R version 2.12.0 (2010-10-15) Copyright (C) 2010 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: x86_64-redhat-linux-gnu (64-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(347553 + ,0.032500 + ,125.01 + ,0.012257 + ,353245 + ,0.025000 + ,120.96 + ,0.014315 + ,347966 + ,0.025000 + ,117.07 + ,0.012208 + ,364343 + ,0.025000 + ,112.45 + ,0.009063 + ,341713 + ,0.025000 + ,110.23 + ,0.009054 + ,361162 + ,0.025000 + ,107.34 + ,0.009063 + ,354400 + ,0.025000 + ,107.73 + ,0.019270 + ,345183 + ,0.025000 + ,103.71 + ,0.018200 + ,341807 + ,0.017500 + ,105.28 + ,0.015106 + ,348712 + ,0.017500 + ,106.92 + ,0.013078 + ,349011 + ,0.017500 + ,107.8 + ,0.010081 + ,416259 + ,0.017500 + ,109.7 + ,0.011089 + ,360289 + ,0.017500 + ,111.51 + ,0.013118 + ,367557 + ,0.017500 + ,106.21 + ,0.012097 + ,364611 + ,0.017500 + ,105.14 + ,0.013065 + ,378688 + ,0.017500 + ,103.53 + ,0.007984 + ,351763 + ,0.017500 + ,103.99 + ,0.007976 + ,377765 + ,0.017500 + ,102.72 + ,0.004990 + ,373212 + ,0.017500 + ,98.5 + ,-0.001990 + ,365819 + ,0.017500 + ,99.85 + ,0.000000 + ,364686 + ,0.017500 + ,98.81 + ,0.001984 + ,363333 + ,0.017500 + ,98.42 + ,0.007944 + 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,0.007500 + ,112.34 + ,0.006986 + ,762561 + ,0.007500 + ,107.66 + ,0.007000 + ,763579 + ,0.007500 + ,107.16 + ,0.010050 + ,764615 + ,0.007500 + ,100.79 + ,0.012024 + ,773312 + ,0.007500 + ,102.49 + ,0.007992 + ,755697 + ,0.007500 + ,104.14 + ,0.012948 + ,762909 + ,0.007500 + ,106.9 + ,0.019960 + ,760337 + ,0.007500 + ,106.81 + ,0.022977 + ,759270 + ,0.007500 + ,109.28 + ,0.020875 + ,754929 + ,0.007500 + ,106.75 + ,0.020875 + ,766116 + ,0.005000 + ,100.33 + ,0.016848 + ,765945 + ,0.005000 + ,96.81 + ,0.009930 + ,814783 + ,0.003000 + ,91.28 + ,0.003964 + ,768494 + ,0.003000 + ,90.41 + ,0.000000 + ,769222 + ,0.003000 + ,92.5 + ,-0.000995 + ,768977 + ,0.003000 + ,97.87 + ,-0.002970 + ,783341 + ,0.003000 + ,99 + ,-0.000991 + ,764061 + ,0.003000 + ,96.3 + ,-0.010816 + ,767394 + ,0.003000 + ,96.52 + ,-0.017613 + ,763910 + ,0.003000 + ,94.5 + ,-0.022461 + ,761677 + ,0.003000 + ,94.84 + ,-0.022395 + ,759173 + ,0.003000 + ,91.49 + ,-0.022395 + ,762486 + ,0.003000 + ,90.29 + ,-0.025341 + ,762690 + ,0.003000 + ,89.19 + ,-0.018682 + ,809542 + ,0.003000 + ,89.55 + ,-0.016782 + ,769041 + ,0.003000 + ,91.16 + ,-0.012910 + ,770889 + ,0.003000 + ,90.28 + ,-0.010956 + ,773527 + ,0.003000 + ,90.52 + ,-0.010924 + ,789890 + ,0.003000 + ,93.38 + ,-0.011905 + ,768325 + ,0.003000 + ,91.74 + ,-0.008946 + ,772712 + ,0.003000 + ,90.92 + ,-0.006972 + ,772944 + ,0.003000 + ,87.72 + ,-0.008991 + ,769637 + ,0.003000 + ,85.47 + ,-0.008964 + ,768546 + ,0.003000 + ,84.38 + ,-0.005976 + ,775013 + ,0.003000 + ,81.87 + ,0.002000 + ,776635 + ,0.003000 + ,82.48 + ,0.001002) + ,dim=c(4 + ,215) + ,dimnames=list(c('Banknotes' + ,'Loan_Interest' + ,'Exchange_Rate_USD' + ,'Inflation') + ,1:215)) > y <- array(NA,dim=c(4,215),dimnames=list(c('Banknotes','Loan_Interest','Exchange_Rate_USD','Inflation'),1:215)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '1' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > library(lmtest) Loading required package: zoo > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x Banknotes Loan_Interest Exchange_Rate_USD Inflation 1 347553 0.0325 125.01 0.012257 2 353245 0.0250 120.96 0.014315 3 347966 0.0250 117.07 0.012208 4 364343 0.0250 112.45 0.009063 5 341713 0.0250 110.23 0.009054 6 361162 0.0250 107.34 0.009063 7 354400 0.0250 107.73 0.019270 8 345183 0.0250 103.71 0.018200 9 341807 0.0175 105.28 0.015106 10 348712 0.0175 106.92 0.013078 11 349011 0.0175 107.80 0.010081 12 416259 0.0175 109.70 0.011089 13 360289 0.0175 111.51 0.013118 14 367557 0.0175 106.21 0.012097 15 364611 0.0175 105.14 0.013065 16 378688 0.0175 103.53 0.007984 17 351763 0.0175 103.99 0.007976 18 377765 0.0175 102.72 0.004990 19 373212 0.0175 98.50 -0.001990 20 365819 0.0175 99.85 0.000000 21 364686 0.0175 98.81 0.001984 22 363333 0.0175 98.42 0.007944 23 362536 0.0175 97.96 0.009980 24 428803 0.0175 100.13 0.005982 25 375361 0.0175 99.75 0.004980 26 377205 0.0175 98.24 0.001992 27 381266 0.0175 90.79 -0.002976 28 390516 0.0100 83.67 -0.001980 29 366117 0.0100 85.10 -0.000989 30 393928 0.0100 84.53 0.001986 31 387784 0.0100 87.22 0.000997 32 385656 0.0100 94.55 -0.001986 33 385320 0.0050 100.49 0.000990 34 389053 0.0050 100.65 -0.006897 35 390595 0.0050 101.92 -0.006917 36 462440 0.0050 101.85 -0.003964 37 402532 0.0050 105.84 -0.004955 38 409070 0.0050 105.73 -0.003976 39 421329 0.0050 105.85 -0.000995 40 428841 0.0050 107.46 0.001984 41 404864 0.0050 106.51 0.001980 42 432633 0.0050 108.86 0.000000 43 416886 0.0050 109.32 0.003984 44 414893 0.0050 107.75 0.001990 45 417914 0.0050 109.75 0.000000 46 417518 0.0050 112.36 0.004960 47 423137 0.0050 112.26 0.004975 48 506710 0.0050 113.81 0.005970 49 436264 0.0050 118.02 0.005976 50 443712 0.0050 123.01 0.005988 51 452849 0.0050 122.64 0.004980 52 453009 0.0050 125.51 0.019802 53 437876 0.0050 118.99 0.019763 54 460041 0.0050 114.20 0.022795 55 450426 0.0050 115.16 0.019841 56 447873 0.0050 117.90 0.021847 57 444955 0.0050 120.74 0.024728 58 452043 0.0050 121.06 0.025666 59 480877 0.0050 125.27 0.021782 60 546696 0.0050 129.47 0.018793 61 483668 0.0050 129.45 0.018812 62 489627 0.0050 126.00 0.019841 63 490007 0.0050 128.69 0.022795 64 496590 0.0050 131.67 0.003883 65 480846 0.0050 135.00 0.004845 66 497677 0.0050 140.57 0.000969 67 492795 0.0050 140.73 -0.000973 68 488495 0.0050 144.67 -0.002915 69 486769 0.0050 134.59 -0.001931 70 494455 0.0050 121.30 0.001925 71 498054 0.0050 120.58 0.007752 72 558648 0.0050 117.54 0.005825 73 506424 0.0050 113.18 0.001944 74 512528 0.0050 116.66 -0.000973 75 512866 0.0050 119.78 -0.003876 76 529324 0.0050 119.81 -0.000967 77 508431 0.0050 122.11 -0.003857 78 523026 0.0050 120.90 -0.002904 79 521355 0.0050 119.86 -0.000974 80 514103 0.0050 113.40 0.002924 81 513885 0.0050 107.57 -0.001934 82 522150 0.0050 105.97 -0.006724 83 527384 0.0050 104.96 -0.011538 84 654047 0.0050 102.68 -0.010618 85 543115 0.0050 105.16 -0.006790 86 543200 0.0050 109.34 -0.006816 87 571201 0.0050 106.71 -0.005837 88 568892 0.0050 105.48 -0.007744 89 537223 0.0050 108.11 -0.006776 90 553186 0.0050 106.23 -0.005825 91 550954 0.0050 107.90 -0.005848 92 543433 0.0050 108.07 -0.004859 93 557195 0.0050 106.75 -0.009690 94 565522 0.0050 108.36 -0.011605 95 571691 0.0050 108.89 -0.008755 96 633972 0.0050 112.21 -0.004878 97 575265 0.0050 117.10 -0.003906 98 572364 0.0035 116.04 -0.002941 99 586744 0.0025 121.12 -0.006849 100 600389 0.0025 123.83 -0.007805 101 578540 0.0025 121.93 -0.007797 102 610778 0.0025 122.15 -0.008789 103 596577 0.0025 124.68 -0.007843 104 590558 0.0025 121.61 -0.007813 105 597294 0.0010 118.98 -0.007828 106 602384 0.0010 121.28 -0.007828 107 614190 0.0010 122.31 -0.009814 108 690042 0.0010 127.36 -0.011765 109 639497 0.0010 132.66 -0.013725 110 649304 0.0010 133.52 -0.015733 111 678762 0.0010 131.20 -0.011823 112 691885 0.0010 131.07 -0.010816 113 667973 0.0010 126.48 -0.008841 114 682032 0.0010 123.60 -0.006897 115 672651 0.0010 118.07 -0.007905 116 671865 0.0010 119.01 -0.008858 117 671463 0.0010 120.50 -0.006903 118 675917 0.0010 123.86 -0.008876 119 680952 0.0010 121.49 -0.003964 120 754718 0.0010 122.27 -0.002976 121 694413 0.0010 118.65 -0.003976 122 699390 0.0010 119.27 -0.001998 123 710573 0.0010 118.57 -0.000997 124 714217 0.0010 119.79 -0.000994 125 702996 0.0010 117.26 -0.001982 126 712370 0.0010 118.26 -0.003968 127 708445 0.0010 118.69 -0.001992 128 707083 0.0010 118.83 -0.002979 129 700632 0.0010 115.19 -0.001986 130 706309 0.0010 109.58 0.000000 131 709523 0.0010 109.20 -0.004975 132 769096 0.0010 107.90 -0.003980 133 715100 0.0010 106.48 -0.002994 134 713872 0.0010 106.55 0.000000 135 714032 0.0010 108.62 -0.000998 136 732269 0.0010 107.25 -0.003980 137 711137 0.0010 112.35 -0.004965 138 715284 0.0010 109.47 0.000000 139 716888 0.0010 109.36 -0.000998 140 716426 0.0010 110.35 -0.001992 141 714726 0.0010 110.01 0.000000 142 718016 0.0010 108.92 0.004975 143 725932 0.0010 104.90 0.008000 144 779564 0.0010 103.84 0.001998 145 732144 0.0010 103.21 0.002002 146 730816 0.0010 104.88 -0.001001 147 746719 0.0010 105.31 0.000000 148 760065 0.0010 107.36 0.000999 149 734516 0.0010 106.91 0.000998 150 740167 0.0010 108.63 -0.004980 151 740976 0.0010 111.93 -0.002997 152 735764 0.0010 110.72 -0.002994 153 734711 0.0010 111.06 -0.002985 154 737916 0.0010 114.82 -0.007921 155 739132 0.0010 118.41 -0.009921 156 792705 0.0010 118.64 -0.003988 157 747488 0.0010 115.45 -0.000999 158 746616 0.0010 117.89 -0.001002 159 749781 0.0010 117.31 -0.001998 160 760911 0.0010 117.11 -0.000998 161 739543 0.0010 111.51 0.000997 162 745626 0.0010 114.53 0.005005 163 746246 0.0040 115.67 0.003006 164 744769 0.0040 115.88 0.009009 165 741388 0.0040 117.01 0.005988 166 744469 0.0040 118.66 0.003992 167 745566 0.0040 117.35 0.003006 168 798367 0.0040 117.30 0.003003 169 752440 0.0040 120.58 0.000000 170 756627 0.0075 120.45 -0.002006 171 758941 0.0075 117.28 -0.001001 172 771287 0.0075 118.83 0.000000 173 749858 0.0075 120.73 0.000000 174 758370 0.0075 122.62 -0.001992 175 755407 0.0075 121.59 0.000000 176 752063 0.0075 116.72 -0.001984 177 756298 0.0075 115.01 -0.001984 178 755892 0.0075 115.74 0.002982 179 758486 0.0075 111.21 0.005994 180 812777 0.0075 112.34 0.006986 181 762561 0.0075 107.66 0.007000 182 763579 0.0075 107.16 0.010050 183 764615 0.0075 100.79 0.012024 184 773312 0.0075 102.49 0.007992 185 755697 0.0075 104.14 0.012948 186 762909 0.0075 106.90 0.019960 187 760337 0.0075 106.81 0.022977 188 759270 0.0075 109.28 0.020875 189 754929 0.0075 106.75 0.020875 190 766116 0.0050 100.33 0.016848 191 765945 0.0050 96.81 0.009930 192 814783 0.0030 91.28 0.003964 193 768494 0.0030 90.41 0.000000 194 769222 0.0030 92.50 -0.000995 195 768977 0.0030 97.87 -0.002970 196 783341 0.0030 99.00 -0.000991 197 764061 0.0030 96.30 -0.010816 198 767394 0.0030 96.52 -0.017613 199 763910 0.0030 94.50 -0.022461 200 761677 0.0030 94.84 -0.022395 201 759173 0.0030 91.49 -0.022395 202 762486 0.0030 90.29 -0.025341 203 762690 0.0030 89.19 -0.018682 204 809542 0.0030 89.55 -0.016782 205 769041 0.0030 91.16 -0.012910 206 770889 0.0030 90.28 -0.010956 207 773527 0.0030 90.52 -0.010924 208 789890 0.0030 93.38 -0.011905 209 768325 0.0030 91.74 -0.008946 210 772712 0.0030 90.92 -0.006972 211 772944 0.0030 87.72 -0.008991 212 769637 0.0030 85.47 -0.008964 213 768546 0.0030 84.38 -0.005976 214 775013 0.0030 81.87 0.002000 215 776635 0.0030 82.48 0.001002 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Loan_Interest Exchange_Rate_USD Inflation 952696 -17024358 -2262 -583456 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -254887 -74202 17946 70822 245940 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 9.527e+05 7.840e+04 12.151 < 2e-16 *** Loan_Interest -1.702e+07 1.499e+06 -11.356 < 2e-16 *** Exchange_Rate_USD -2.262e+03 6.814e+02 -3.319 0.00106 ** Inflation -5.835e+05 9.447e+05 -0.618 0.53751 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 113200 on 211 degrees of freedom Multiple R-squared: 0.4629, Adjusted R-squared: 0.4552 F-statistic: 60.61 on 3 and 211 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,] 1.156715e-03 2.313429e-03 9.988433e-01 [2,] 1.183763e-04 2.367525e-04 9.998816e-01 [3,] 1.408408e-05 2.816816e-05 9.999859e-01 [4,] 1.058607e-06 2.117213e-06 9.999989e-01 [5,] 7.421328e-08 1.484266e-07 9.999999e-01 [6,] 2.080191e-05 4.160381e-05 9.999792e-01 [7,] 3.794080e-06 7.588161e-06 9.999962e-01 [8,] 6.584548e-07 1.316910e-06 9.999993e-01 [9,] 1.074915e-07 2.149830e-07 9.999999e-01 [10,] 1.928498e-08 3.856996e-08 1.000000e+00 [11,] 4.467472e-09 8.934945e-09 1.000000e+00 [12,] 7.322174e-10 1.464435e-09 1.000000e+00 [13,] 1.094575e-10 2.189150e-10 1.000000e+00 [14,] 1.697343e-11 3.394686e-11 1.000000e+00 [15,] 2.419092e-12 4.838184e-12 1.000000e+00 [16,] 3.233142e-13 6.466285e-13 1.000000e+00 [17,] 4.215719e-14 8.431438e-14 1.000000e+00 [18,] 1.987561e-12 3.975122e-12 1.000000e+00 [19,] 3.363223e-13 6.726446e-13 1.000000e+00 [20,] 5.516466e-14 1.103293e-13 1.000000e+00 [21,] 8.793757e-15 1.758751e-14 1.000000e+00 [22,] 1.587921e-15 3.175841e-15 1.000000e+00 [23,] 5.795710e-16 1.159142e-15 1.000000e+00 [24,] 1.349114e-16 2.698229e-16 1.000000e+00 [25,] 2.700514e-17 5.401028e-17 1.000000e+00 [26,] 5.389672e-18 1.077934e-17 1.000000e+00 [27,] 1.446305e-18 2.892609e-18 1.000000e+00 [28,] 4.087215e-19 8.174429e-19 1.000000e+00 [29,] 1.111879e-19 2.223758e-19 1.000000e+00 [30,] 8.890248e-18 1.778050e-17 1.000000e+00 [31,] 2.833336e-18 5.666671e-18 1.000000e+00 [32,] 9.038628e-19 1.807726e-18 1.000000e+00 [33,] 4.013728e-19 8.027455e-19 1.000000e+00 [34,] 2.441692e-19 4.883384e-19 1.000000e+00 [35,] 8.989909e-20 1.797982e-19 1.000000e+00 [36,] 5.278794e-20 1.055759e-19 1.000000e+00 [37,] 2.025425e-20 4.050849e-20 1.000000e+00 [38,] 8.339899e-21 1.667980e-20 1.000000e+00 [39,] 3.418690e-21 6.837381e-21 1.000000e+00 [40,] 1.376025e-21 2.752049e-21 1.000000e+00 [41,] 6.303355e-22 1.260671e-21 1.000000e+00 [42,] 1.115389e-18 2.230778e-18 1.000000e+00 [43,] 4.754896e-19 9.509792e-19 1.000000e+00 [44,] 1.806103e-19 3.612206e-19 1.000000e+00 [45,] 8.113556e-20 1.622711e-19 1.000000e+00 [46,] 3.245243e-20 6.490485e-20 1.000000e+00 [47,] 1.438901e-20 2.877802e-20 1.000000e+00 [48,] 1.432349e-20 2.864698e-20 1.000000e+00 [49,] 9.244663e-21 1.848933e-20 1.000000e+00 [50,] 5.467714e-21 1.093543e-20 1.000000e+00 [51,] 3.432414e-21 6.864828e-21 1.000000e+00 [52,] 2.466943e-21 4.933886e-21 1.000000e+00 [53,] 2.919289e-21 5.838577e-21 1.000000e+00 [54,] 6.749012e-19 1.349802e-18 1.000000e+00 [55,] 4.492307e-19 8.984615e-19 1.000000e+00 [56,] 4.927165e-19 9.854329e-19 1.000000e+00 [57,] 4.888908e-19 9.777816e-19 1.000000e+00 [58,] 4.134474e-19 8.268949e-19 1.000000e+00 [59,] 1.915298e-19 3.830597e-19 1.000000e+00 [60,] 7.507845e-20 1.501569e-19 1.000000e+00 [61,] 2.672854e-20 5.345708e-20 1.000000e+00 [62,] 8.857415e-21 1.771483e-20 1.000000e+00 [63,] 4.044099e-21 8.088199e-21 1.000000e+00 [64,] 1.004869e-20 2.009737e-20 1.000000e+00 [65,] 3.832311e-20 7.664622e-20 1.000000e+00 [66,] 4.221563e-17 8.443126e-17 1.000000e+00 [67,] 4.036915e-16 8.073830e-16 1.000000e+00 [68,] 2.325954e-15 4.651908e-15 1.000000e+00 [69,] 6.813723e-15 1.362745e-14 1.000000e+00 [70,] 3.957166e-14 7.914332e-14 1.000000e+00 [71,] 6.698670e-14 1.339734e-13 1.000000e+00 [72,] 1.959005e-13 3.918009e-13 1.000000e+00 [73,] 6.657476e-13 1.331495e-12 1.000000e+00 [74,] 5.867681e-12 1.173536e-11 1.000000e+00 [75,] 7.724868e-11 1.544974e-10 1.000000e+00 [76,] 9.372400e-10 1.874480e-09 1.000000e+00 [77,] 8.090166e-09 1.618033e-08 1.000000e+00 [78,] 1.625156e-05 3.250312e-05 9.999837e-01 [79,] 7.584179e-05 1.516836e-04 9.999242e-01 [80,] 2.416879e-04 4.833757e-04 9.997583e-01 [81,] 1.131179e-03 2.262359e-03 9.988688e-01 [82,] 4.068182e-03 8.136364e-03 9.959318e-01 [83,] 1.143541e-02 2.287082e-02 9.885646e-01 [84,] 3.463691e-02 6.927381e-02 9.653631e-01 [85,] 8.886363e-02 1.777273e-01 9.111364e-01 [86,] 2.171718e-01 4.343436e-01 7.828282e-01 [87,] 4.060691e-01 8.121382e-01 5.939309e-01 [88,] 6.125862e-01 7.748276e-01 3.874138e-01 [89,] 8.209330e-01 3.581340e-01 1.790670e-01 [90,] 9.360230e-01 1.279540e-01 6.397702e-02 [91,] 9.827228e-01 3.455431e-02 1.727715e-02 [92,] 9.971906e-01 5.618769e-03 2.809384e-03 [93,] 9.991838e-01 1.632461e-03 8.162303e-04 [94,] 9.996902e-01 6.196449e-04 3.098225e-04 [95,] 9.999598e-01 8.047763e-05 4.023882e-05 [96,] 9.999905e-01 1.909589e-05 9.547947e-06 [97,] 9.999988e-01 2.488792e-06 1.244396e-06 [98,] 1.000000e+00 7.186855e-08 3.593427e-08 [99,] 1.000000e+00 1.385486e-09 6.927428e-10 [100,] 1.000000e+00 1.775855e-11 8.879276e-12 [101,] 1.000000e+00 2.730772e-13 1.365386e-13 [102,] 1.000000e+00 1.690118e-13 8.450590e-14 [103,] 1.000000e+00 7.435368e-14 3.717684e-14 [104,] 1.000000e+00 5.081239e-14 2.540620e-14 [105,] 1.000000e+00 5.104922e-14 2.552461e-14 [106,] 1.000000e+00 4.838599e-14 2.419300e-14 [107,] 1.000000e+00 1.999924e-14 9.999618e-15 [108,] 1.000000e+00 6.683218e-15 3.341609e-15 [109,] 1.000000e+00 7.454991e-16 3.727496e-16 [110,] 1.000000e+00 8.806859e-17 4.403430e-17 [111,] 1.000000e+00 9.183689e-18 4.591845e-18 [112,] 1.000000e+00 2.063368e-18 1.031684e-18 [113,] 1.000000e+00 2.545337e-19 1.272668e-19 [114,] 1.000000e+00 5.316655e-21 2.658328e-21 [115,] 1.000000e+00 1.046861e-21 5.234305e-22 [116,] 1.000000e+00 2.427350e-22 1.213675e-22 [117,] 1.000000e+00 6.643115e-23 3.321557e-23 [118,] 1.000000e+00 2.567119e-23 1.283559e-23 [119,] 1.000000e+00 7.451687e-24 3.725843e-24 [120,] 1.000000e+00 4.079135e-24 2.039568e-24 [121,] 1.000000e+00 2.003554e-24 1.001777e-24 [122,] 1.000000e+00 1.082914e-24 5.414569e-25 [123,] 1.000000e+00 2.571198e-25 1.285599e-25 [124,] 1.000000e+00 3.611215e-26 1.805607e-26 [125,] 1.000000e+00 8.258830e-27 4.129415e-27 [126,] 1.000000e+00 9.022788e-28 4.511394e-28 [127,] 1.000000e+00 2.570866e-28 1.285433e-28 [128,] 1.000000e+00 6.278468e-29 3.139234e-29 [129,] 1.000000e+00 2.134899e-29 1.067449e-29 [130,] 1.000000e+00 1.922403e-29 9.612013e-30 [131,] 1.000000e+00 8.881523e-30 4.440761e-30 [132,] 1.000000e+00 3.553955e-30 1.776978e-30 [133,] 1.000000e+00 1.573225e-30 7.866126e-31 [134,] 1.000000e+00 7.036197e-31 3.518098e-31 [135,] 1.000000e+00 2.196836e-31 1.098418e-31 [136,] 1.000000e+00 6.733561e-32 3.366780e-32 [137,] 1.000000e+00 2.431909e-32 1.215955e-32 [138,] 1.000000e+00 7.427910e-33 3.713955e-33 [139,] 1.000000e+00 5.796285e-33 2.898143e-33 [140,] 1.000000e+00 4.693838e-33 2.346919e-33 [141,] 1.000000e+00 1.004747e-32 5.023736e-33 [142,] 1.000000e+00 2.167557e-32 1.083778e-32 [143,] 1.000000e+00 2.909692e-32 1.454846e-32 [144,] 1.000000e+00 6.762521e-32 3.381260e-32 [145,] 1.000000e+00 1.819471e-31 9.097356e-32 [146,] 1.000000e+00 3.304958e-31 1.652479e-31 [147,] 1.000000e+00 5.193971e-31 2.596985e-31 [148,] 1.000000e+00 1.273522e-30 6.367608e-31 [149,] 1.000000e+00 3.776613e-30 1.888307e-30 [150,] 1.000000e+00 2.300597e-31 1.150299e-31 [151,] 1.000000e+00 9.277799e-31 4.638900e-31 [152,] 1.000000e+00 3.884927e-30 1.942463e-30 [153,] 1.000000e+00 1.688855e-29 8.444276e-30 [154,] 1.000000e+00 5.320782e-29 2.660391e-29 [155,] 1.000000e+00 1.387728e-28 6.938640e-29 [156,] 1.000000e+00 4.643508e-28 2.321754e-28 [157,] 1.000000e+00 1.154450e-27 5.772249e-28 [158,] 1.000000e+00 2.189934e-27 1.094967e-27 [159,] 1.000000e+00 2.935390e-27 1.467695e-27 [160,] 1.000000e+00 4.098257e-27 2.049128e-27 [161,] 1.000000e+00 3.550004e-27 1.775002e-27 [162,] 1.000000e+00 1.379771e-27 6.898853e-28 [163,] 1.000000e+00 3.762691e-27 1.881345e-27 [164,] 1.000000e+00 1.457145e-26 7.285727e-27 [165,] 1.000000e+00 5.732452e-26 2.866226e-26 [166,] 1.000000e+00 1.471009e-25 7.355047e-26 [167,] 1.000000e+00 5.411016e-25 2.705508e-25 [168,] 1.000000e+00 2.526268e-24 1.263134e-24 [169,] 1.000000e+00 1.130738e-23 5.653690e-24 [170,] 1.000000e+00 4.617544e-23 2.308772e-23 [171,] 1.000000e+00 2.098189e-22 1.049094e-22 [172,] 1.000000e+00 8.307579e-22 4.153789e-22 [173,] 1.000000e+00 3.373882e-21 1.686941e-21 [174,] 1.000000e+00 9.894004e-24 4.947002e-24 [175,] 1.000000e+00 5.428086e-23 2.714043e-23 [176,] 1.000000e+00 2.934891e-22 1.467446e-22 [177,] 1.000000e+00 1.596933e-21 7.984666e-22 [178,] 1.000000e+00 2.899811e-21 1.449905e-21 [179,] 1.000000e+00 1.973146e-20 9.865730e-21 [180,] 1.000000e+00 1.181975e-19 5.909877e-20 [181,] 1.000000e+00 8.066591e-19 4.033296e-19 [182,] 1.000000e+00 5.402230e-18 2.701115e-18 [183,] 1.000000e+00 3.641966e-17 1.820983e-17 [184,] 1.000000e+00 2.797131e-16 1.398566e-16 [185,] 1.000000e+00 2.198563e-15 1.099282e-15 [186,] 1.000000e+00 3.314901e-16 1.657450e-16 [187,] 1.000000e+00 2.720109e-15 1.360055e-15 [188,] 1.000000e+00 2.249731e-14 1.124866e-14 [189,] 1.000000e+00 1.743441e-13 8.717207e-14 [190,] 1.000000e+00 1.447160e-12 7.235798e-13 [191,] 1.000000e+00 1.040604e-11 5.203021e-12 [192,] 1.000000e+00 8.926847e-11 4.463423e-11 [193,] 1.000000e+00 7.332279e-10 3.666140e-10 [194,] 1.000000e+00 4.977276e-09 2.488638e-09 [195,] 1.000000e+00 2.900781e-08 1.450390e-08 [196,] 9.999999e-01 1.619390e-07 8.096950e-08 [197,] 9.999998e-01 3.867654e-07 1.933827e-07 [198,] 1.000000e+00 3.172889e-08 1.586444e-08 [199,] 9.999998e-01 4.871263e-07 2.435632e-07 [200,] 9.999962e-01 7.571150e-06 3.785575e-06 [201,] 9.999407e-01 1.186642e-04 5.933208e-05 [202,] 9.999776e-01 4.487866e-05 2.243933e-05 > postscript(file="/var/www/wessaorg/rcomp/tmp/1v78b1293642378.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/2v78b1293642378.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/35g7w1293642378.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/45g7w1293642378.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/55g7w1293642378.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 215 Frequency = 1 1 2 3 4 5 6 238057.8859 108107.3389 92800.2864 96892.4346 69235.8113 82153.2310 7 8 9 10 11 12 82228.6995 63294.6465 -66018.1038 -56586.8704 -56046.0343 16087.6602 13 14 15 16 17 18 -34604.5059 -39920.1751 -44721.6006 -37250.7664 -63139.9695 -41752.7560 19 20 21 22 23 24 -59923.4098 -63101.7952 -65429.5731 -64187.3082 -64836.8563 4005.7648 25 26 27 28 29 30 -50880.3722 -54195.1766 -69883.7874 -203839.9343 -224426.2419 -196168.7315 31 32 33 34 35 36 -196805.3140 -184094.1875 -254380.0510 -254886.8679 -250483.9502 -177074.3361 37 38 39 40 41 42 -228535.6424 -221675.2457 -207405.5378 -194513.7966 -220641.9158 -188712.7422 43 44 45 46 47 48 -201094.7889 -207802.3508 -201418.6695 -193017.2226 -187615.6587 -99956.2069 49 50 51 52 53 54 -160876.1941 -142134.4146 -134422.4336 -119122.8548 -149026.0631 -135926.4266 55 56 57 58 59 60 -145093.5515 -140278.5893 -135091.9151 -126732.8320 -90642.4630 -17067.5197 61 62 63 64 65 66 -80129.6716 -81373.7792 -73185.7946 -70896.7142 -78547.3712 -51379.1786 67 68 69 70 71 72 -57032.3495 -53553.6164 -77505.2397 -97629.8101 -92259.5650 -39665.9980 73 74 75 76 77 78 -104016.1848 -91742.7858 -86041.4950 -67818.3651 -85195.2304 -72781.0709 79 80 81 82 83 84 -75678.3553 -95267.7845 -111506.9705 -109655.7317 -109514.9871 12527.7074 85 86 87 88 89 90 -90561.3621 -81036.8762 -58413.4155 -64617.1778 -89772.6496 -77507.1162 91 92 93 94 95 96 -75975.1971 -82534.6396 -74576.9964 -63725.6888 -54695.0432 17357.4553 97 98 99 100 101 102 -29721.8354 -59993.9301 -53428.0874 -34211.1782 -60353.0814 -28196.2563 103 104 105 106 107 108 -36122.7521 -49068.2181 -73826.2502 -63533.9277 -50556.9356 35579.2325 109 110 111 112 113 114 -4121.3806 6459.2560 32951.0088 46367.5047 13225.8041 21904.8300 115 116 117 118 119 120 -572.4866 211.6464 4320.5032 15223.2592 17763.5410 93870.2614 121 122 123 124 125 126 24793.8021 32327.2433 42510.9672 48916.2104 31396.2011 41873.3368 127 128 129 130 131 132 40073.8540 38452.6460 24347.7770 18494.3774 17946.1696 75159.2651 133 134 135 136 137 138 18526.6840 19203.8829 23463.6841 36862.0435 26690.9241 27220.5706 139 140 141 142 143 144 27993.4748 29190.7801 27883.9855 31611.2306 32199.4300 79931.9349 145 146 147 148 149 150 31089.2848 31786.5049 49246.1525 67811.8777 41244.4486 47297.9810 151 152 153 154 155 156 56728.1762 48781.0526 48502.3426 57332.0702 65501.3051 123056.1818 157 158 159 160 161 162 72367.7367 77012.9720 78284.9598 89546.0399 56675.5102 71927.8776 163 164 165 166 167 168 125033.1667 127533.6478 124945.9508 130594.4736 128153.1240 180839.2797 169 170 171 172 173 174 140579.1256 202886.9229 198617.1386 215053.0911 197921.6619 209546.3695 175 176 177 178 179 180 205415.8781 189898.9489 190266.1352 194408.7497 188513.8057 245939.5177 181 182 183 184 185 186 185146.0907 186812.6918 174592.2624 184781.9627 173790.6716 191336.6522 187 188 189 190 191 192 190321.3699 193614.7874 183551.2326 135306.4937 123137.3297 121937.5214 193 194 195 196 197 198 71367.8668 76242.6559 86991.6225 105066.2056 73946.6760 73811.5390 199 200 201 202 203 204 62929.9479 61504.4950 51423.1991 50303.0825 51904.2488 100679.0917 205 206 207 208 209 210 66078.8592 67076.4784 70276.0000 92535.6047 68987.5688 72671.5699 211 212 213 214 215 64487.5583 56107.0830 54294.0011 59737.3290 62156.7863 > postscript(file="/var/www/wessaorg/rcomp/tmp/6g76h1293642378.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 215 Frequency = 1 lag(myerror, k = 1) myerror 0 238057.8859 NA 1 108107.3389 238057.8859 2 92800.2864 108107.3389 3 96892.4346 92800.2864 4 69235.8113 96892.4346 5 82153.2310 69235.8113 6 82228.6995 82153.2310 7 63294.6465 82228.6995 8 -66018.1038 63294.6465 9 -56586.8704 -66018.1038 10 -56046.0343 -56586.8704 11 16087.6602 -56046.0343 12 -34604.5059 16087.6602 13 -39920.1751 -34604.5059 14 -44721.6006 -39920.1751 15 -37250.7664 -44721.6006 16 -63139.9695 -37250.7664 17 -41752.7560 -63139.9695 18 -59923.4098 -41752.7560 19 -63101.7952 -59923.4098 20 -65429.5731 -63101.7952 21 -64187.3082 -65429.5731 22 -64836.8563 -64187.3082 23 4005.7648 -64836.8563 24 -50880.3722 4005.7648 25 -54195.1766 -50880.3722 26 -69883.7874 -54195.1766 27 -203839.9343 -69883.7874 28 -224426.2419 -203839.9343 29 -196168.7315 -224426.2419 30 -196805.3140 -196168.7315 31 -184094.1875 -196805.3140 32 -254380.0510 -184094.1875 33 -254886.8679 -254380.0510 34 -250483.9502 -254886.8679 35 -177074.3361 -250483.9502 36 -228535.6424 -177074.3361 37 -221675.2457 -228535.6424 38 -207405.5378 -221675.2457 39 -194513.7966 -207405.5378 40 -220641.9158 -194513.7966 41 -188712.7422 -220641.9158 42 -201094.7889 -188712.7422 43 -207802.3508 -201094.7889 44 -201418.6695 -207802.3508 45 -193017.2226 -201418.6695 46 -187615.6587 -193017.2226 47 -99956.2069 -187615.6587 48 -160876.1941 -99956.2069 49 -142134.4146 -160876.1941 50 -134422.4336 -142134.4146 51 -119122.8548 -134422.4336 52 -149026.0631 -119122.8548 53 -135926.4266 -149026.0631 54 -145093.5515 -135926.4266 55 -140278.5893 -145093.5515 56 -135091.9151 -140278.5893 57 -126732.8320 -135091.9151 58 -90642.4630 -126732.8320 59 -17067.5197 -90642.4630 60 -80129.6716 -17067.5197 61 -81373.7792 -80129.6716 62 -73185.7946 -81373.7792 63 -70896.7142 -73185.7946 64 -78547.3712 -70896.7142 65 -51379.1786 -78547.3712 66 -57032.3495 -51379.1786 67 -53553.6164 -57032.3495 68 -77505.2397 -53553.6164 69 -97629.8101 -77505.2397 70 -92259.5650 -97629.8101 71 -39665.9980 -92259.5650 72 -104016.1848 -39665.9980 73 -91742.7858 -104016.1848 74 -86041.4950 -91742.7858 75 -67818.3651 -86041.4950 76 -85195.2304 -67818.3651 77 -72781.0709 -85195.2304 78 -75678.3553 -72781.0709 79 -95267.7845 -75678.3553 80 -111506.9705 -95267.7845 81 -109655.7317 -111506.9705 82 -109514.9871 -109655.7317 83 12527.7074 -109514.9871 84 -90561.3621 12527.7074 85 -81036.8762 -90561.3621 86 -58413.4155 -81036.8762 87 -64617.1778 -58413.4155 88 -89772.6496 -64617.1778 89 -77507.1162 -89772.6496 90 -75975.1971 -77507.1162 91 -82534.6396 -75975.1971 92 -74576.9964 -82534.6396 93 -63725.6888 -74576.9964 94 -54695.0432 -63725.6888 95 17357.4553 -54695.0432 96 -29721.8354 17357.4553 97 -59993.9301 -29721.8354 98 -53428.0874 -59993.9301 99 -34211.1782 -53428.0874 100 -60353.0814 -34211.1782 101 -28196.2563 -60353.0814 102 -36122.7521 -28196.2563 103 -49068.2181 -36122.7521 104 -73826.2502 -49068.2181 105 -63533.9277 -73826.2502 106 -50556.9356 -63533.9277 107 35579.2325 -50556.9356 108 -4121.3806 35579.2325 109 6459.2560 -4121.3806 110 32951.0088 6459.2560 111 46367.5047 32951.0088 112 13225.8041 46367.5047 113 21904.8300 13225.8041 114 -572.4866 21904.8300 115 211.6464 -572.4866 116 4320.5032 211.6464 117 15223.2592 4320.5032 118 17763.5410 15223.2592 119 93870.2614 17763.5410 120 24793.8021 93870.2614 121 32327.2433 24793.8021 122 42510.9672 32327.2433 123 48916.2104 42510.9672 124 31396.2011 48916.2104 125 41873.3368 31396.2011 126 40073.8540 41873.3368 127 38452.6460 40073.8540 128 24347.7770 38452.6460 129 18494.3774 24347.7770 130 17946.1696 18494.3774 131 75159.2651 17946.1696 132 18526.6840 75159.2651 133 19203.8829 18526.6840 134 23463.6841 19203.8829 135 36862.0435 23463.6841 136 26690.9241 36862.0435 137 27220.5706 26690.9241 138 27993.4748 27220.5706 139 29190.7801 27993.4748 140 27883.9855 29190.7801 141 31611.2306 27883.9855 142 32199.4300 31611.2306 143 79931.9349 32199.4300 144 31089.2848 79931.9349 145 31786.5049 31089.2848 146 49246.1525 31786.5049 147 67811.8777 49246.1525 148 41244.4486 67811.8777 149 47297.9810 41244.4486 150 56728.1762 47297.9810 151 48781.0526 56728.1762 152 48502.3426 48781.0526 153 57332.0702 48502.3426 154 65501.3051 57332.0702 155 123056.1818 65501.3051 156 72367.7367 123056.1818 157 77012.9720 72367.7367 158 78284.9598 77012.9720 159 89546.0399 78284.9598 160 56675.5102 89546.0399 161 71927.8776 56675.5102 162 125033.1667 71927.8776 163 127533.6478 125033.1667 164 124945.9508 127533.6478 165 130594.4736 124945.9508 166 128153.1240 130594.4736 167 180839.2797 128153.1240 168 140579.1256 180839.2797 169 202886.9229 140579.1256 170 198617.1386 202886.9229 171 215053.0911 198617.1386 172 197921.6619 215053.0911 173 209546.3695 197921.6619 174 205415.8781 209546.3695 175 189898.9489 205415.8781 176 190266.1352 189898.9489 177 194408.7497 190266.1352 178 188513.8057 194408.7497 179 245939.5177 188513.8057 180 185146.0907 245939.5177 181 186812.6918 185146.0907 182 174592.2624 186812.6918 183 184781.9627 174592.2624 184 173790.6716 184781.9627 185 191336.6522 173790.6716 186 190321.3699 191336.6522 187 193614.7874 190321.3699 188 183551.2326 193614.7874 189 135306.4937 183551.2326 190 123137.3297 135306.4937 191 121937.5214 123137.3297 192 71367.8668 121937.5214 193 76242.6559 71367.8668 194 86991.6225 76242.6559 195 105066.2056 86991.6225 196 73946.6760 105066.2056 197 73811.5390 73946.6760 198 62929.9479 73811.5390 199 61504.4950 62929.9479 200 51423.1991 61504.4950 201 50303.0825 51423.1991 202 51904.2488 50303.0825 203 100679.0917 51904.2488 204 66078.8592 100679.0917 205 67076.4784 66078.8592 206 70276.0000 67076.4784 207 92535.6047 70276.0000 208 68987.5688 92535.6047 209 72671.5699 68987.5688 210 64487.5583 72671.5699 211 56107.0830 64487.5583 212 54294.0011 56107.0830 213 59737.3290 54294.0011 214 62156.7863 59737.3290 215 NA 62156.7863 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 108107.3389 238057.8859 [2,] 92800.2864 108107.3389 [3,] 96892.4346 92800.2864 [4,] 69235.8113 96892.4346 [5,] 82153.2310 69235.8113 [6,] 82228.6995 82153.2310 [7,] 63294.6465 82228.6995 [8,] -66018.1038 63294.6465 [9,] -56586.8704 -66018.1038 [10,] -56046.0343 -56586.8704 [11,] 16087.6602 -56046.0343 [12,] -34604.5059 16087.6602 [13,] -39920.1751 -34604.5059 [14,] -44721.6006 -39920.1751 [15,] -37250.7664 -44721.6006 [16,] -63139.9695 -37250.7664 [17,] -41752.7560 -63139.9695 [18,] -59923.4098 -41752.7560 [19,] -63101.7952 -59923.4098 [20,] -65429.5731 -63101.7952 [21,] -64187.3082 -65429.5731 [22,] -64836.8563 -64187.3082 [23,] 4005.7648 -64836.8563 [24,] -50880.3722 4005.7648 [25,] -54195.1766 -50880.3722 [26,] -69883.7874 -54195.1766 [27,] -203839.9343 -69883.7874 [28,] -224426.2419 -203839.9343 [29,] -196168.7315 -224426.2419 [30,] -196805.3140 -196168.7315 [31,] -184094.1875 -196805.3140 [32,] -254380.0510 -184094.1875 [33,] -254886.8679 -254380.0510 [34,] -250483.9502 -254886.8679 [35,] -177074.3361 -250483.9502 [36,] -228535.6424 -177074.3361 [37,] -221675.2457 -228535.6424 [38,] -207405.5378 -221675.2457 [39,] -194513.7966 -207405.5378 [40,] -220641.9158 -194513.7966 [41,] -188712.7422 -220641.9158 [42,] -201094.7889 -188712.7422 [43,] -207802.3508 -201094.7889 [44,] -201418.6695 -207802.3508 [45,] -193017.2226 -201418.6695 [46,] -187615.6587 -193017.2226 [47,] -99956.2069 -187615.6587 [48,] -160876.1941 -99956.2069 [49,] -142134.4146 -160876.1941 [50,] -134422.4336 -142134.4146 [51,] -119122.8548 -134422.4336 [52,] -149026.0631 -119122.8548 [53,] -135926.4266 -149026.0631 [54,] -145093.5515 -135926.4266 [55,] -140278.5893 -145093.5515 [56,] -135091.9151 -140278.5893 [57,] -126732.8320 -135091.9151 [58,] -90642.4630 -126732.8320 [59,] -17067.5197 -90642.4630 [60,] -80129.6716 -17067.5197 [61,] -81373.7792 -80129.6716 [62,] -73185.7946 -81373.7792 [63,] -70896.7142 -73185.7946 [64,] -78547.3712 -70896.7142 [65,] -51379.1786 -78547.3712 [66,] -57032.3495 -51379.1786 [67,] -53553.6164 -57032.3495 [68,] -77505.2397 -53553.6164 [69,] -97629.8101 -77505.2397 [70,] -92259.5650 -97629.8101 [71,] -39665.9980 -92259.5650 [72,] -104016.1848 -39665.9980 [73,] -91742.7858 -104016.1848 [74,] -86041.4950 -91742.7858 [75,] -67818.3651 -86041.4950 [76,] -85195.2304 -67818.3651 [77,] -72781.0709 -85195.2304 [78,] -75678.3553 -72781.0709 [79,] -95267.7845 -75678.3553 [80,] -111506.9705 -95267.7845 [81,] -109655.7317 -111506.9705 [82,] -109514.9871 -109655.7317 [83,] 12527.7074 -109514.9871 [84,] -90561.3621 12527.7074 [85,] -81036.8762 -90561.3621 [86,] -58413.4155 -81036.8762 [87,] -64617.1778 -58413.4155 [88,] -89772.6496 -64617.1778 [89,] -77507.1162 -89772.6496 [90,] -75975.1971 -77507.1162 [91,] -82534.6396 -75975.1971 [92,] -74576.9964 -82534.6396 [93,] -63725.6888 -74576.9964 [94,] -54695.0432 -63725.6888 [95,] 17357.4553 -54695.0432 [96,] -29721.8354 17357.4553 [97,] -59993.9301 -29721.8354 [98,] -53428.0874 -59993.9301 [99,] -34211.1782 -53428.0874 [100,] -60353.0814 -34211.1782 [101,] -28196.2563 -60353.0814 [102,] -36122.7521 -28196.2563 [103,] -49068.2181 -36122.7521 [104,] -73826.2502 -49068.2181 [105,] -63533.9277 -73826.2502 [106,] -50556.9356 -63533.9277 [107,] 35579.2325 -50556.9356 [108,] -4121.3806 35579.2325 [109,] 6459.2560 -4121.3806 [110,] 32951.0088 6459.2560 [111,] 46367.5047 32951.0088 [112,] 13225.8041 46367.5047 [113,] 21904.8300 13225.8041 [114,] -572.4866 21904.8300 [115,] 211.6464 -572.4866 [116,] 4320.5032 211.6464 [117,] 15223.2592 4320.5032 [118,] 17763.5410 15223.2592 [119,] 93870.2614 17763.5410 [120,] 24793.8021 93870.2614 [121,] 32327.2433 24793.8021 [122,] 42510.9672 32327.2433 [123,] 48916.2104 42510.9672 [124,] 31396.2011 48916.2104 [125,] 41873.3368 31396.2011 [126,] 40073.8540 41873.3368 [127,] 38452.6460 40073.8540 [128,] 24347.7770 38452.6460 [129,] 18494.3774 24347.7770 [130,] 17946.1696 18494.3774 [131,] 75159.2651 17946.1696 [132,] 18526.6840 75159.2651 [133,] 19203.8829 18526.6840 [134,] 23463.6841 19203.8829 [135,] 36862.0435 23463.6841 [136,] 26690.9241 36862.0435 [137,] 27220.5706 26690.9241 [138,] 27993.4748 27220.5706 [139,] 29190.7801 27993.4748 [140,] 27883.9855 29190.7801 [141,] 31611.2306 27883.9855 [142,] 32199.4300 31611.2306 [143,] 79931.9349 32199.4300 [144,] 31089.2848 79931.9349 [145,] 31786.5049 31089.2848 [146,] 49246.1525 31786.5049 [147,] 67811.8777 49246.1525 [148,] 41244.4486 67811.8777 [149,] 47297.9810 41244.4486 [150,] 56728.1762 47297.9810 [151,] 48781.0526 56728.1762 [152,] 48502.3426 48781.0526 [153,] 57332.0702 48502.3426 [154,] 65501.3051 57332.0702 [155,] 123056.1818 65501.3051 [156,] 72367.7367 123056.1818 [157,] 77012.9720 72367.7367 [158,] 78284.9598 77012.9720 [159,] 89546.0399 78284.9598 [160,] 56675.5102 89546.0399 [161,] 71927.8776 56675.5102 [162,] 125033.1667 71927.8776 [163,] 127533.6478 125033.1667 [164,] 124945.9508 127533.6478 [165,] 130594.4736 124945.9508 [166,] 128153.1240 130594.4736 [167,] 180839.2797 128153.1240 [168,] 140579.1256 180839.2797 [169,] 202886.9229 140579.1256 [170,] 198617.1386 202886.9229 [171,] 215053.0911 198617.1386 [172,] 197921.6619 215053.0911 [173,] 209546.3695 197921.6619 [174,] 205415.8781 209546.3695 [175,] 189898.9489 205415.8781 [176,] 190266.1352 189898.9489 [177,] 194408.7497 190266.1352 [178,] 188513.8057 194408.7497 [179,] 245939.5177 188513.8057 [180,] 185146.0907 245939.5177 [181,] 186812.6918 185146.0907 [182,] 174592.2624 186812.6918 [183,] 184781.9627 174592.2624 [184,] 173790.6716 184781.9627 [185,] 191336.6522 173790.6716 [186,] 190321.3699 191336.6522 [187,] 193614.7874 190321.3699 [188,] 183551.2326 193614.7874 [189,] 135306.4937 183551.2326 [190,] 123137.3297 135306.4937 [191,] 121937.5214 123137.3297 [192,] 71367.8668 121937.5214 [193,] 76242.6559 71367.8668 [194,] 86991.6225 76242.6559 [195,] 105066.2056 86991.6225 [196,] 73946.6760 105066.2056 [197,] 73811.5390 73946.6760 [198,] 62929.9479 73811.5390 [199,] 61504.4950 62929.9479 [200,] 51423.1991 61504.4950 [201,] 50303.0825 51423.1991 [202,] 51904.2488 50303.0825 [203,] 100679.0917 51904.2488 [204,] 66078.8592 100679.0917 [205,] 67076.4784 66078.8592 [206,] 70276.0000 67076.4784 [207,] 92535.6047 70276.0000 [208,] 68987.5688 92535.6047 [209,] 72671.5699 68987.5688 [210,] 64487.5583 72671.5699 [211,] 56107.0830 64487.5583 [212,] 54294.0011 56107.0830 [213,] 59737.3290 54294.0011 [214,] 62156.7863 59737.3290 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 108107.3389 238057.8859 2 92800.2864 108107.3389 3 96892.4346 92800.2864 4 69235.8113 96892.4346 5 82153.2310 69235.8113 6 82228.6995 82153.2310 7 63294.6465 82228.6995 8 -66018.1038 63294.6465 9 -56586.8704 -66018.1038 10 -56046.0343 -56586.8704 11 16087.6602 -56046.0343 12 -34604.5059 16087.6602 13 -39920.1751 -34604.5059 14 -44721.6006 -39920.1751 15 -37250.7664 -44721.6006 16 -63139.9695 -37250.7664 17 -41752.7560 -63139.9695 18 -59923.4098 -41752.7560 19 -63101.7952 -59923.4098 20 -65429.5731 -63101.7952 21 -64187.3082 -65429.5731 22 -64836.8563 -64187.3082 23 4005.7648 -64836.8563 24 -50880.3722 4005.7648 25 -54195.1766 -50880.3722 26 -69883.7874 -54195.1766 27 -203839.9343 -69883.7874 28 -224426.2419 -203839.9343 29 -196168.7315 -224426.2419 30 -196805.3140 -196168.7315 31 -184094.1875 -196805.3140 32 -254380.0510 -184094.1875 33 -254886.8679 -254380.0510 34 -250483.9502 -254886.8679 35 -177074.3361 -250483.9502 36 -228535.6424 -177074.3361 37 -221675.2457 -228535.6424 38 -207405.5378 -221675.2457 39 -194513.7966 -207405.5378 40 -220641.9158 -194513.7966 41 -188712.7422 -220641.9158 42 -201094.7889 -188712.7422 43 -207802.3508 -201094.7889 44 -201418.6695 -207802.3508 45 -193017.2226 -201418.6695 46 -187615.6587 -193017.2226 47 -99956.2069 -187615.6587 48 -160876.1941 -99956.2069 49 -142134.4146 -160876.1941 50 -134422.4336 -142134.4146 51 -119122.8548 -134422.4336 52 -149026.0631 -119122.8548 53 -135926.4266 -149026.0631 54 -145093.5515 -135926.4266 55 -140278.5893 -145093.5515 56 -135091.9151 -140278.5893 57 -126732.8320 -135091.9151 58 -90642.4630 -126732.8320 59 -17067.5197 -90642.4630 60 -80129.6716 -17067.5197 61 -81373.7792 -80129.6716 62 -73185.7946 -81373.7792 63 -70896.7142 -73185.7946 64 -78547.3712 -70896.7142 65 -51379.1786 -78547.3712 66 -57032.3495 -51379.1786 67 -53553.6164 -57032.3495 68 -77505.2397 -53553.6164 69 -97629.8101 -77505.2397 70 -92259.5650 -97629.8101 71 -39665.9980 -92259.5650 72 -104016.1848 -39665.9980 73 -91742.7858 -104016.1848 74 -86041.4950 -91742.7858 75 -67818.3651 -86041.4950 76 -85195.2304 -67818.3651 77 -72781.0709 -85195.2304 78 -75678.3553 -72781.0709 79 -95267.7845 -75678.3553 80 -111506.9705 -95267.7845 81 -109655.7317 -111506.9705 82 -109514.9871 -109655.7317 83 12527.7074 -109514.9871 84 -90561.3621 12527.7074 85 -81036.8762 -90561.3621 86 -58413.4155 -81036.8762 87 -64617.1778 -58413.4155 88 -89772.6496 -64617.1778 89 -77507.1162 -89772.6496 90 -75975.1971 -77507.1162 91 -82534.6396 -75975.1971 92 -74576.9964 -82534.6396 93 -63725.6888 -74576.9964 94 -54695.0432 -63725.6888 95 17357.4553 -54695.0432 96 -29721.8354 17357.4553 97 -59993.9301 -29721.8354 98 -53428.0874 -59993.9301 99 -34211.1782 -53428.0874 100 -60353.0814 -34211.1782 101 -28196.2563 -60353.0814 102 -36122.7521 -28196.2563 103 -49068.2181 -36122.7521 104 -73826.2502 -49068.2181 105 -63533.9277 -73826.2502 106 -50556.9356 -63533.9277 107 35579.2325 -50556.9356 108 -4121.3806 35579.2325 109 6459.2560 -4121.3806 110 32951.0088 6459.2560 111 46367.5047 32951.0088 112 13225.8041 46367.5047 113 21904.8300 13225.8041 114 -572.4866 21904.8300 115 211.6464 -572.4866 116 4320.5032 211.6464 117 15223.2592 4320.5032 118 17763.5410 15223.2592 119 93870.2614 17763.5410 120 24793.8021 93870.2614 121 32327.2433 24793.8021 122 42510.9672 32327.2433 123 48916.2104 42510.9672 124 31396.2011 48916.2104 125 41873.3368 31396.2011 126 40073.8540 41873.3368 127 38452.6460 40073.8540 128 24347.7770 38452.6460 129 18494.3774 24347.7770 130 17946.1696 18494.3774 131 75159.2651 17946.1696 132 18526.6840 75159.2651 133 19203.8829 18526.6840 134 23463.6841 19203.8829 135 36862.0435 23463.6841 136 26690.9241 36862.0435 137 27220.5706 26690.9241 138 27993.4748 27220.5706 139 29190.7801 27993.4748 140 27883.9855 29190.7801 141 31611.2306 27883.9855 142 32199.4300 31611.2306 143 79931.9349 32199.4300 144 31089.2848 79931.9349 145 31786.5049 31089.2848 146 49246.1525 31786.5049 147 67811.8777 49246.1525 148 41244.4486 67811.8777 149 47297.9810 41244.4486 150 56728.1762 47297.9810 151 48781.0526 56728.1762 152 48502.3426 48781.0526 153 57332.0702 48502.3426 154 65501.3051 57332.0702 155 123056.1818 65501.3051 156 72367.7367 123056.1818 157 77012.9720 72367.7367 158 78284.9598 77012.9720 159 89546.0399 78284.9598 160 56675.5102 89546.0399 161 71927.8776 56675.5102 162 125033.1667 71927.8776 163 127533.6478 125033.1667 164 124945.9508 127533.6478 165 130594.4736 124945.9508 166 128153.1240 130594.4736 167 180839.2797 128153.1240 168 140579.1256 180839.2797 169 202886.9229 140579.1256 170 198617.1386 202886.9229 171 215053.0911 198617.1386 172 197921.6619 215053.0911 173 209546.3695 197921.6619 174 205415.8781 209546.3695 175 189898.9489 205415.8781 176 190266.1352 189898.9489 177 194408.7497 190266.1352 178 188513.8057 194408.7497 179 245939.5177 188513.8057 180 185146.0907 245939.5177 181 186812.6918 185146.0907 182 174592.2624 186812.6918 183 184781.9627 174592.2624 184 173790.6716 184781.9627 185 191336.6522 173790.6716 186 190321.3699 191336.6522 187 193614.7874 190321.3699 188 183551.2326 193614.7874 189 135306.4937 183551.2326 190 123137.3297 135306.4937 191 121937.5214 123137.3297 192 71367.8668 121937.5214 193 76242.6559 71367.8668 194 86991.6225 76242.6559 195 105066.2056 86991.6225 196 73946.6760 105066.2056 197 73811.5390 73946.6760 198 62929.9479 73811.5390 199 61504.4950 62929.9479 200 51423.1991 61504.4950 201 50303.0825 51423.1991 202 51904.2488 50303.0825 203 100679.0917 51904.2488 204 66078.8592 100679.0917 205 67076.4784 66078.8592 206 70276.0000 67076.4784 207 92535.6047 70276.0000 208 68987.5688 92535.6047 209 72671.5699 68987.5688 210 64487.5583 72671.5699 211 56107.0830 64487.5583 212 54294.0011 56107.0830 213 59737.3290 54294.0011 214 62156.7863 59737.3290 > 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/wessaorg/rcomp/tmp/7w2v81293642378.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/8w2v81293642378.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/wessaorg/rcomp/tmp/9w2v81293642378.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/wessaorg/rcomp/tmp/107buc1293642378.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/wessaorg/rcomp/tmp/11n8lb1293642378.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/wessaorg/rcomp/tmp/128rkh1293642378.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/wessaorg/rcomp/tmp/13xazs1293642378.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/wessaorg/rcomp/tmp/148jyv1293642378.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/wessaorg/rcomp/tmp/15tke11293642378.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/wessaorg/rcomp/tmp/16pccs1293642378.tab") + } > > try(system("convert tmp/1v78b1293642378.ps tmp/1v78b1293642378.png",intern=TRUE)) character(0) > try(system("convert tmp/2v78b1293642378.ps tmp/2v78b1293642378.png",intern=TRUE)) character(0) > try(system("convert tmp/35g7w1293642378.ps tmp/35g7w1293642378.png",intern=TRUE)) character(0) > try(system("convert tmp/45g7w1293642378.ps tmp/45g7w1293642378.png",intern=TRUE)) character(0) > try(system("convert tmp/55g7w1293642378.ps tmp/55g7w1293642378.png",intern=TRUE)) character(0) > try(system("convert tmp/6g76h1293642378.ps tmp/6g76h1293642378.png",intern=TRUE)) character(0) > try(system("convert tmp/7w2v81293642378.ps tmp/7w2v81293642378.png",intern=TRUE)) character(0) > try(system("convert tmp/8w2v81293642378.ps tmp/8w2v81293642378.png",intern=TRUE)) character(0) > try(system("convert tmp/9w2v81293642378.ps tmp/9w2v81293642378.png",intern=TRUE)) character(0) > try(system("convert tmp/107buc1293642378.ps tmp/107buc1293642378.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 6.67 0.36 7.22