -3.343013e-12 -3.190903e-12 9 -2.228580e-12 -3.343013e-12 10 -2.462519e-12 -2.228580e-12 11 -1.905206e-12 -2.462519e-12 12 -5.408049e-13 -1.905206e-12 13 -3.033226e-13 -5.408049e-13 14 -1.072901e-11 -3.033226e-13 15 -1.017147e-12 -1.072901e-11 16 -1.549925e-12 -1.017147e-12 17 -3.982031e-13 -1.549925e-12 18 -2.531827e-12 -3.982031e-13 19 -5.855712e-13 -2.531827e-12 20 -1.457316e-12 -5.855712e-13 21 -1.565009e-12 -1.457316e-12 22 -4.071462e-13 -1.565009e-12 23 8.216688e-14 -4.071462e-13 24 7.127185e-13 8.216688e-14 25 -2.640893e-13 7.127185e-13 26 -8.466594e-12 -2.640893e-13 27 -9.343540e-13 -8.466594e-12 28 4.020905e-13 -9.343540e-13 29 4.419167e-13 4.020905e-13 30 -1.712887e-12 4.419167e-13 31 -1.019012e-13 -1.712887e-12 32 7.814730e-13 -1.019012e-13 33 7.046905e-13 7.814730e-13 34 4.426948e-13 7.046905e-13 35 7.763677e-13 4.426948e-13 36 8.833980e-13 7.763677e-13 37 1.048774e-12 8.833980e-13 38 -5.567535e-12 1.048774e-12 39 1.618611e-12 -5.567535e-12 40 2.441230e-12 1.618611e-12 41 1.477590e-12 2.441230e-12 42 1.386895e-13 1.477590e-12 43 1.580823e-12 1.386895e-13 44 1.916845e-12 1.580823e-12 45 1.204188e-12 1.916845e-12 46 1.013284e-12 1.204188e-12 47 -3.665830e-13 1.013284e-12 48 6.093722e-13 -3.665830e-13 49 -2.857702e-13 6.093722e-13 50 -7.880863e-12 -2.857702e-13 51 -5.016976e-13 -7.880863e-12 52 -2.341411e-13 -5.016976e-13 53 2.113893e-13 -2.341411e-13 54 6.253208e-13 2.113893e-13 55 -9.468865e-13 6.253208e-13 56 4.616693e-13 -9.468865e-13 57 2.578772e-13 4.616693e-13 58 1.277897e-12 2.578772e-13 59 -2.621163e-13 1.277897e-12 60 1.825821e-12 -2.621163e-13 61 1.464428e-12 1.825821e-12 62 -6.212706e-12 1.464428e-12 63 2.349018e-13 -6.212706e-12 64 4.418327e-13 2.349018e-13 65 4.369118e-13 4.418327e-13 66 1.257700e-12 4.369118e-13 67 5.755019e-13 1.257700e-12 68 -2.194504e-13 5.755019e-13 69 2.210532e-13 -2.194504e-13 70 8.695660e-13 2.210532e-13 71 1.445253e-12 8.695660e-13 72 2.094509e-12 1.445253e-12 73 1.334913e-12 2.094509e-12 74 -7.936224e-12 1.334913e-12 75 2.187357e-12 -7.936224e-12 76 1.628940e-12 2.187357e-12 77 1.128822e-12 1.628940e-12 78 1.646084e-12 1.128822e-12 79 1.784804e-12 1.646084e-12 80 8.203668e-13 1.784804e-12 81 2.078343e-13 8.203668e-13 82 -5.101454e-13 2.078343e-13 83 2.301176e-13 -5.101454e-13 84 1.385747e-12 2.301176e-13 85 1.630324e-12 1.385747e-12 86 -7.625378e-12 1.630324e-12 87 1.812860e-12 -7.625378e-12 88 5.391682e-14 1.812860e-12 89 -7.216607e-13 5.391682e-14 90 6.426593e-13 -7.216607e-13 91 8.841329e-13 6.426593e-13 92 1.039425e-12 8.841329e-13 93 1.197946e-12 1.039425e-12 94 -2.236319e-13 1.197946e-12 > 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/7wcr61258645334.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8isik1258645334.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9sw251258645334.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/105drq1258645334.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/116vuf1258645334.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/122ye11258645334.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/13fc7q1258645334.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/14rl8a1258645334.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/15j9rj1258645334.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/16v3bz1258645334.tab") + } > > system("convert tmp/1p0k91258645334.ps tmp/1p0k91258645334.png") > system("convert tmp/2qhxc1258645334.ps tmp/2qhxc1258645334.png") > system("convert tmp/3ji0c1258645334.ps tmp/3ji0c1258645334.png") > system("convert tmp/4ucep1258645334.ps tmp/4ucep1258645334.png") > system("convert tmp/516b71258645334.ps tmp/516b71258645334.png") > system("convert tmp/6pucb1258645334.ps tmp/6pucb1258645334.png") > system("convert tmp/7wcr61258645334.ps tmp/7wcr61258645334.png") > system("convert tmp/8isik1258645334.ps tmp/8isik1258645334.png") > system("convert tmp/9sw251258645334.ps tmp/9sw251258645334.png") > system("convert tmp/105drq1258645334.ps tmp/105drq1258645334.png") > > > proc.time() user system elapsed 2.829 1.693 4.126