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Type 'q()' to quit R. > x <- array(list(13363 + ,0 + ,12530 + ,0 + ,11420 + ,0 + ,10948 + ,0 + ,10173 + ,0 + ,10602 + ,0 + ,16094 + ,0 + ,19631 + ,0 + ,17140 + ,0 + ,14345 + ,0 + ,12632 + ,0 + ,12894 + ,0 + ,11808 + ,0 + ,10673 + ,0 + ,9939 + ,0 + ,9890 + ,0 + ,9283 + ,0 + ,10131 + ,0 + ,15864 + ,0 + ,19283 + ,0 + ,16203 + ,0 + ,13919 + ,0 + ,11937 + ,0 + ,11795 + ,0 + ,11268 + ,0 + ,10522 + ,0 + ,9929 + ,0 + ,9725 + ,0 + ,9372 + ,0 + ,10068 + ,0 + ,16230 + ,0 + ,19115 + ,0 + ,18351 + ,0 + ,16265 + ,0 + ,14103 + ,0 + ,14115 + ,0 + ,13327 + ,0 + ,12618 + ,0 + ,12129 + ,0 + ,11775 + ,0 + ,11493 + ,0 + ,12470 + ,0 + ,20792 + ,0 + ,22337 + ,0 + ,21325 + ,0 + ,18581 + ,0 + ,16475 + ,0 + ,16581 + ,0 + ,15745 + ,0 + ,14453 + ,0 + ,13712 + ,0 + ,13766 + ,0 + ,13336 + ,0 + ,15346 + ,0 + ,24446 + ,0 + ,26178 + ,0 + ,24628 + ,0 + ,21282 + ,0 + ,18850 + ,0 + ,18822 + ,0 + ,18060 + ,0 + ,17536 + ,0 + ,16417 + ,0 + ,15842 + ,0 + ,15188 + ,0 + ,16905 + ,0 + ,25430 + ,0 + ,27962 + ,0 + ,26607 + ,0 + ,23364 + ,0 + ,20827 + ,0 + ,20506 + ,0 + ,19181 + ,0 + ,18016 + ,0 + ,17354 + ,0 + ,16256 + ,0 + ,15770 + ,0 + ,17538 + ,0 + ,26899 + ,0 + ,28915 + ,0 + ,25247 + ,0 + ,22856 + ,0 + ,19980 + ,0 + ,19856 + ,0 + ,16994 + ,0 + ,16839 + ,0 + ,15618 + ,0 + ,15883 + ,0 + ,15513 + ,0 + ,17106 + ,0 + ,25272 + ,0 + ,26731 + ,0 + ,22891 + ,0 + ,19583 + ,0 + ,16939 + ,0 + ,16757 + ,0 + ,15435 + ,0 + ,14786 + ,0 + ,13680 + ,0 + ,13208 + ,0 + ,12707 + ,0 + ,14277 + ,0 + ,22436 + ,1 + ,23229 + ,1 + ,18241 + ,1 + ,16145 + ,1 + ,13994 + ,1 + ,14780 + ,1 + ,13100 + ,1 + ,12329 + ,1 + ,12463 + ,1 + ,11532 + ,1 + ,10784 + ,1 + ,13106 + ,1 + ,19491 + ,1 + ,20418 + ,1 + ,16094 + ,1 + ,14491 + ,1 + ,13067 + ,1) + ,dim=c(2 + ,119) + ,dimnames=list(c('NWWZPB' + ,'Dummy') + ,1:119)) > y <- array(NA,dim=c(2,119),dimnames=list(c('NWWZPB','Dummy'),1:119)) > 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 NWWZPB Dummy M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 t 1 13363 0 1 0 0 0 0 0 0 0 0 0 0 1 2 12530 0 0 1 0 0 0 0 0 0 0 0 0 2 3 11420 0 0 0 1 0 0 0 0 0 0 0 0 3 4 10948 0 0 0 0 1 0 0 0 0 0 0 0 4 5 10173 0 0 0 0 0 1 0 0 0 0 0 0 5 6 10602 0 0 0 0 0 0 1 0 0 0 0 0 6 7 16094 0 0 0 0 0 0 0 1 0 0 0 0 7 8 19631 0 0 0 0 0 0 0 0 1 0 0 0 8 9 17140 0 0 0 0 0 0 0 0 0 1 0 0 9 10 14345 0 0 0 0 0 0 0 0 0 0 1 0 10 11 12632 0 0 0 0 0 0 0 0 0 0 0 1 11 12 12894 0 0 0 0 0 0 0 0 0 0 0 0 12 13 11808 0 1 0 0 0 0 0 0 0 0 0 0 13 14 10673 0 0 1 0 0 0 0 0 0 0 0 0 14 15 9939 0 0 0 1 0 0 0 0 0 0 0 0 15 16 9890 0 0 0 0 1 0 0 0 0 0 0 0 16 17 9283 0 0 0 0 0 1 0 0 0 0 0 0 17 18 10131 0 0 0 0 0 0 1 0 0 0 0 0 18 19 15864 0 0 0 0 0 0 0 1 0 0 0 0 19 20 19283 0 0 0 0 0 0 0 0 1 0 0 0 20 21 16203 0 0 0 0 0 0 0 0 0 1 0 0 21 22 13919 0 0 0 0 0 0 0 0 0 0 1 0 22 23 11937 0 0 0 0 0 0 0 0 0 0 0 1 23 24 11795 0 0 0 0 0 0 0 0 0 0 0 0 24 25 11268 0 1 0 0 0 0 0 0 0 0 0 0 25 26 10522 0 0 1 0 0 0 0 0 0 0 0 0 26 27 9929 0 0 0 1 0 0 0 0 0 0 0 0 27 28 9725 0 0 0 0 1 0 0 0 0 0 0 0 28 29 9372 0 0 0 0 0 1 0 0 0 0 0 0 29 30 10068 0 0 0 0 0 0 1 0 0 0 0 0 30 31 16230 0 0 0 0 0 0 0 1 0 0 0 0 31 32 19115 0 0 0 0 0 0 0 0 1 0 0 0 32 33 18351 0 0 0 0 0 0 0 0 0 1 0 0 33 34 16265 0 0 0 0 0 0 0 0 0 0 1 0 34 35 14103 0 0 0 0 0 0 0 0 0 0 0 1 35 36 14115 0 0 0 0 0 0 0 0 0 0 0 0 36 37 13327 0 1 0 0 0 0 0 0 0 0 0 0 37 38 12618 0 0 1 0 0 0 0 0 0 0 0 0 38 39 12129 0 0 0 1 0 0 0 0 0 0 0 0 39 40 11775 0 0 0 0 1 0 0 0 0 0 0 0 40 41 11493 0 0 0 0 0 1 0 0 0 0 0 0 41 42 12470 0 0 0 0 0 0 1 0 0 0 0 0 42 43 20792 0 0 0 0 0 0 0 1 0 0 0 0 43 44 22337 0 0 0 0 0 0 0 0 1 0 0 0 44 45 21325 0 0 0 0 0 0 0 0 0 1 0 0 45 46 18581 0 0 0 0 0 0 0 0 0 0 1 0 46 47 16475 0 0 0 0 0 0 0 0 0 0 0 1 47 48 16581 0 0 0 0 0 0 0 0 0 0 0 0 48 49 15745 0 1 0 0 0 0 0 0 0 0 0 0 49 50 14453 0 0 1 0 0 0 0 0 0 0 0 0 50 51 13712 0 0 0 1 0 0 0 0 0 0 0 0 51 52 13766 0 0 0 0 1 0 0 0 0 0 0 0 52 53 13336 0 0 0 0 0 1 0 0 0 0 0 0 53 54 15346 0 0 0 0 0 0 1 0 0 0 0 0 54 55 24446 0 0 0 0 0 0 0 1 0 0 0 0 55 56 26178 0 0 0 0 0 0 0 0 1 0 0 0 56 57 24628 0 0 0 0 0 0 0 0 0 1 0 0 57 58 21282 0 0 0 0 0 0 0 0 0 0 1 0 58 59 18850 0 0 0 0 0 0 0 0 0 0 0 1 59 60 18822 0 0 0 0 0 0 0 0 0 0 0 0 60 61 18060 0 1 0 0 0 0 0 0 0 0 0 0 61 62 17536 0 0 1 0 0 0 0 0 0 0 0 0 62 63 16417 0 0 0 1 0 0 0 0 0 0 0 0 63 64 15842 0 0 0 0 1 0 0 0 0 0 0 0 64 65 15188 0 0 0 0 0 1 0 0 0 0 0 0 65 66 16905 0 0 0 0 0 0 1 0 0 0 0 0 66 67 25430 0 0 0 0 0 0 0 1 0 0 0 0 67 68 27962 0 0 0 0 0 0 0 0 1 0 0 0 68 69 26607 0 0 0 0 0 0 0 0 0 1 0 0 69 70 23364 0 0 0 0 0 0 0 0 0 0 1 0 70 71 20827 0 0 0 0 0 0 0 0 0 0 0 1 71 72 20506 0 0 0 0 0 0 0 0 0 0 0 0 72 73 19181 0 1 0 0 0 0 0 0 0 0 0 0 73 74 18016 0 0 1 0 0 0 0 0 0 0 0 0 74 75 17354 0 0 0 1 0 0 0 0 0 0 0 0 75 76 16256 0 0 0 0 1 0 0 0 0 0 0 0 76 77 15770 0 0 0 0 0 1 0 0 0 0 0 0 77 78 17538 0 0 0 0 0 0 1 0 0 0 0 0 78 79 26899 0 0 0 0 0 0 0 1 0 0 0 0 79 80 28915 0 0 0 0 0 0 0 0 1 0 0 0 80 81 25247 0 0 0 0 0 0 0 0 0 1 0 0 81 82 22856 0 0 0 0 0 0 0 0 0 0 1 0 82 83 19980 0 0 0 0 0 0 0 0 0 0 0 1 83 84 19856 0 0 0 0 0 0 0 0 0 0 0 0 84 85 16994 0 1 0 0 0 0 0 0 0 0 0 0 85 86 16839 0 0 1 0 0 0 0 0 0 0 0 0 86 87 15618 0 0 0 1 0 0 0 0 0 0 0 0 87 88 15883 0 0 0 0 1 0 0 0 0 0 0 0 88 89 15513 0 0 0 0 0 1 0 0 0 0 0 0 89 90 17106 0 0 0 0 0 0 1 0 0 0 0 0 90 91 25272 0 0 0 0 0 0 0 1 0 0 0 0 91 92 26731 0 0 0 0 0 0 0 0 1 0 0 0 92 93 22891 0 0 0 0 0 0 0 0 0 1 0 0 93 94 19583 0 0 0 0 0 0 0 0 0 0 1 0 94 95 16939 0 0 0 0 0 0 0 0 0 0 0 1 95 96 16757 0 0 0 0 0 0 0 0 0 0 0 0 96 97 15435 0 1 0 0 0 0 0 0 0 0 0 0 97 98 14786 0 0 1 0 0 0 0 0 0 0 0 0 98 99 13680 0 0 0 1 0 0 0 0 0 0 0 0 99 100 13208 0 0 0 0 1 0 0 0 0 0 0 0 100 101 12707 0 0 0 0 0 1 0 0 0 0 0 0 101 102 14277 0 0 0 0 0 0 1 0 0 0 0 0 102 103 22436 1 0 0 0 0 0 0 1 0 0 0 0 103 104 23229 1 0 0 0 0 0 0 0 1 0 0 0 104 105 18241 1 0 0 0 0 0 0 0 0 1 0 0 105 106 16145 1 0 0 0 0 0 0 0 0 0 1 0 106 107 13994 1 0 0 0 0 0 0 0 0 0 0 1 107 108 14780 1 0 0 0 0 0 0 0 0 0 0 0 108 109 13100 1 1 0 0 0 0 0 0 0 0 0 0 109 110 12329 1 0 1 0 0 0 0 0 0 0 0 0 110 111 12463 1 0 0 1 0 0 0 0 0 0 0 0 111 112 11532 1 0 0 0 1 0 0 0 0 0 0 0 112 113 10784 1 0 0 0 0 1 0 0 0 0 0 0 113 114 13106 1 0 0 0 0 0 1 0 0 0 0 0 114 115 19491 1 0 0 0 0 0 0 1 0 0 0 0 115 116 20418 1 0 0 0 0 0 0 0 1 0 0 0 116 117 16094 1 0 0 0 0 0 0 0 0 1 0 0 117 118 14491 1 0 0 0 0 0 0 0 0 0 1 0 118 119 13067 1 0 0 0 0 0 0 0 0 0 0 1 119 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Dummy M1 M2 M3 M4 12013.67 -7096.89 -1067.35 -1948.73 -2796.31 -3263.39 M5 M6 M7 M8 M9 M10 -3867.47 -2557.95 5608.75 7609.77 4819.09 2146.01 M11 t -140.17 83.48 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -3980.34 -1121.69 -63.02 1633.89 4014.04 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 12013.675 756.171 15.888 < 2e-16 *** Dummy -7096.887 660.983 -10.737 < 2e-16 *** M1 -1067.349 915.549 -1.166 0.246336 M2 -1948.730 915.361 -2.129 0.035599 * M3 -2796.311 915.223 -3.055 0.002850 ** M4 -3263.392 915.133 -3.566 0.000547 *** M5 -3867.473 915.092 -4.226 5.08e-05 *** M6 -2557.954 915.100 -2.795 0.006167 ** M7 5608.753 916.720 6.118 1.65e-08 *** M8 7609.772 916.534 8.303 3.78e-13 *** M9 4819.091 916.397 5.259 7.69e-07 *** M10 2146.010 916.309 2.342 0.021067 * M11 -140.171 916.270 -0.153 0.878707 t 83.481 6.694 12.471 < 2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 1992 on 105 degrees of freedom Multiple R-squared: 0.8382, Adjusted R-squared: 0.8182 F-statistic: 41.84 on 13 and 105 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,] 4.860968e-03 9.721937e-03 9.951390e-01 [2,] 2.564137e-03 5.128274e-03 9.974359e-01 [3,] 1.514814e-03 3.029627e-03 9.984852e-01 [4,] 5.338316e-04 1.067663e-03 9.994662e-01 [5,] 1.122537e-04 2.245073e-04 9.998877e-01 [6,] 3.287641e-05 6.575283e-05 9.999671e-01 [7,] 6.955963e-06 1.391193e-05 9.999930e-01 [8,] 1.448437e-06 2.896875e-06 9.999986e-01 [9,] 2.665989e-07 5.331978e-07 9.999997e-01 [10,] 5.658456e-08 1.131691e-07 9.999999e-01 [11,] 2.029467e-08 4.058934e-08 1.000000e+00 [12,] 6.898754e-09 1.379751e-08 1.000000e+00 [13,] 4.894903e-09 9.789806e-09 1.000000e+00 [14,] 3.333091e-09 6.666182e-09 1.000000e+00 [15,] 1.915462e-08 3.830924e-08 1.000000e+00 [16,] 1.371445e-08 2.742891e-08 1.000000e+00 [17,] 1.997607e-06 3.995214e-06 9.999980e-01 [18,] 4.780094e-05 9.560189e-05 9.999522e-01 [19,] 1.586374e-04 3.172748e-04 9.998414e-01 [20,] 3.453148e-04 6.906295e-04 9.996547e-01 [21,] 3.599498e-04 7.198997e-04 9.996401e-01 [22,] 3.963812e-04 7.927624e-04 9.996036e-01 [23,] 4.921626e-04 9.843252e-04 9.995078e-01 [24,] 5.057753e-04 1.011551e-03 9.994942e-01 [25,] 5.843696e-04 1.168739e-03 9.994156e-01 [26,] 9.866697e-04 1.973339e-03 9.990133e-01 [27,] 2.005696e-02 4.011392e-02 9.799430e-01 [28,] 4.761006e-02 9.522012e-02 9.523899e-01 [29,] 9.932216e-02 1.986443e-01 9.006778e-01 [30,] 1.513861e-01 3.027723e-01 8.486139e-01 [31,] 1.999966e-01 3.999931e-01 8.000034e-01 [32,] 2.635788e-01 5.271577e-01 7.364212e-01 [33,] 2.767026e-01 5.534052e-01 7.232974e-01 [34,] 3.136123e-01 6.272245e-01 6.863877e-01 [35,] 3.687540e-01 7.375080e-01 6.312460e-01 [36,] 4.170662e-01 8.341325e-01 5.829338e-01 [37,] 4.818688e-01 9.637376e-01 5.181312e-01 [38,] 6.165816e-01 7.668369e-01 3.834184e-01 [39,] 8.844762e-01 2.310476e-01 1.155238e-01 [40,] 9.558031e-01 8.839384e-02 4.419692e-02 [41,] 9.717177e-01 5.656455e-02 2.828228e-02 [42,] 9.797119e-01 4.057616e-02 2.028808e-02 [43,] 9.853033e-01 2.939344e-02 1.469672e-02 [44,] 9.908311e-01 1.833781e-02 9.168903e-03 [45,] 9.903229e-01 1.935424e-02 9.677118e-03 [46,] 9.901469e-01 1.970611e-02 9.853054e-03 [47,] 9.918005e-01 1.639898e-02 8.199489e-03 [48,] 9.939823e-01 1.203544e-02 6.017720e-03 [49,] 9.969137e-01 6.172591e-03 3.086295e-03 [50,] 9.992499e-01 1.500219e-03 7.501094e-04 [51,] 9.999444e-01 1.111384e-04 5.556921e-05 [52,] 9.999842e-01 3.161799e-05 1.580900e-05 [53,] 9.999857e-01 2.867997e-05 1.433999e-05 [54,] 9.999775e-01 4.509461e-05 2.254730e-05 [55,] 9.999615e-01 7.696847e-05 3.848424e-05 [56,] 9.999402e-01 1.196241e-04 5.981203e-05 [57,] 9.998828e-01 2.344872e-04 1.172436e-04 [58,] 9.998209e-01 3.582109e-04 1.791055e-04 [59,] 9.997286e-01 5.428419e-04 2.714209e-04 [60,] 9.998251e-01 3.498040e-04 1.749020e-04 [61,] 9.999208e-01 1.583792e-04 7.918959e-05 [62,] 9.999869e-01 2.627293e-05 1.313646e-05 [63,] 9.999801e-01 3.988100e-05 1.994050e-05 [64,] 9.999607e-01 7.863191e-05 3.931595e-05 [65,] 9.999604e-01 7.919365e-05 3.959683e-05 [66,] 9.999655e-01 6.894586e-05 3.447293e-05 [67,] 9.999388e-01 1.223541e-04 6.117707e-05 [68,] 9.998920e-01 2.160601e-04 1.080301e-04 [69,] 9.999048e-01 1.904201e-04 9.521004e-05 [70,] 9.998453e-01 3.093029e-04 1.546514e-04 [71,] 9.998736e-01 2.528630e-04 1.264315e-04 [72,] 9.997570e-01 4.860376e-04 2.430188e-04 [73,] 9.995050e-01 9.899800e-04 4.949900e-04 [74,] 9.990272e-01 1.945544e-03 9.727720e-04 [75,] 9.981510e-01 3.698034e-03 1.849017e-03 [76,] 9.982253e-01 3.549476e-03 1.774738e-03 [77,] 9.999379e-01 1.242570e-04 6.212849e-05 [78,] 9.999742e-01 5.166654e-05 2.583327e-05 [79,] 9.999509e-01 9.823159e-05 4.911579e-05 [80,] 9.998649e-01 2.702661e-04 1.351331e-04 [81,] 9.997246e-01 5.508920e-04 2.754460e-04 [82,] 9.995668e-01 8.663344e-04 4.331672e-04 [83,] 9.986446e-01 2.710724e-03 1.355362e-03 [84,] 9.953288e-01 9.342441e-03 4.671220e-03 [85,] 9.866275e-01 2.674506e-02 1.337253e-02 [86,] 9.534849e-01 9.303016e-02 4.651508e-02 > postscript(file="/var/www/html/freestat/rcomp/tmp/197y11228917225.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/29l4k1228917225.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/freestat/rcomp/tmp/3099b1228917225.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/4vb391228917225.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/5ug3r1228917225.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 = 119 Frequency = 1 1 2 3 4 5 6 2333.19252 2298.09252 1952.19252 1863.79252 1609.39252 645.39252 7 8 9 10 11 12 -2112.79615 -660.29615 -444.09615 -649.49615 -159.79615 -121.44858 13 14 15 16 17 18 -223.58108 -560.68108 -530.58108 -195.98108 -282.38108 -827.38108 19 20 21 22 23 24 -3344.56975 -2010.06975 -2382.86975 -2077.26975 -1856.56975 -2222.22217 25 26 27 28 29 30 -1765.35468 -1713.45468 -1542.35468 -1362.75468 -1195.15468 -1892.15468 31 32 33 34 35 36 -3980.34335 -3179.84335 -1236.64335 -733.04335 -692.34335 -903.99577 37 38 39 40 41 42 -708.12827 -619.22827 -344.12827 -314.52827 -75.92827 -491.92827 43 44 45 46 47 48 -420.11694 -959.61694 735.58306 581.18306 677.88306 560.23063 49 50 51 52 53 54 708.09813 213.99813 237.09813 674.69813 765.29813 1382.29813 55 56 57 58 59 60 2232.10946 1879.60946 3036.80946 2280.40946 2051.10946 1799.45703 61 62 63 64 65 66 2021.32453 2295.22453 1940.32453 1748.92453 1615.52453 1939.52453 67 68 69 70 71 72 2214.33586 2661.83586 4014.03586 3360.63586 3026.33586 2481.68344 73 74 75 76 77 78 2140.55094 1773.45094 1875.55094 1161.15094 1195.75094 1570.75094 79 80 81 82 83 84 2681.56227 2613.06227 1652.26227 1850.86227 1177.56227 829.90984 85 86 87 88 89 90 -1048.22266 -405.32266 -862.22266 -213.62266 -63.02266 136.97734 91 92 93 94 95 96 52.78867 -572.71133 -1705.51133 -2423.91133 -2865.21133 -3270.86376 97 98 99 100 101 102 -3608.99626 -3460.09626 -3801.99626 -3890.39626 -3870.79626 -3693.79626 103 104 105 106 107 108 3311.90176 2020.40176 -260.39824 233.20176 284.90176 847.24934 109 110 111 112 113 114 151.11684 178.01684 1076.11684 528.71684 301.31684 1230.31684 115 116 117 118 119 -634.87183 -1792.37183 -3409.17183 -2422.57183 -1643.87183 > postscript(file="/var/www/html/freestat/rcomp/tmp/6y1ym1228917225.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 = 119 Frequency = 1 lag(myerror, k = 1) myerror 0 2333.19252 NA 1 2298.09252 2333.19252 2 1952.19252 2298.09252 3 1863.79252 1952.19252 4 1609.39252 1863.79252 5 645.39252 1609.39252 6 -2112.79615 645.39252 7 -660.29615 -2112.79615 8 -444.09615 -660.29615 9 -649.49615 -444.09615 10 -159.79615 -649.49615 11 -121.44858 -159.79615 12 -223.58108 -121.44858 13 -560.68108 -223.58108 14 -530.58108 -560.68108 15 -195.98108 -530.58108 16 -282.38108 -195.98108 17 -827.38108 -282.38108 18 -3344.56975 -827.38108 19 -2010.06975 -3344.56975 20 -2382.86975 -2010.06975 21 -2077.26975 -2382.86975 22 -1856.56975 -2077.26975 23 -2222.22217 -1856.56975 24 -1765.35468 -2222.22217 25 -1713.45468 -1765.35468 26 -1542.35468 -1713.45468 27 -1362.75468 -1542.35468 28 -1195.15468 -1362.75468 29 -1892.15468 -1195.15468 30 -3980.34335 -1892.15468 31 -3179.84335 -3980.34335 32 -1236.64335 -3179.84335 33 -733.04335 -1236.64335 34 -692.34335 -733.04335 35 -903.99577 -692.34335 36 -708.12827 -903.99577 37 -619.22827 -708.12827 38 -344.12827 -619.22827 39 -314.52827 -344.12827 40 -75.92827 -314.52827 41 -491.92827 -75.92827 42 -420.11694 -491.92827 43 -959.61694 -420.11694 44 735.58306 -959.61694 45 581.18306 735.58306 46 677.88306 581.18306 47 560.23063 677.88306 48 708.09813 560.23063 49 213.99813 708.09813 50 237.09813 213.99813 51 674.69813 237.09813 52 765.29813 674.69813 53 1382.29813 765.29813 54 2232.10946 1382.29813 55 1879.60946 2232.10946 56 3036.80946 1879.60946 57 2280.40946 3036.80946 58 2051.10946 2280.40946 59 1799.45703 2051.10946 60 2021.32453 1799.45703 61 2295.22453 2021.32453 62 1940.32453 2295.22453 63 1748.92453 1940.32453 64 1615.52453 1748.92453 65 1939.52453 1615.52453 66 2214.33586 1939.52453 67 2661.83586 2214.33586 68 4014.03586 2661.83586 69 3360.63586 4014.03586 70 3026.33586 3360.63586 71 2481.68344 3026.33586 72 2140.55094 2481.68344 73 1773.45094 2140.55094 74 1875.55094 1773.45094 75 1161.15094 1875.55094 76 1195.75094 1161.15094 77 1570.75094 1195.75094 78 2681.56227 1570.75094 79 2613.06227 2681.56227 80 1652.26227 2613.06227 81 1850.86227 1652.26227 82 1177.56227 1850.86227 83 829.90984 1177.56227 84 -1048.22266 829.90984 85 -405.32266 -1048.22266 86 -862.22266 -405.32266 87 -213.62266 -862.22266 88 -63.02266 -213.62266 89 136.97734 -63.02266 90 52.78867 136.97734 91 -572.71133 52.78867 92 -1705.51133 -572.71133 93 -2423.91133 -1705.51133 94 -2865.21133 -2423.91133 95 -3270.86376 -2865.21133 96 -3608.99626 -3270.86376 97 -3460.09626 -3608.99626 98 -3801.99626 -3460.09626 99 -3890.39626 -3801.99626 100 -3870.79626 -3890.39626 101 -3693.79626 -3870.79626 102 3311.90176 -3693.79626 103 2020.40176 3311.90176 104 -260.39824 2020.40176 105 233.20176 -260.39824 106 284.90176 233.20176 107 847.24934 284.90176 108 151.11684 847.24934 109 178.01684 151.11684 110 1076.11684 178.01684 111 528.71684 1076.11684 112 301.31684 528.71684 113 1230.31684 301.31684 114 -634.87183 1230.31684 115 -1792.37183 -634.87183 116 -3409.17183 -1792.37183 117 -2422.57183 -3409.17183 118 -1643.87183 -2422.57183 119 NA -1643.87183 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 2298.09252 2333.19252 [2,] 1952.19252 2298.09252 [3,] 1863.79252 1952.19252 [4,] 1609.39252 1863.79252 [5,] 645.39252 1609.39252 [6,] -2112.79615 645.39252 [7,] -660.29615 -2112.79615 [8,] -444.09615 -660.29615 [9,] -649.49615 -444.09615 [10,] -159.79615 -649.49615 [11,] -121.44858 -159.79615 [12,] -223.58108 -121.44858 [13,] -560.68108 -223.58108 [14,] -530.58108 -560.68108 [15,] -195.98108 -530.58108 [16,] -282.38108 -195.98108 [17,] -827.38108 -282.38108 [18,] -3344.56975 -827.38108 [19,] -2010.06975 -3344.56975 [20,] -2382.86975 -2010.06975 [21,] -2077.26975 -2382.86975 [22,] -1856.56975 -2077.26975 [23,] -2222.22217 -1856.56975 [24,] -1765.35468 -2222.22217 [25,] -1713.45468 -1765.35468 [26,] -1542.35468 -1713.45468 [27,] -1362.75468 -1542.35468 [28,] -1195.15468 -1362.75468 [29,] -1892.15468 -1195.15468 [30,] -3980.34335 -1892.15468 [31,] -3179.84335 -3980.34335 [32,] -1236.64335 -3179.84335 [33,] -733.04335 -1236.64335 [34,] -692.34335 -733.04335 [35,] -903.99577 -692.34335 [36,] -708.12827 -903.99577 [37,] -619.22827 -708.12827 [38,] -344.12827 -619.22827 [39,] -314.52827 -344.12827 [40,] -75.92827 -314.52827 [41,] -491.92827 -75.92827 [42,] -420.11694 -491.92827 [43,] -959.61694 -420.11694 [44,] 735.58306 -959.61694 [45,] 581.18306 735.58306 [46,] 677.88306 581.18306 [47,] 560.23063 677.88306 [48,] 708.09813 560.23063 [49,] 213.99813 708.09813 [50,] 237.09813 213.99813 [51,] 674.69813 237.09813 [52,] 765.29813 674.69813 [53,] 1382.29813 765.29813 [54,] 2232.10946 1382.29813 [55,] 1879.60946 2232.10946 [56,] 3036.80946 1879.60946 [57,] 2280.40946 3036.80946 [58,] 2051.10946 2280.40946 [59,] 1799.45703 2051.10946 [60,] 2021.32453 1799.45703 [61,] 2295.22453 2021.32453 [62,] 1940.32453 2295.22453 [63,] 1748.92453 1940.32453 [64,] 1615.52453 1748.92453 [65,] 1939.52453 1615.52453 [66,] 2214.33586 1939.52453 [67,] 2661.83586 2214.33586 [68,] 4014.03586 2661.83586 [69,] 3360.63586 4014.03586 [70,] 3026.33586 3360.63586 [71,] 2481.68344 3026.33586 [72,] 2140.55094 2481.68344 [73,] 1773.45094 2140.55094 [74,] 1875.55094 1773.45094 [75,] 1161.15094 1875.55094 [76,] 1195.75094 1161.15094 [77,] 1570.75094 1195.75094 [78,] 2681.56227 1570.75094 [79,] 2613.06227 2681.56227 [80,] 1652.26227 2613.06227 [81,] 1850.86227 1652.26227 [82,] 1177.56227 1850.86227 [83,] 829.90984 1177.56227 [84,] -1048.22266 829.90984 [85,] -405.32266 -1048.22266 [86,] -862.22266 -405.32266 [87,] -213.62266 -862.22266 [88,] -63.02266 -213.62266 [89,] 136.97734 -63.02266 [90,] 52.78867 136.97734 [91,] -572.71133 52.78867 [92,] -1705.51133 -572.71133 [93,] -2423.91133 -1705.51133 [94,] -2865.21133 -2423.91133 [95,] -3270.86376 -2865.21133 [96,] -3608.99626 -3270.86376 [97,] -3460.09626 -3608.99626 [98,] -3801.99626 -3460.09626 [99,] -3890.39626 -3801.99626 [100,] -3870.79626 -3890.39626 [101,] -3693.79626 -3870.79626 [102,] 3311.90176 -3693.79626 [103,] 2020.40176 3311.90176 [104,] -260.39824 2020.40176 [105,] 233.20176 -260.39824 [106,] 284.90176 233.20176 [107,] 847.24934 284.90176 [108,] 151.11684 847.24934 [109,] 178.01684 151.11684 [110,] 1076.11684 178.01684 [111,] 528.71684 1076.11684 [112,] 301.31684 528.71684 [113,] 1230.31684 301.31684 [114,] -634.87183 1230.31684 [115,] -1792.37183 -634.87183 [116,] -3409.17183 -1792.37183 [117,] -2422.57183 -3409.17183 [118,] -1643.87183 -2422.57183 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 2298.09252 2333.19252 2 1952.19252 2298.09252 3 1863.79252 1952.19252 4 1609.39252 1863.79252 5 645.39252 1609.39252 6 -2112.79615 645.39252 7 -660.29615 -2112.79615 8 -444.09615 -660.29615 9 -649.49615 -444.09615 10 -159.79615 -649.49615 11 -121.44858 -159.79615 12 -223.58108 -121.44858 13 -560.68108 -223.58108 14 -530.58108 -560.68108 15 -195.98108 -530.58108 16 -282.38108 -195.98108 17 -827.38108 -282.38108 18 -3344.56975 -827.38108 19 -2010.06975 -3344.56975 20 -2382.86975 -2010.06975 21 -2077.26975 -2382.86975 22 -1856.56975 -2077.26975 23 -2222.22217 -1856.56975 24 -1765.35468 -2222.22217 25 -1713.45468 -1765.35468 26 -1542.35468 -1713.45468 27 -1362.75468 -1542.35468 28 -1195.15468 -1362.75468 29 -1892.15468 -1195.15468 30 -3980.34335 -1892.15468 31 -3179.84335 -3980.34335 32 -1236.64335 -3179.84335 33 -733.04335 -1236.64335 34 -692.34335 -733.04335 35 -903.99577 -692.34335 36 -708.12827 -903.99577 37 -619.22827 -708.12827 38 -344.12827 -619.22827 39 -314.52827 -344.12827 40 -75.92827 -314.52827 41 -491.92827 -75.92827 42 -420.11694 -491.92827 43 -959.61694 -420.11694 44 735.58306 -959.61694 45 581.18306 735.58306 46 677.88306 581.18306 47 560.23063 677.88306 48 708.09813 560.23063 49 213.99813 708.09813 50 237.09813 213.99813 51 674.69813 237.09813 52 765.29813 674.69813 53 1382.29813 765.29813 54 2232.10946 1382.29813 55 1879.60946 2232.10946 56 3036.80946 1879.60946 57 2280.40946 3036.80946 58 2051.10946 2280.40946 59 1799.45703 2051.10946 60 2021.32453 1799.45703 61 2295.22453 2021.32453 62 1940.32453 2295.22453 63 1748.92453 1940.32453 64 1615.52453 1748.92453 65 1939.52453 1615.52453 66 2214.33586 1939.52453 67 2661.83586 2214.33586 68 4014.03586 2661.83586 69 3360.63586 4014.03586 70 3026.33586 3360.63586 71 2481.68344 3026.33586 72 2140.55094 2481.68344 73 1773.45094 2140.55094 74 1875.55094 1773.45094 75 1161.15094 1875.55094 76 1195.75094 1161.15094 77 1570.75094 1195.75094 78 2681.56227 1570.75094 79 2613.06227 2681.56227 80 1652.26227 2613.06227 81 1850.86227 1652.26227 82 1177.56227 1850.86227 83 829.90984 1177.56227 84 -1048.22266 829.90984 85 -405.32266 -1048.22266 86 -862.22266 -405.32266 87 -213.62266 -862.22266 88 -63.02266 -213.62266 89 136.97734 -63.02266 90 52.78867 136.97734 91 -572.71133 52.78867 92 -1705.51133 -572.71133 93 -2423.91133 -1705.51133 94 -2865.21133 -2423.91133 95 -3270.86376 -2865.21133 96 -3608.99626 -3270.86376 97 -3460.09626 -3608.99626 98 -3801.99626 -3460.09626 99 -3890.39626 -3801.99626 100 -3870.79626 -3890.39626 101 -3693.79626 -3870.79626 102 3311.90176 -3693.79626 103 2020.40176 3311.90176 104 -260.39824 2020.40176 105 233.20176 -260.39824 106 284.90176 233.20176 107 847.24934 284.90176 108 151.11684 847.24934 109 178.01684 151.11684 110 1076.11684 178.01684 111 528.71684 1076.11684 112 301.31684 528.71684 113 1230.31684 301.31684 114 -634.87183 1230.31684 115 -1792.37183 -634.87183 116 -3409.17183 -1792.37183 117 -2422.57183 -3409.17183 118 -1643.87183 -2422.57183 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/7vsij1228917225.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/8raxu1228917225.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/9475v1228917225.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/freestat/rcomp/tmp/108kvy1228917225.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/11f0n31228917225.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/12iifa1228917225.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/13s5mh1228917226.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/1436wb1228917226.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/15e84e1228917226.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/16g80q1228917226.tab") + } > > system("convert tmp/197y11228917225.ps tmp/197y11228917225.png") > system("convert tmp/29l4k1228917225.ps tmp/29l4k1228917225.png") > system("convert tmp/3099b1228917225.ps tmp/3099b1228917225.png") > system("convert tmp/4vb391228917225.ps tmp/4vb391228917225.png") > system("convert tmp/5ug3r1228917225.ps tmp/5ug3r1228917225.png") > system("convert tmp/6y1ym1228917225.ps tmp/6y1ym1228917225.png") > system("convert tmp/7vsij1228917225.ps tmp/7vsij1228917225.png") > system("convert tmp/8raxu1228917225.ps tmp/8raxu1228917225.png") > system("convert tmp/9475v1228917225.ps tmp/9475v1228917225.png") > system("convert tmp/108kvy1228917225.ps tmp/108kvy1228917225.png") > > > proc.time() user system elapsed 4.660 2.582 5.107