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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 + ,0 + ,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('Profbach' + ,'Dummy') + ,1:119)) > y <- array(NA,dim=c(2,119),dimnames=list(c('Profbach','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 = 'No 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 Profbach Dummy M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 1 13363 0 1 0 0 0 0 0 0 0 0 0 0 2 12530 0 0 1 0 0 0 0 0 0 0 0 0 3 11420 0 0 0 1 0 0 0 0 0 0 0 0 4 10948 0 0 0 0 1 0 0 0 0 0 0 0 5 10173 0 0 0 0 0 1 0 0 0 0 0 0 6 10602 0 0 0 0 0 0 1 0 0 0 0 0 7 16094 0 0 0 0 0 0 0 1 0 0 0 0 8 19631 0 0 0 0 0 0 0 0 1 0 0 0 9 17140 0 0 0 0 0 0 0 0 0 1 0 0 10 14345 0 0 0 0 0 0 0 0 0 0 1 0 11 12632 0 0 0 0 0 0 0 0 0 0 0 1 12 12894 0 0 0 0 0 0 0 0 0 0 0 0 13 11808 0 1 0 0 0 0 0 0 0 0 0 0 14 10673 0 0 1 0 0 0 0 0 0 0 0 0 15 9939 0 0 0 1 0 0 0 0 0 0 0 0 16 9890 0 0 0 0 1 0 0 0 0 0 0 0 17 9283 0 0 0 0 0 1 0 0 0 0 0 0 18 10131 0 0 0 0 0 0 1 0 0 0 0 0 19 15864 0 0 0 0 0 0 0 1 0 0 0 0 20 19283 0 0 0 0 0 0 0 0 1 0 0 0 21 16203 0 0 0 0 0 0 0 0 0 1 0 0 22 13919 0 0 0 0 0 0 0 0 0 0 1 0 23 11937 0 0 0 0 0 0 0 0 0 0 0 1 24 11795 0 0 0 0 0 0 0 0 0 0 0 0 25 11268 0 1 0 0 0 0 0 0 0 0 0 0 26 10522 0 0 1 0 0 0 0 0 0 0 0 0 27 9929 0 0 0 1 0 0 0 0 0 0 0 0 28 9725 0 0 0 0 1 0 0 0 0 0 0 0 29 9372 0 0 0 0 0 1 0 0 0 0 0 0 30 10068 0 0 0 0 0 0 1 0 0 0 0 0 31 16230 0 0 0 0 0 0 0 1 0 0 0 0 32 19115 0 0 0 0 0 0 0 0 1 0 0 0 33 18351 0 0 0 0 0 0 0 0 0 1 0 0 34 16265 0 0 0 0 0 0 0 0 0 0 1 0 35 14103 0 0 0 0 0 0 0 0 0 0 0 1 36 14115 0 0 0 0 0 0 0 0 0 0 0 0 37 13327 0 1 0 0 0 0 0 0 0 0 0 0 38 12618 0 0 1 0 0 0 0 0 0 0 0 0 39 12129 0 0 0 1 0 0 0 0 0 0 0 0 40 11775 0 0 0 0 1 0 0 0 0 0 0 0 41 11493 0 0 0 0 0 1 0 0 0 0 0 0 42 12470 0 0 0 0 0 0 1 0 0 0 0 0 43 20792 0 0 0 0 0 0 0 1 0 0 0 0 44 22337 0 0 0 0 0 0 0 0 1 0 0 0 45 21325 0 0 0 0 0 0 0 0 0 1 0 0 46 18581 0 0 0 0 0 0 0 0 0 0 1 0 47 16475 0 0 0 0 0 0 0 0 0 0 0 1 48 16581 0 0 0 0 0 0 0 0 0 0 0 0 49 15745 0 1 0 0 0 0 0 0 0 0 0 0 50 14453 0 0 1 0 0 0 0 0 0 0 0 0 51 13712 0 0 0 1 0 0 0 0 0 0 0 0 52 13766 0 0 0 0 1 0 0 0 0 0 0 0 53 13336 0 0 0 0 0 1 0 0 0 0 0 0 54 15346 0 0 0 0 0 0 1 0 0 0 0 0 55 24446 0 0 0 0 0 0 0 1 0 0 0 0 56 26178 0 0 0 0 0 0 0 0 1 0 0 0 57 24628 0 0 0 0 0 0 0 0 0 1 0 0 58 21282 0 0 0 0 0 0 0 0 0 0 1 0 59 18850 0 0 0 0 0 0 0 0 0 0 0 1 60 18822 0 0 0 0 0 0 0 0 0 0 0 0 61 18060 0 1 0 0 0 0 0 0 0 0 0 0 62 17536 0 0 1 0 0 0 0 0 0 0 0 0 63 16417 0 0 0 1 0 0 0 0 0 0 0 0 64 15842 0 0 0 0 1 0 0 0 0 0 0 0 65 15188 0 0 0 0 0 1 0 0 0 0 0 0 66 16905 0 0 0 0 0 0 1 0 0 0 0 0 67 25430 0 0 0 0 0 0 0 1 0 0 0 0 68 27962 0 0 0 0 0 0 0 0 1 0 0 0 69 26607 0 0 0 0 0 0 0 0 0 1 0 0 70 23364 0 0 0 0 0 0 0 0 0 0 1 0 71 20827 0 0 0 0 0 0 0 0 0 0 0 1 72 20506 0 0 0 0 0 0 0 0 0 0 0 0 73 19181 0 1 0 0 0 0 0 0 0 0 0 0 74 18016 0 0 1 0 0 0 0 0 0 0 0 0 75 17354 0 0 0 1 0 0 0 0 0 0 0 0 76 16256 0 0 0 0 1 0 0 0 0 0 0 0 77 15770 0 0 0 0 0 1 0 0 0 0 0 0 78 17538 0 0 0 0 0 0 1 0 0 0 0 0 79 26899 0 0 0 0 0 0 0 1 0 0 0 0 80 28915 0 0 0 0 0 0 0 0 1 0 0 0 81 25247 0 0 0 0 0 0 0 0 0 1 0 0 82 22856 0 0 0 0 0 0 0 0 0 0 1 0 83 19980 0 0 0 0 0 0 0 0 0 0 0 1 84 19856 0 0 0 0 0 0 0 0 0 0 0 0 85 16994 0 1 0 0 0 0 0 0 0 0 0 0 86 16839 0 0 1 0 0 0 0 0 0 0 0 0 87 15618 0 0 0 1 0 0 0 0 0 0 0 0 88 15883 0 0 0 0 1 0 0 0 0 0 0 0 89 15513 0 0 0 0 0 1 0 0 0 0 0 0 90 17106 0 0 0 0 0 0 1 0 0 0 0 0 91 25272 0 0 0 0 0 0 0 1 0 0 0 0 92 26731 0 0 0 0 0 0 0 0 1 0 0 0 93 22891 0 0 0 0 0 0 0 0 0 1 0 0 94 19583 0 0 0 0 0 0 0 0 0 0 1 0 95 16939 0 0 0 0 0 0 0 0 0 0 0 1 96 16757 0 0 0 0 0 0 0 0 0 0 0 0 97 15435 0 1 0 0 0 0 0 0 0 0 0 0 98 14786 0 0 1 0 0 0 0 0 0 0 0 0 99 13680 0 0 0 1 0 0 0 0 0 0 0 0 100 13208 0 0 0 0 1 0 0 0 0 0 0 0 101 12707 0 0 0 0 0 1 0 0 0 0 0 0 102 14277 0 0 0 0 0 0 1 0 0 0 0 0 103 22436 0 0 0 0 0 0 0 1 0 0 0 0 104 23229 1 0 0 0 0 0 0 0 1 0 0 0 105 18241 1 0 0 0 0 0 0 0 0 1 0 0 106 16145 1 0 0 0 0 0 0 0 0 0 1 0 107 13994 1 0 0 0 0 0 0 0 0 0 0 1 108 14780 1 0 0 0 0 0 0 0 0 0 0 0 109 13100 1 1 0 0 0 0 0 0 0 0 0 0 110 12329 1 0 1 0 0 0 0 0 0 0 0 0 111 12463 1 0 0 1 0 0 0 0 0 0 0 0 112 11532 1 0 0 0 1 0 0 0 0 0 0 0 113 10784 1 0 0 0 0 1 0 0 0 0 0 0 114 13106 1 0 0 0 0 0 1 0 0 0 0 0 115 19491 1 0 0 0 0 0 0 1 0 0 0 0 116 20418 1 0 0 0 0 0 0 0 1 0 0 0 117 16094 1 0 0 0 0 0 0 0 0 1 0 0 118 14491 1 0 0 0 0 0 0 0 0 0 1 0 119 13067 1 0 0 0 0 0 0 0 0 0 0 1 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Dummy M1 M2 M3 M4 16490.9 -2312.3 -1431.6 -2229.5 -2993.6 -3377.2 M5 M6 M7 M8 M9 M10 -3897.8 -2504.8 5035.7 7351.4 4644.2 2054.6 M11 -148.1 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -5662.6 -2398.0 214.7 2732.4 5471.8 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 16490.9 1040.7 15.846 < 2e-16 *** Dummy -2312.3 843.5 -2.741 0.007185 ** M1 -1431.6 1428.7 -1.002 0.318622 M2 -2229.5 1428.7 -1.560 0.121628 M3 -2993.6 1428.7 -2.095 0.038527 * M4 -3377.2 1428.7 -2.364 0.019911 * M5 -3897.8 1428.7 -2.728 0.007457 ** M6 -2504.8 1428.7 -1.753 0.082464 . M7 5035.7 1428.7 3.525 0.000628 *** M8 7351.4 1430.7 5.138 1.27e-06 *** M9 4644.2 1430.7 3.246 0.001566 ** M10 2054.6 1430.7 1.436 0.153905 M11 -148.1 1430.7 -0.103 0.917767 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 3109 on 106 degrees of freedom Multiple R-squared: 0.6018, Adjusted R-squared: 0.5568 F-statistic: 13.35 on 12 and 106 DF, p-value: 2.447e-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,] 8.421738e-02 1.684348e-01 9.157826e-01 [2,] 3.320204e-02 6.640407e-02 9.667980e-01 [3,] 1.156664e-02 2.313327e-02 9.884334e-01 [4,] 4.066461e-03 8.132922e-03 9.959335e-01 [5,] 1.363998e-03 2.727996e-03 9.986360e-01 [6,] 6.031462e-04 1.206292e-03 9.993969e-01 [7,] 2.151710e-04 4.303420e-04 9.997848e-01 [8,] 8.610349e-05 1.722070e-04 9.999139e-01 [9,] 4.908260e-05 9.816521e-05 9.999509e-01 [10,] 4.119060e-05 8.238121e-05 9.999588e-01 [11,] 2.715568e-05 5.431136e-05 9.999728e-01 [12,] 1.396526e-05 2.793052e-05 9.999860e-01 [13,] 7.008649e-06 1.401730e-05 9.999930e-01 [14,] 3.000556e-06 6.001113e-06 9.999970e-01 [15,] 1.521402e-06 3.042803e-06 9.999985e-01 [16,] 1.376754e-06 2.753508e-06 9.999986e-01 [17,] 1.305385e-06 2.610769e-06 9.999987e-01 [18,] 3.584496e-06 7.168992e-06 9.999964e-01 [19,] 1.638017e-05 3.276034e-05 9.999836e-01 [20,] 3.698279e-05 7.396559e-05 9.999630e-01 [21,] 7.891135e-05 1.578227e-04 9.999211e-01 [22,] 8.962798e-05 1.792560e-04 9.999104e-01 [23,] 1.234223e-04 2.468446e-04 9.998766e-01 [24,] 2.181721e-04 4.363443e-04 9.997818e-01 [25,] 3.350808e-04 6.701616e-04 9.996649e-01 [26,] 6.255054e-04 1.251011e-03 9.993745e-01 [27,] 1.863714e-03 3.727428e-03 9.981363e-01 [28,] 4.751927e-02 9.503854e-02 9.524807e-01 [29,] 1.380445e-01 2.760889e-01 8.619555e-01 [30,] 3.099071e-01 6.198142e-01 6.900929e-01 [31,] 4.755252e-01 9.510503e-01 5.244748e-01 [32,] 6.101737e-01 7.796526e-01 3.898263e-01 [33,] 7.302689e-01 5.394621e-01 2.697311e-01 [34,] 7.927293e-01 4.145414e-01 2.072707e-01 [35,] 8.404036e-01 3.191927e-01 1.595964e-01 [36,] 8.781256e-01 2.437489e-01 1.218744e-01 [37,] 9.053776e-01 1.892449e-01 9.462243e-02 [38,] 9.262617e-01 1.474766e-01 7.373829e-02 [39,] 9.588013e-01 8.239743e-02 4.119871e-02 [40,] 9.919017e-01 1.619666e-02 8.098332e-03 [41,] 9.972164e-01 5.567187e-03 2.783594e-03 [42,] 9.989769e-01 2.046294e-03 1.023147e-03 [43,] 9.993773e-01 1.245400e-03 6.226998e-04 [44,] 9.995275e-01 9.449802e-04 4.724901e-04 [45,] 9.996155e-01 7.690108e-04 3.845054e-04 [46,] 9.996824e-01 6.352438e-04 3.176219e-04 [47,] 9.997588e-01 4.824477e-04 2.412238e-04 [48,] 9.997770e-01 4.459455e-04 2.229727e-04 [49,] 9.997658e-01 4.684466e-04 2.342233e-04 [50,] 9.997364e-01 5.272254e-04 2.636127e-04 [51,] 9.997372e-01 5.256517e-04 2.628258e-04 [52,] 9.998167e-01 3.665295e-04 1.832648e-04 [53,] 9.998574e-01 2.852056e-04 1.426028e-04 [54,] 9.999606e-01 7.872556e-05 3.936278e-05 [55,] 9.999803e-01 3.947550e-05 1.973775e-05 [56,] 9.999876e-01 2.484520e-05 1.242260e-05 [57,] 9.999884e-01 2.322788e-05 1.161394e-05 [58,] 9.999910e-01 1.795960e-05 8.979802e-06 [59,] 9.999903e-01 1.938560e-05 9.692801e-06 [60,] 9.999898e-01 2.030921e-05 1.015460e-05 [61,] 9.999849e-01 3.018132e-05 1.509066e-05 [62,] 9.999778e-01 4.439467e-05 2.219733e-05 [63,] 9.999689e-01 6.229904e-05 3.114952e-05 [64,] 9.999847e-01 3.061754e-05 1.530877e-05 [65,] 9.999893e-01 2.147100e-05 1.073550e-05 [66,] 9.999950e-01 9.921887e-06 4.960943e-06 [67,] 9.999983e-01 3.448926e-06 1.724463e-06 [68,] 9.999989e-01 2.118620e-06 1.059310e-06 [69,] 9.999989e-01 2.220248e-06 1.110124e-06 [70,] 9.999974e-01 5.171645e-06 2.585823e-06 [71,] 9.999954e-01 9.174613e-06 4.587306e-06 [72,] 9.999892e-01 2.161867e-05 1.080933e-05 [73,] 9.999836e-01 3.278376e-05 1.639188e-05 [74,] 9.999796e-01 4.085260e-05 2.042630e-05 [75,] 9.999696e-01 6.070264e-05 3.035132e-05 [76,] 9.999804e-01 3.924382e-05 1.962191e-05 [77,] 9.999749e-01 5.022574e-05 2.511287e-05 [78,] 9.999926e-01 1.482178e-05 7.410888e-06 [79,] 9.999920e-01 1.602375e-05 8.011875e-06 [80,] 9.999833e-01 3.338569e-05 1.669284e-05 [81,] 9.999349e-01 1.302934e-04 6.514668e-05 [82,] 9.997669e-01 4.661601e-04 2.330800e-04 [83,] 9.992371e-01 1.525765e-03 7.628826e-04 [84,] 9.976139e-01 4.772199e-03 2.386100e-03 [85,] 9.925044e-01 1.499115e-02 7.495573e-03 [86,] 9.778202e-01 4.435957e-02 2.217979e-02 [87,] 9.486353e-01 1.027294e-01 5.136469e-02 [88,] 8.673209e-01 2.653581e-01 1.326791e-01 > postscript(file="/var/www/html/freestat/rcomp/tmp/1nvmc1229608093.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/2kl1e1229608093.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3hcrf1229608093.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/40feb1229608093.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/5bx0t1229608094.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 -1696.32788 -1731.42788 -2077.32788 -2165.72788 -2420.12788 -3384.12788 7 8 9 10 11 12 -5432.62788 -4211.35576 -3995.15576 -4200.55576 -3710.85576 -3596.91987 13 14 15 16 17 18 -3251.32788 -3588.42788 -3558.32788 -3223.72788 -3310.12788 -3855.12788 19 20 21 22 23 24 -5662.62788 -4559.35576 -4932.15576 -4626.55576 -4405.85576 -4695.91987 25 26 27 28 29 30 -3791.32788 -3739.42788 -3568.32788 -3388.72788 -3221.12788 -3918.12788 31 32 33 34 35 36 -5296.62788 -4727.35576 -2784.15576 -2280.55576 -2239.85576 -2375.91987 37 38 39 40 41 42 -1732.32788 -1643.42788 -1368.32788 -1338.72788 -1100.12788 -1516.12788 43 44 45 46 47 48 -734.62788 -1505.35576 189.84424 35.44424 132.14424 90.08013 49 50 51 52 53 54 685.67212 191.57212 214.67212 652.27212 742.87212 1359.87212 55 56 57 58 59 60 2919.37212 2335.64424 3492.84424 2736.44424 2507.14424 2331.08013 61 62 63 64 65 66 3000.67212 3274.57212 2919.67212 2728.27212 2594.87212 2918.87212 67 68 69 70 71 72 3903.37212 4119.64424 5471.84424 4818.44424 4484.14424 4015.08013 73 74 75 76 77 78 4121.67212 3754.57212 3856.67212 3142.27212 3176.87212 3551.87212 79 80 81 82 83 84 5372.37212 5072.64424 4111.84424 4310.44424 3637.14424 3365.08013 85 86 87 88 89 90 1934.67212 2577.57212 2120.67212 2769.27212 2919.87212 3119.87212 91 92 93 94 95 96 3745.37212 2888.64424 1755.84424 1037.44424 596.14424 266.08013 97 98 99 100 101 102 375.67212 524.57212 182.67212 94.27212 113.87212 290.87212 103 104 105 106 107 108 909.37212 1698.92306 -581.87694 -88.27694 -36.57694 601.35895 109 110 111 112 113 114 352.95094 379.85094 1277.95094 730.55094 503.15094 1432.15094 115 116 117 118 119 276.65094 -1112.07694 -2728.87694 -1742.27694 -963.57694 > postscript(file="/var/www/html/freestat/rcomp/tmp/69qf41229608094.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 -1696.32788 NA 1 -1731.42788 -1696.32788 2 -2077.32788 -1731.42788 3 -2165.72788 -2077.32788 4 -2420.12788 -2165.72788 5 -3384.12788 -2420.12788 6 -5432.62788 -3384.12788 7 -4211.35576 -5432.62788 8 -3995.15576 -4211.35576 9 -4200.55576 -3995.15576 10 -3710.85576 -4200.55576 11 -3596.91987 -3710.85576 12 -3251.32788 -3596.91987 13 -3588.42788 -3251.32788 14 -3558.32788 -3588.42788 15 -3223.72788 -3558.32788 16 -3310.12788 -3223.72788 17 -3855.12788 -3310.12788 18 -5662.62788 -3855.12788 19 -4559.35576 -5662.62788 20 -4932.15576 -4559.35576 21 -4626.55576 -4932.15576 22 -4405.85576 -4626.55576 23 -4695.91987 -4405.85576 24 -3791.32788 -4695.91987 25 -3739.42788 -3791.32788 26 -3568.32788 -3739.42788 27 -3388.72788 -3568.32788 28 -3221.12788 -3388.72788 29 -3918.12788 -3221.12788 30 -5296.62788 -3918.12788 31 -4727.35576 -5296.62788 32 -2784.15576 -4727.35576 33 -2280.55576 -2784.15576 34 -2239.85576 -2280.55576 35 -2375.91987 -2239.85576 36 -1732.32788 -2375.91987 37 -1643.42788 -1732.32788 38 -1368.32788 -1643.42788 39 -1338.72788 -1368.32788 40 -1100.12788 -1338.72788 41 -1516.12788 -1100.12788 42 -734.62788 -1516.12788 43 -1505.35576 -734.62788 44 189.84424 -1505.35576 45 35.44424 189.84424 46 132.14424 35.44424 47 90.08013 132.14424 48 685.67212 90.08013 49 191.57212 685.67212 50 214.67212 191.57212 51 652.27212 214.67212 52 742.87212 652.27212 53 1359.87212 742.87212 54 2919.37212 1359.87212 55 2335.64424 2919.37212 56 3492.84424 2335.64424 57 2736.44424 3492.84424 58 2507.14424 2736.44424 59 2331.08013 2507.14424 60 3000.67212 2331.08013 61 3274.57212 3000.67212 62 2919.67212 3274.57212 63 2728.27212 2919.67212 64 2594.87212 2728.27212 65 2918.87212 2594.87212 66 3903.37212 2918.87212 67 4119.64424 3903.37212 68 5471.84424 4119.64424 69 4818.44424 5471.84424 70 4484.14424 4818.44424 71 4015.08013 4484.14424 72 4121.67212 4015.08013 73 3754.57212 4121.67212 74 3856.67212 3754.57212 75 3142.27212 3856.67212 76 3176.87212 3142.27212 77 3551.87212 3176.87212 78 5372.37212 3551.87212 79 5072.64424 5372.37212 80 4111.84424 5072.64424 81 4310.44424 4111.84424 82 3637.14424 4310.44424 83 3365.08013 3637.14424 84 1934.67212 3365.08013 85 2577.57212 1934.67212 86 2120.67212 2577.57212 87 2769.27212 2120.67212 88 2919.87212 2769.27212 89 3119.87212 2919.87212 90 3745.37212 3119.87212 91 2888.64424 3745.37212 92 1755.84424 2888.64424 93 1037.44424 1755.84424 94 596.14424 1037.44424 95 266.08013 596.14424 96 375.67212 266.08013 97 524.57212 375.67212 98 182.67212 524.57212 99 94.27212 182.67212 100 113.87212 94.27212 101 290.87212 113.87212 102 909.37212 290.87212 103 1698.92306 909.37212 104 -581.87694 1698.92306 105 -88.27694 -581.87694 106 -36.57694 -88.27694 107 601.35895 -36.57694 108 352.95094 601.35895 109 379.85094 352.95094 110 1277.95094 379.85094 111 730.55094 1277.95094 112 503.15094 730.55094 113 1432.15094 503.15094 114 276.65094 1432.15094 115 -1112.07694 276.65094 116 -2728.87694 -1112.07694 117 -1742.27694 -2728.87694 118 -963.57694 -1742.27694 119 NA -963.57694 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -1731.42788 -1696.32788 [2,] -2077.32788 -1731.42788 [3,] -2165.72788 -2077.32788 [4,] -2420.12788 -2165.72788 [5,] -3384.12788 -2420.12788 [6,] -5432.62788 -3384.12788 [7,] -4211.35576 -5432.62788 [8,] -3995.15576 -4211.35576 [9,] -4200.55576 -3995.15576 [10,] -3710.85576 -4200.55576 [11,] -3596.91987 -3710.85576 [12,] -3251.32788 -3596.91987 [13,] -3588.42788 -3251.32788 [14,] -3558.32788 -3588.42788 [15,] -3223.72788 -3558.32788 [16,] -3310.12788 -3223.72788 [17,] -3855.12788 -3310.12788 [18,] -5662.62788 -3855.12788 [19,] -4559.35576 -5662.62788 [20,] -4932.15576 -4559.35576 [21,] -4626.55576 -4932.15576 [22,] -4405.85576 -4626.55576 [23,] -4695.91987 -4405.85576 [24,] -3791.32788 -4695.91987 [25,] -3739.42788 -3791.32788 [26,] -3568.32788 -3739.42788 [27,] -3388.72788 -3568.32788 [28,] -3221.12788 -3388.72788 [29,] -3918.12788 -3221.12788 [30,] -5296.62788 -3918.12788 [31,] -4727.35576 -5296.62788 [32,] -2784.15576 -4727.35576 [33,] -2280.55576 -2784.15576 [34,] -2239.85576 -2280.55576 [35,] -2375.91987 -2239.85576 [36,] -1732.32788 -2375.91987 [37,] -1643.42788 -1732.32788 [38,] -1368.32788 -1643.42788 [39,] -1338.72788 -1368.32788 [40,] -1100.12788 -1338.72788 [41,] -1516.12788 -1100.12788 [42,] -734.62788 -1516.12788 [43,] -1505.35576 -734.62788 [44,] 189.84424 -1505.35576 [45,] 35.44424 189.84424 [46,] 132.14424 35.44424 [47,] 90.08013 132.14424 [48,] 685.67212 90.08013 [49,] 191.57212 685.67212 [50,] 214.67212 191.57212 [51,] 652.27212 214.67212 [52,] 742.87212 652.27212 [53,] 1359.87212 742.87212 [54,] 2919.37212 1359.87212 [55,] 2335.64424 2919.37212 [56,] 3492.84424 2335.64424 [57,] 2736.44424 3492.84424 [58,] 2507.14424 2736.44424 [59,] 2331.08013 2507.14424 [60,] 3000.67212 2331.08013 [61,] 3274.57212 3000.67212 [62,] 2919.67212 3274.57212 [63,] 2728.27212 2919.67212 [64,] 2594.87212 2728.27212 [65,] 2918.87212 2594.87212 [66,] 3903.37212 2918.87212 [67,] 4119.64424 3903.37212 [68,] 5471.84424 4119.64424 [69,] 4818.44424 5471.84424 [70,] 4484.14424 4818.44424 [71,] 4015.08013 4484.14424 [72,] 4121.67212 4015.08013 [73,] 3754.57212 4121.67212 [74,] 3856.67212 3754.57212 [75,] 3142.27212 3856.67212 [76,] 3176.87212 3142.27212 [77,] 3551.87212 3176.87212 [78,] 5372.37212 3551.87212 [79,] 5072.64424 5372.37212 [80,] 4111.84424 5072.64424 [81,] 4310.44424 4111.84424 [82,] 3637.14424 4310.44424 [83,] 3365.08013 3637.14424 [84,] 1934.67212 3365.08013 [85,] 2577.57212 1934.67212 [86,] 2120.67212 2577.57212 [87,] 2769.27212 2120.67212 [88,] 2919.87212 2769.27212 [89,] 3119.87212 2919.87212 [90,] 3745.37212 3119.87212 [91,] 2888.64424 3745.37212 [92,] 1755.84424 2888.64424 [93,] 1037.44424 1755.84424 [94,] 596.14424 1037.44424 [95,] 266.08013 596.14424 [96,] 375.67212 266.08013 [97,] 524.57212 375.67212 [98,] 182.67212 524.57212 [99,] 94.27212 182.67212 [100,] 113.87212 94.27212 [101,] 290.87212 113.87212 [102,] 909.37212 290.87212 [103,] 1698.92306 909.37212 [104,] -581.87694 1698.92306 [105,] -88.27694 -581.87694 [106,] -36.57694 -88.27694 [107,] 601.35895 -36.57694 [108,] 352.95094 601.35895 [109,] 379.85094 352.95094 [110,] 1277.95094 379.85094 [111,] 730.55094 1277.95094 [112,] 503.15094 730.55094 [113,] 1432.15094 503.15094 [114,] 276.65094 1432.15094 [115,] -1112.07694 276.65094 [116,] -2728.87694 -1112.07694 [117,] -1742.27694 -2728.87694 [118,] -963.57694 -1742.27694 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -1731.42788 -1696.32788 2 -2077.32788 -1731.42788 3 -2165.72788 -2077.32788 4 -2420.12788 -2165.72788 5 -3384.12788 -2420.12788 6 -5432.62788 -3384.12788 7 -4211.35576 -5432.62788 8 -3995.15576 -4211.35576 9 -4200.55576 -3995.15576 10 -3710.85576 -4200.55576 11 -3596.91987 -3710.85576 12 -3251.32788 -3596.91987 13 -3588.42788 -3251.32788 14 -3558.32788 -3588.42788 15 -3223.72788 -3558.32788 16 -3310.12788 -3223.72788 17 -3855.12788 -3310.12788 18 -5662.62788 -3855.12788 19 -4559.35576 -5662.62788 20 -4932.15576 -4559.35576 21 -4626.55576 -4932.15576 22 -4405.85576 -4626.55576 23 -4695.91987 -4405.85576 24 -3791.32788 -4695.91987 25 -3739.42788 -3791.32788 26 -3568.32788 -3739.42788 27 -3388.72788 -3568.32788 28 -3221.12788 -3388.72788 29 -3918.12788 -3221.12788 30 -5296.62788 -3918.12788 31 -4727.35576 -5296.62788 32 -2784.15576 -4727.35576 33 -2280.55576 -2784.15576 34 -2239.85576 -2280.55576 35 -2375.91987 -2239.85576 36 -1732.32788 -2375.91987 37 -1643.42788 -1732.32788 38 -1368.32788 -1643.42788 39 -1338.72788 -1368.32788 40 -1100.12788 -1338.72788 41 -1516.12788 -1100.12788 42 -734.62788 -1516.12788 43 -1505.35576 -734.62788 44 189.84424 -1505.35576 45 35.44424 189.84424 46 132.14424 35.44424 47 90.08013 132.14424 48 685.67212 90.08013 49 191.57212 685.67212 50 214.67212 191.57212 51 652.27212 214.67212 52 742.87212 652.27212 53 1359.87212 742.87212 54 2919.37212 1359.87212 55 2335.64424 2919.37212 56 3492.84424 2335.64424 57 2736.44424 3492.84424 58 2507.14424 2736.44424 59 2331.08013 2507.14424 60 3000.67212 2331.08013 61 3274.57212 3000.67212 62 2919.67212 3274.57212 63 2728.27212 2919.67212 64 2594.87212 2728.27212 65 2918.87212 2594.87212 66 3903.37212 2918.87212 67 4119.64424 3903.37212 68 5471.84424 4119.64424 69 4818.44424 5471.84424 70 4484.14424 4818.44424 71 4015.08013 4484.14424 72 4121.67212 4015.08013 73 3754.57212 4121.67212 74 3856.67212 3754.57212 75 3142.27212 3856.67212 76 3176.87212 3142.27212 77 3551.87212 3176.87212 78 5372.37212 3551.87212 79 5072.64424 5372.37212 80 4111.84424 5072.64424 81 4310.44424 4111.84424 82 3637.14424 4310.44424 83 3365.08013 3637.14424 84 1934.67212 3365.08013 85 2577.57212 1934.67212 86 2120.67212 2577.57212 87 2769.27212 2120.67212 88 2919.87212 2769.27212 89 3119.87212 2919.87212 90 3745.37212 3119.87212 91 2888.64424 3745.37212 92 1755.84424 2888.64424 93 1037.44424 1755.84424 94 596.14424 1037.44424 95 266.08013 596.14424 96 375.67212 266.08013 97 524.57212 375.67212 98 182.67212 524.57212 99 94.27212 182.67212 100 113.87212 94.27212 101 290.87212 113.87212 102 909.37212 290.87212 103 1698.92306 909.37212 104 -581.87694 1698.92306 105 -88.27694 -581.87694 106 -36.57694 -88.27694 107 601.35895 -36.57694 108 352.95094 601.35895 109 379.85094 352.95094 110 1277.95094 379.85094 111 730.55094 1277.95094 112 503.15094 730.55094 113 1432.15094 503.15094 114 276.65094 1432.15094 115 -1112.07694 276.65094 116 -2728.87694 -1112.07694 117 -1742.27694 -2728.87694 118 -963.57694 -1742.27694 > 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/7uq9h1229608094.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/8yz3v1229608094.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/9o4871229608094.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/freestat/rcomp/tmp/10wpj31229608094.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/115rfm1229608094.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/12oy831229608094.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/13409u1229608094.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/1482jo1229608094.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/1589qv1229608094.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/16nnm11229608094.tab") + } > > system("convert tmp/1nvmc1229608093.ps tmp/1nvmc1229608093.png") > system("convert tmp/2kl1e1229608093.ps tmp/2kl1e1229608093.png") > system("convert tmp/3hcrf1229608093.ps tmp/3hcrf1229608093.png") > system("convert tmp/40feb1229608093.ps tmp/40feb1229608093.png") > system("convert tmp/5bx0t1229608094.ps tmp/5bx0t1229608094.png") > system("convert tmp/69qf41229608094.ps tmp/69qf41229608094.png") > system("convert tmp/7uq9h1229608094.ps tmp/7uq9h1229608094.png") > system("convert tmp/8yz3v1229608094.ps tmp/8yz3v1229608094.png") > system("convert tmp/9o4871229608094.ps tmp/9o4871229608094.png") > system("convert tmp/10wpj31229608094.ps tmp/10wpj31229608094.png") > > > proc.time() user system elapsed 4.624 2.557 5.065