R version 2.13.0 (2011-04-13) Copyright (C) 2011 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i486-pc-linux-gnu (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(1845 + ,162687 + ,95 + ,48 + ,21 + ,20465 + ,0 + ,1796 + ,201906 + ,62 + ,58 + ,20 + ,33629 + ,1 + ,192 + ,7215 + ,18 + ,0 + ,0 + ,1423 + ,0 + ,2444 + ,146367 + ,97 + ,67 + ,27 + ,25629 + ,0 + ,3567 + ,257045 + ,139 + ,83 + ,31 + ,54002 + ,0 + ,6917 + ,524450 + ,265 + ,136 + ,36 + ,151036 + ,1 + ,1840 + ,188294 + ,58 + ,65 + ,23 + ,33287 + ,1 + ,1740 + ,195674 + ,60 + ,86 + ,30 + ,31172 + ,0 + ,2078 + ,177020 + ,44 + ,62 + ,30 + ,28113 + ,0 + ,3097 + ,325899 + ,98 + ,71 + ,27 + ,57803 + ,1 + ,1946 + ,121844 + ,75 + ,50 + ,24 + ,49830 + ,2 + ,2370 + ,203938 + ,72 + ,88 + ,30 + ,52143 + ,0 + ,1883 + ,107394 + ,105 + ,50 + ,22 + ,21055 + ,0 + ,3198 + ,220751 + ,120 + ,79 + ,28 + ,47007 + ,4 + ,1490 + ,172905 + ,62 + ,56 + ,18 + ,28735 + ,4 + ,1573 + ,156326 + ,88 + ,54 + ,22 + ,59147 + ,3 + ,1807 + ,145178 + ,58 + ,81 + ,37 + ,78950 + ,0 + ,1309 + ,89171 + ,61 + ,13 + ,15 + ,13497 + ,5 + ,2820 + ,172624 + ,88 + ,74 + ,34 + ,46154 + ,0 + ,757 + 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,53 + ,53 + ,22 + ,39644 + ,0 + ,1248 + ,111408 + ,20 + ,17 + ,22 + ,23494 + ,1) + ,dim=c(7 + ,144) + ,dimnames=list(c('Pageviews' + ,'Time_in_RFC' + ,'#Logins' + ,'blogs' + ,'reviews' + ,'Characters' + ,'Shared') + ,1:144)) > y <- array(NA,dim=c(7,144),dimnames=list(c('Pageviews','Time_in_RFC','#Logins','blogs','reviews','Characters','Shared'),1:144)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par20 = '' > par19 = '' > par18 = '' > par17 = '' > par16 = '' > par15 = '' > par14 = '' > par13 = '' > par12 = '' > par11 = '' > par10 = '' > par9 = '' > par8 = '' > par7 = '' > par6 = '' > par5 = '' > par4 = '' > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '2' > 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 Time_in_RFC Pageviews #Logins blogs reviews Characters Shared 1 162687 1845 95 48 21 20465 0 2 201906 1796 62 58 20 33629 1 3 7215 192 18 0 0 1423 0 4 146367 2444 97 67 27 25629 0 5 257045 3567 139 83 31 54002 0 6 524450 6917 265 136 36 151036 1 7 188294 1840 58 65 23 33287 1 8 195674 1740 60 86 30 31172 0 9 177020 2078 44 62 30 28113 0 10 325899 3097 98 71 27 57803 1 11 121844 1946 75 50 24 49830 2 12 203938 2370 72 88 30 52143 0 13 107394 1883 105 50 22 21055 0 14 220751 3198 120 79 28 47007 4 15 172905 1490 62 56 18 28735 4 16 156326 1573 88 54 22 59147 3 17 145178 1807 58 81 37 78950 0 18 89171 1309 61 13 15 13497 5 19 172624 2820 88 74 34 46154 0 20 32443 757 26 14 18 53249 0 21 87927 1162 62 31 15 10726 0 22 241285 2818 103 99 30 83700 0 23 195820 1760 72 38 25 40400 1 24 146946 2315 56 59 34 33797 1 25 159763 1994 89 54 21 36205 1 26 207078 1806 34 63 21 30165 0 27 212394 2152 166 66 25 58534 0 28 201536 1457 95 90 31 44663 0 29 394662 3000 121 72 31 92556 0 30 217892 2236 46 61 20 40078 0 31 182286 1684 44 61 28 34711 0 32 181740 1626 47 61 22 31076 2 33 137978 2257 107 53 17 74608 4 34 255929 3373 130 118 25 58092 0 35 236489 2571 55 73 25 42009 1 36 0 1 1 0 0 0 0 37 230761 2142 64 54 31 36022 0 38 132807 1878 54 54 14 23333 3 39 157118 2190 49 46 35 53349 9 40 253254 2186 68 83 34 92596 0 41 269329 2532 71 106 22 49598 2 42 161273 1823 61 44 34 44093 0 43 107181 1095 33 27 23 84205 2 44 195891 2162 79 64 24 63369 1 45 139667 1365 51 71 26 60132 2 46 171101 1244 98 44 23 37403 2 47 81407 756 33 23 35 24460 1 48 247563 2417 104 78 24 46456 0 49 239807 2327 90 60 31 66616 1 50 172743 2786 59 73 30 41554 8 51 48188 658 28 12 22 22346 0 52 169355 2012 70 104 23 30874 0 53 315622 2602 76 83 27 68701 0 54 241518 2071 79 57 30 35728 0 55 195583 1911 59 67 33 29010 1 56 159913 1775 57 44 12 23110 8 57 220241 1918 69 53 26 38844 0 58 101694 1046 25 26 26 27084 1 59 157258 1190 68 67 23 35139 0 60 202536 2890 99 36 38 57476 10 61 173505 1836 64 56 32 33277 6 62 150518 2254 83 52 21 31141 0 63 141491 1392 64 54 22 61281 11 64 125612 1325 38 57 26 25820 3 65 166049 1317 36 27 28 23284 0 66 124197 1525 42 58 33 35378 0 67 195043 2335 71 76 36 74990 8 68 138708 2897 65 93 25 29653 2 69 116552 1118 40 59 25 64622 0 70 31970 340 15 5 21 4157 0 71 258158 2977 115 57 19 29245 3 72 151184 1449 78 42 12 50008 1 73 135926 1550 68 88 30 52338 2 74 119629 1684 72 53 21 13310 1 75 171518 2728 71 81 39 92901 0 76 108949 1574 45 35 32 10956 2 77 183471 2413 60 102 28 34241 1 78 159966 2563 98 71 29 75043 0 79 93786 1079 34 28 21 21152 0 80 84971 1235 72 34 31 42249 0 81 88882 980 76 54 26 42005 0 82 304603 2246 65 49 29 41152 0 83 75101 1076 30 30 23 14399 1 84 145043 1637 40 57 25 28263 0 85 95827 1208 48 54 22 17215 0 86 173924 1865 58 38 26 48140 0 87 241957 2726 237 63 33 62897 0 88 115367 1208 115 58 24 22883 0 89 118408 1419 64 46 24 41622 7 90 164078 1609 53 46 21 40715 0 91 158931 1864 41 51 28 65897 5 92 184139 2412 82 87 28 76542 1 93 152856 1238 58 39 25 37477 0 94 144014 1462 59 28 15 53216 0 95 62535 973 42 26 13 40911 0 96 245196 2319 117 52 36 57021 0 97 199841 1890 71 96 27 73116 0 98 19349 223 12 13 1 3895 0 99 247280 2526 108 43 24 46609 3 100 159408 2072 83 42 31 29351 0 101 72128 778 30 30 4 2325 0 102 104253 1194 26 59 21 31747 0 103 151090 1424 57 73 27 32665 0 104 137382 1327 65 39 23 19249 1 105 87448 839 42 36 12 15292 1 106 27676 596 22 2 16 5842 0 107 165507 1671 50 102 29 33994 0 108 132148 1167 37 30 26 13018 1 109 0 0 0 0 0 0 0 110 95778 1106 34 46 25 98177 0 111 109001 1148 67 25 21 37941 0 112 158833 1485 46 59 24 31032 0 113 147690 1526 63 60 21 32683 1 114 89887 962 63 36 21 34545 0 115 3616 78 5 0 0 0 0 116 0 0 0 0 0 0 0 117 199005 1184 45 45 23 27525 0 118 160930 1671 92 79 33 66856 0 119 177948 2142 102 30 32 28549 2 120 136061 1015 39 43 23 38610 0 121 43410 778 19 7 1 2781 0 122 184277 1856 74 80 29 41211 1 123 108858 1056 43 32 20 22698 0 124 141744 2234 58 81 33 41194 8 125 60493 731 40 3 12 32689 3 126 19764 285 12 10 2 5752 1 127 177559 1872 56 47 21 26757 3 128 140281 1181 35 35 28 22527 0 129 164249 1725 54 54 35 44810 0 130 11796 256 9 1 2 0 0 131 10674 98 9 0 0 0 0 132 151322 1435 59 46 18 100674 0 133 6836 41 3 0 1 0 0 134 174712 1930 67 51 21 57786 6 135 5118 42 3 5 0 0 0 136 40248 528 16 8 4 5444 1 137 0 0 0 0 0 0 0 138 127628 1121 50 38 29 28470 0 139 88837 1305 38 21 26 61849 0 140 7131 81 4 0 0 0 1 141 9056 262 15 0 4 2179 0 142 87957 1099 26 18 19 8019 1 143 144470 1290 53 53 22 39644 0 144 111408 1248 20 17 22 23494 1 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Pageviews `#Logins` blogs reviews Characters 5684.3637 58.8282 133.8772 337.1295 655.3391 0.2386 Shared -2669.1603 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -95576 -18035 -3196 21711 129623 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 5684.3637 7487.2776 0.759 0.4490 Pageviews 58.8282 7.5912 7.750 1.86e-12 *** `#Logins` 133.8772 134.4994 0.995 0.3213 blogs 337.1295 183.8764 1.833 0.0689 . reviews 655.3391 442.2489 1.482 0.1407 Characters 0.2386 0.1701 1.403 0.1630 Shared -2669.1603 1375.2007 -1.941 0.0543 . --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 34850 on 137 degrees of freedom Multiple R-squared: 0.8224, Adjusted R-squared: 0.8147 F-statistic: 105.8 on 6 and 137 DF, p-value: < 2.2e-16 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 0.3021709 6.043417e-01 6.978291e-01 [2,] 0.9115200 1.769600e-01 8.847999e-02 [3,] 0.8601633 2.796733e-01 1.398367e-01 [4,] 0.7971777 4.056445e-01 2.028223e-01 [5,] 0.8388912 3.222176e-01 1.611088e-01 [6,] 0.8192219 3.615563e-01 1.807781e-01 [7,] 0.7705606 4.588788e-01 2.294394e-01 [8,] 0.7494289 5.011421e-01 2.505711e-01 [9,] 0.6760047 6.479905e-01 3.239953e-01 [10,] 0.6970804 6.058392e-01 3.029196e-01 [11,] 0.6395245 7.209510e-01 3.604755e-01 [12,] 0.5655640 8.688720e-01 4.344360e-01 [13,] 0.5269057 9.461885e-01 4.730943e-01 [14,] 0.8057859 3.884282e-01 1.942141e-01 [15,] 0.7948877 4.102246e-01 2.051123e-01 [16,] 0.7433825 5.132349e-01 2.566175e-01 [17,] 0.7144103 5.711794e-01 2.855897e-01 [18,] 0.7776571 4.446859e-01 2.223429e-01 [19,] 0.7677202 4.645597e-01 2.322798e-01 [20,] 0.9979599 4.080118e-03 2.040059e-03 [21,] 0.9972123 5.575355e-03 2.787677e-03 [22,] 0.9965310 6.937921e-03 3.468961e-03 [23,] 0.9957175 8.565067e-03 4.282534e-03 [24,] 0.9982446 3.510745e-03 1.755372e-03 [25,] 0.9988213 2.357396e-03 1.178698e-03 [26,] 0.9983062 3.387698e-03 1.693849e-03 [27,] 0.9975393 4.921331e-03 2.460666e-03 [28,] 0.9981380 3.724057e-03 1.862028e-03 [29,] 0.9974219 5.156193e-03 2.578096e-03 [30,] 0.9961528 7.694328e-03 3.847164e-03 [31,] 0.9955030 8.994094e-03 4.497047e-03 [32,] 0.9957009 8.598220e-03 4.299110e-03 [33,] 0.9937057 1.258865e-02 6.294323e-03 [34,] 0.9916128 1.677443e-02 8.387215e-03 [35,] 0.9880624 2.387514e-02 1.193757e-02 [36,] 0.9844161 3.116789e-02 1.558395e-02 [37,] 0.9884914 2.301720e-02 1.150860e-02 [38,] 0.9839290 3.214191e-02 1.607096e-02 [39,] 0.9823272 3.534557e-02 1.767279e-02 [40,] 0.9810278 3.794448e-02 1.897224e-02 [41,] 0.9806780 3.864392e-02 1.932196e-02 [42,] 0.9765725 4.685492e-02 2.342746e-02 [43,] 0.9745899 5.082026e-02 2.541013e-02 [44,] 0.9939709 1.205828e-02 6.029139e-03 [45,] 0.9968515 6.297007e-03 3.148504e-03 [46,] 0.9960627 7.874561e-03 3.937281e-03 [47,] 0.9963336 7.332781e-03 3.666391e-03 [48,] 0.9975661 4.867773e-03 2.433887e-03 [49,] 0.9964243 7.151432e-03 3.575716e-03 [50,] 0.9959025 8.195055e-03 4.097528e-03 [51,] 0.9950192 9.961611e-03 4.980805e-03 [52,] 0.9935020 1.299591e-02 6.497956e-03 [53,] 0.9934623 1.307537e-02 6.537684e-03 [54,] 0.9921520 1.569607e-02 7.848035e-03 [55,] 0.9892610 2.147807e-02 1.073904e-02 [56,] 0.9915028 1.699437e-02 8.497187e-03 [57,] 0.9903358 1.932841e-02 9.664207e-03 [58,] 0.9870754 2.584912e-02 1.292456e-02 [59,] 0.9990442 1.911651e-03 9.558254e-04 [60,] 0.9987870 2.425989e-03 1.212994e-03 [61,] 0.9982419 3.516200e-03 1.758100e-03 [62,] 0.9979790 4.041917e-03 2.020959e-03 [63,] 0.9974341 5.131788e-03 2.565894e-03 [64,] 0.9968848 6.230426e-03 3.115213e-03 [65,] 0.9966190 6.762037e-03 3.381018e-03 [66,] 0.9995247 9.506760e-04 4.753380e-04 [67,] 0.9995176 9.648070e-04 4.824035e-04 [68,] 0.9996107 7.785601e-04 3.892801e-04 [69,] 0.9999778 4.432341e-05 2.216170e-05 [70,] 0.9999643 7.134187e-05 3.567094e-05 [71,] 0.9999733 5.337287e-05 2.668643e-05 [72,] 0.9999621 7.588934e-05 3.794467e-05 [73,] 0.9999999 1.933771e-07 9.668853e-08 [74,] 0.9999999 2.125443e-07 1.062721e-07 [75,] 0.9999998 3.863390e-07 1.931695e-07 [76,] 0.9999998 4.100076e-07 2.050038e-07 [77,] 0.9999996 8.298483e-07 4.149242e-07 [78,] 0.9999994 1.150256e-06 5.751282e-07 [79,] 0.9999994 1.133515e-06 5.667574e-07 [80,] 0.9999989 2.275456e-06 1.137728e-06 [81,] 0.9999981 3.762227e-06 1.881114e-06 [82,] 0.9999968 6.333117e-06 3.166558e-06 [83,] 0.9999985 2.957682e-06 1.478841e-06 [84,] 0.9999983 3.337167e-06 1.668583e-06 [85,] 0.9999969 6.259992e-06 3.129996e-06 [86,] 0.9999976 4.888172e-06 2.444086e-06 [87,] 0.9999963 7.304605e-06 3.652302e-06 [88,] 0.9999927 1.452175e-05 7.260876e-06 [89,] 0.9999863 2.748985e-05 1.374493e-05 [90,] 0.9999906 1.886651e-05 9.433253e-06 [91,] 0.9999930 1.396790e-05 6.983949e-06 [92,] 0.9999861 2.771870e-05 1.385935e-05 [93,] 0.9999802 3.966708e-05 1.983354e-05 [94,] 0.9999621 7.573040e-05 3.786520e-05 [95,] 0.9999309 1.381407e-04 6.907033e-05 [96,] 0.9998704 2.592450e-04 1.296225e-04 [97,] 0.9998853 2.293905e-04 1.146953e-04 [98,] 0.9998653 2.694211e-04 1.347105e-04 [99,] 0.9998117 3.766132e-04 1.883066e-04 [100,] 0.9996475 7.050303e-04 3.525151e-04 [101,] 0.9995644 8.712403e-04 4.356201e-04 [102,] 0.9992003 1.599308e-03 7.996542e-04 [103,] 0.9985777 2.844506e-03 1.422253e-03 [104,] 0.9975283 4.943387e-03 2.471694e-03 [105,] 0.9964553 7.089500e-03 3.544750e-03 [106,] 0.9940347 1.193063e-02 5.965317e-03 [107,] 0.9900716 1.985682e-02 9.928411e-03 [108,] 0.9998331 3.337868e-04 1.668934e-04 [109,] 0.9998977 2.046903e-04 1.023451e-04 [110,] 0.9998735 2.530463e-04 1.265231e-04 [111,] 0.9999065 1.869955e-04 9.349775e-05 [112,] 0.9999277 1.446185e-04 7.230924e-05 [113,] 0.9998887 2.225647e-04 1.112824e-04 [114,] 0.9997445 5.109291e-04 2.554646e-04 [115,] 0.9999897 2.069489e-05 1.034744e-05 [116,] 0.9999816 3.685919e-05 1.842959e-05 [117,] 0.9999595 8.102225e-05 4.051112e-05 [118,] 0.9998884 2.231033e-04 1.115517e-04 [119,] 0.9999089 1.822239e-04 9.111195e-05 [120,] 0.9998504 2.992659e-04 1.496330e-04 [121,] 0.9994131 1.173760e-03 5.868798e-04 [122,] 0.9982252 3.549595e-03 1.774798e-03 [123,] 0.9995240 9.520681e-04 4.760340e-04 [124,] 0.9976555 4.688935e-03 2.344467e-03 [125,] 0.9880504 2.389927e-02 1.194963e-02 > postscript(file="/var/wessaorg/rcomp/tmp/1zeko1324572921.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/wessaorg/rcomp/tmp/20yso1324572921.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3toy01324572921.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4bltg1324572921.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/59mf91324572921.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 144 Frequency = 1 1 2 3 4 5 6 919.38976 44251.41221 -12513.66548 -62475.97699 -38269.60329 -26433.57931 7 8 9 10 11 12 24342.15342 23505.56750 -4069.38700 72151.81637 -47495.66348 -12576.29381 13 14 15 16 17 18 -59418.21448 -34652.27622 44411.87677 7597.28229 -44964.92001 -5773.07229 19 20 21 22 23 24 -68977.67482 -50475.32819 -17256.22571 -16971.90085 40794.90159 -49989.10419 25 26 27 28 29 30 -13075.66083 48399.99673 5288.55207 36107.65643 129622.84625 31275.87965 31 32 33 34 35 36 24448.54824 37050.55557 -50938.60304 -35611.34523 23846.75505 -5877.06899 37 38 39 40 41 42 43383.80872 -15525.15516 -11110.59528 37512.48323 48538.31674 -7456.70072 43 44 45 46 47 48 -6265.02955 2689.79223 -3128.72455 45622.52738 -7026.83730 32659.86439 49 50 51 52 53 54 31412.95980 -37566.82852 -23748.25424 -21563.32573 84625.26554 56023.54559 55 56 57 58 59 60 21113.24687 35319.49311 48312.47631 1531.63116 26420.41803 -10476.36895 61 62 63 64 65 66 19469.50382 -37599.43850 27467.37901 2485.04484 45061.19614 -26443.46011 67 68 69 70 71 72 -3262.53975 -95576.49529 -11949.18398 -12163.65746 31308.58958 18529.78261 73 74 75 76 77 78 -26521.88759 -26897.52399 -79185.22158 -25401.35608 -30435.23666 -70459.95278 79 80 81 82 83 84 -8174.04131 -44863.12551 -29894.12982 112746.19528 -23851.67253 -4641.09956 85 86 87 88 89 90 -24077.55852 9425.09058 -13693.35986 -17518.81413 -1803.95811 17659.62831 91 92 93 94 95 96 182.74907 -37689.07232 28104.57646 12457.94247 -33057.46648 32698.28753 97 98 99 100 101 102 5963.28185 -7027.87541 45199.59345 -20757.74346 3369.05811 -16380.06574 103 104 105 106 107 108 3905.39657 14786.46201 5803.97635 -28568.73856 -6675.53097 25268.28990 109 110 111 112 113 114 -5684.36365 -34836.95935 -4430.31661 16607.96281 4681.24311 -14964.96345 115 116 117 118 119 120 -7326.34687 -5684.36365 80832.98230 -19583.07192 40.49702 26663.77043 121 122 123 124 125 126 -14265.09242 6362.35858 5984.08378 -40535.96349 -2216.86625 -7678.06149 127 128 129 130 131 132 26267.68337 24911.27651 -1976.09748 -11801.07766 -1980.41896 1997.27425 133 134 135 136 137 138 -2317.28925 17791.96550 -5124.42562 -2587.75145 -5684.36365 10695.18194 139 140 141 142 143 144 -37580.12642 -1184.79394 -17190.73115 -3624.14132 14058.09243 6543.76134 > postscript(file="/var/wessaorg/rcomp/tmp/64zsh1324572921.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 144 Frequency = 1 lag(myerror, k = 1) myerror 0 919.38976 NA 1 44251.41221 919.38976 2 -12513.66548 44251.41221 3 -62475.97699 -12513.66548 4 -38269.60329 -62475.97699 5 -26433.57931 -38269.60329 6 24342.15342 -26433.57931 7 23505.56750 24342.15342 8 -4069.38700 23505.56750 9 72151.81637 -4069.38700 10 -47495.66348 72151.81637 11 -12576.29381 -47495.66348 12 -59418.21448 -12576.29381 13 -34652.27622 -59418.21448 14 44411.87677 -34652.27622 15 7597.28229 44411.87677 16 -44964.92001 7597.28229 17 -5773.07229 -44964.92001 18 -68977.67482 -5773.07229 19 -50475.32819 -68977.67482 20 -17256.22571 -50475.32819 21 -16971.90085 -17256.22571 22 40794.90159 -16971.90085 23 -49989.10419 40794.90159 24 -13075.66083 -49989.10419 25 48399.99673 -13075.66083 26 5288.55207 48399.99673 27 36107.65643 5288.55207 28 129622.84625 36107.65643 29 31275.87965 129622.84625 30 24448.54824 31275.87965 31 37050.55557 24448.54824 32 -50938.60304 37050.55557 33 -35611.34523 -50938.60304 34 23846.75505 -35611.34523 35 -5877.06899 23846.75505 36 43383.80872 -5877.06899 37 -15525.15516 43383.80872 38 -11110.59528 -15525.15516 39 37512.48323 -11110.59528 40 48538.31674 37512.48323 41 -7456.70072 48538.31674 42 -6265.02955 -7456.70072 43 2689.79223 -6265.02955 44 -3128.72455 2689.79223 45 45622.52738 -3128.72455 46 -7026.83730 45622.52738 47 32659.86439 -7026.83730 48 31412.95980 32659.86439 49 -37566.82852 31412.95980 50 -23748.25424 -37566.82852 51 -21563.32573 -23748.25424 52 84625.26554 -21563.32573 53 56023.54559 84625.26554 54 21113.24687 56023.54559 55 35319.49311 21113.24687 56 48312.47631 35319.49311 57 1531.63116 48312.47631 58 26420.41803 1531.63116 59 -10476.36895 26420.41803 60 19469.50382 -10476.36895 61 -37599.43850 19469.50382 62 27467.37901 -37599.43850 63 2485.04484 27467.37901 64 45061.19614 2485.04484 65 -26443.46011 45061.19614 66 -3262.53975 -26443.46011 67 -95576.49529 -3262.53975 68 -11949.18398 -95576.49529 69 -12163.65746 -11949.18398 70 31308.58958 -12163.65746 71 18529.78261 31308.58958 72 -26521.88759 18529.78261 73 -26897.52399 -26521.88759 74 -79185.22158 -26897.52399 75 -25401.35608 -79185.22158 76 -30435.23666 -25401.35608 77 -70459.95278 -30435.23666 78 -8174.04131 -70459.95278 79 -44863.12551 -8174.04131 80 -29894.12982 -44863.12551 81 112746.19528 -29894.12982 82 -23851.67253 112746.19528 83 -4641.09956 -23851.67253 84 -24077.55852 -4641.09956 85 9425.09058 -24077.55852 86 -13693.35986 9425.09058 87 -17518.81413 -13693.35986 88 -1803.95811 -17518.81413 89 17659.62831 -1803.95811 90 182.74907 17659.62831 91 -37689.07232 182.74907 92 28104.57646 -37689.07232 93 12457.94247 28104.57646 94 -33057.46648 12457.94247 95 32698.28753 -33057.46648 96 5963.28185 32698.28753 97 -7027.87541 5963.28185 98 45199.59345 -7027.87541 99 -20757.74346 45199.59345 100 3369.05811 -20757.74346 101 -16380.06574 3369.05811 102 3905.39657 -16380.06574 103 14786.46201 3905.39657 104 5803.97635 14786.46201 105 -28568.73856 5803.97635 106 -6675.53097 -28568.73856 107 25268.28990 -6675.53097 108 -5684.36365 25268.28990 109 -34836.95935 -5684.36365 110 -4430.31661 -34836.95935 111 16607.96281 -4430.31661 112 4681.24311 16607.96281 113 -14964.96345 4681.24311 114 -7326.34687 -14964.96345 115 -5684.36365 -7326.34687 116 80832.98230 -5684.36365 117 -19583.07192 80832.98230 118 40.49702 -19583.07192 119 26663.77043 40.49702 120 -14265.09242 26663.77043 121 6362.35858 -14265.09242 122 5984.08378 6362.35858 123 -40535.96349 5984.08378 124 -2216.86625 -40535.96349 125 -7678.06149 -2216.86625 126 26267.68337 -7678.06149 127 24911.27651 26267.68337 128 -1976.09748 24911.27651 129 -11801.07766 -1976.09748 130 -1980.41896 -11801.07766 131 1997.27425 -1980.41896 132 -2317.28925 1997.27425 133 17791.96550 -2317.28925 134 -5124.42562 17791.96550 135 -2587.75145 -5124.42562 136 -5684.36365 -2587.75145 137 10695.18194 -5684.36365 138 -37580.12642 10695.18194 139 -1184.79394 -37580.12642 140 -17190.73115 -1184.79394 141 -3624.14132 -17190.73115 142 14058.09243 -3624.14132 143 6543.76134 14058.09243 144 NA 6543.76134 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 44251.41221 919.38976 [2,] -12513.66548 44251.41221 [3,] -62475.97699 -12513.66548 [4,] -38269.60329 -62475.97699 [5,] -26433.57931 -38269.60329 [6,] 24342.15342 -26433.57931 [7,] 23505.56750 24342.15342 [8,] -4069.38700 23505.56750 [9,] 72151.81637 -4069.38700 [10,] -47495.66348 72151.81637 [11,] -12576.29381 -47495.66348 [12,] -59418.21448 -12576.29381 [13,] -34652.27622 -59418.21448 [14,] 44411.87677 -34652.27622 [15,] 7597.28229 44411.87677 [16,] -44964.92001 7597.28229 [17,] -5773.07229 -44964.92001 [18,] -68977.67482 -5773.07229 [19,] -50475.32819 -68977.67482 [20,] -17256.22571 -50475.32819 [21,] -16971.90085 -17256.22571 [22,] 40794.90159 -16971.90085 [23,] -49989.10419 40794.90159 [24,] -13075.66083 -49989.10419 [25,] 48399.99673 -13075.66083 [26,] 5288.55207 48399.99673 [27,] 36107.65643 5288.55207 [28,] 129622.84625 36107.65643 [29,] 31275.87965 129622.84625 [30,] 24448.54824 31275.87965 [31,] 37050.55557 24448.54824 [32,] -50938.60304 37050.55557 [33,] -35611.34523 -50938.60304 [34,] 23846.75505 -35611.34523 [35,] -5877.06899 23846.75505 [36,] 43383.80872 -5877.06899 [37,] -15525.15516 43383.80872 [38,] -11110.59528 -15525.15516 [39,] 37512.48323 -11110.59528 [40,] 48538.31674 37512.48323 [41,] -7456.70072 48538.31674 [42,] -6265.02955 -7456.70072 [43,] 2689.79223 -6265.02955 [44,] -3128.72455 2689.79223 [45,] 45622.52738 -3128.72455 [46,] -7026.83730 45622.52738 [47,] 32659.86439 -7026.83730 [48,] 31412.95980 32659.86439 [49,] -37566.82852 31412.95980 [50,] -23748.25424 -37566.82852 [51,] -21563.32573 -23748.25424 [52,] 84625.26554 -21563.32573 [53,] 56023.54559 84625.26554 [54,] 21113.24687 56023.54559 [55,] 35319.49311 21113.24687 [56,] 48312.47631 35319.49311 [57,] 1531.63116 48312.47631 [58,] 26420.41803 1531.63116 [59,] -10476.36895 26420.41803 [60,] 19469.50382 -10476.36895 [61,] -37599.43850 19469.50382 [62,] 27467.37901 -37599.43850 [63,] 2485.04484 27467.37901 [64,] 45061.19614 2485.04484 [65,] -26443.46011 45061.19614 [66,] -3262.53975 -26443.46011 [67,] -95576.49529 -3262.53975 [68,] -11949.18398 -95576.49529 [69,] -12163.65746 -11949.18398 [70,] 31308.58958 -12163.65746 [71,] 18529.78261 31308.58958 [72,] -26521.88759 18529.78261 [73,] -26897.52399 -26521.88759 [74,] -79185.22158 -26897.52399 [75,] -25401.35608 -79185.22158 [76,] -30435.23666 -25401.35608 [77,] -70459.95278 -30435.23666 [78,] -8174.04131 -70459.95278 [79,] -44863.12551 -8174.04131 [80,] -29894.12982 -44863.12551 [81,] 112746.19528 -29894.12982 [82,] -23851.67253 112746.19528 [83,] -4641.09956 -23851.67253 [84,] -24077.55852 -4641.09956 [85,] 9425.09058 -24077.55852 [86,] -13693.35986 9425.09058 [87,] -17518.81413 -13693.35986 [88,] -1803.95811 -17518.81413 [89,] 17659.62831 -1803.95811 [90,] 182.74907 17659.62831 [91,] -37689.07232 182.74907 [92,] 28104.57646 -37689.07232 [93,] 12457.94247 28104.57646 [94,] -33057.46648 12457.94247 [95,] 32698.28753 -33057.46648 [96,] 5963.28185 32698.28753 [97,] -7027.87541 5963.28185 [98,] 45199.59345 -7027.87541 [99,] -20757.74346 45199.59345 [100,] 3369.05811 -20757.74346 [101,] -16380.06574 3369.05811 [102,] 3905.39657 -16380.06574 [103,] 14786.46201 3905.39657 [104,] 5803.97635 14786.46201 [105,] -28568.73856 5803.97635 [106,] -6675.53097 -28568.73856 [107,] 25268.28990 -6675.53097 [108,] -5684.36365 25268.28990 [109,] -34836.95935 -5684.36365 [110,] -4430.31661 -34836.95935 [111,] 16607.96281 -4430.31661 [112,] 4681.24311 16607.96281 [113,] -14964.96345 4681.24311 [114,] -7326.34687 -14964.96345 [115,] -5684.36365 -7326.34687 [116,] 80832.98230 -5684.36365 [117,] -19583.07192 80832.98230 [118,] 40.49702 -19583.07192 [119,] 26663.77043 40.49702 [120,] -14265.09242 26663.77043 [121,] 6362.35858 -14265.09242 [122,] 5984.08378 6362.35858 [123,] -40535.96349 5984.08378 [124,] -2216.86625 -40535.96349 [125,] -7678.06149 -2216.86625 [126,] 26267.68337 -7678.06149 [127,] 24911.27651 26267.68337 [128,] -1976.09748 24911.27651 [129,] -11801.07766 -1976.09748 [130,] -1980.41896 -11801.07766 [131,] 1997.27425 -1980.41896 [132,] -2317.28925 1997.27425 [133,] 17791.96550 -2317.28925 [134,] -5124.42562 17791.96550 [135,] -2587.75145 -5124.42562 [136,] -5684.36365 -2587.75145 [137,] 10695.18194 -5684.36365 [138,] -37580.12642 10695.18194 [139,] -1184.79394 -37580.12642 [140,] -17190.73115 -1184.79394 [141,] -3624.14132 -17190.73115 [142,] 14058.09243 -3624.14132 [143,] 6543.76134 14058.09243 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 44251.41221 919.38976 2 -12513.66548 44251.41221 3 -62475.97699 -12513.66548 4 -38269.60329 -62475.97699 5 -26433.57931 -38269.60329 6 24342.15342 -26433.57931 7 23505.56750 24342.15342 8 -4069.38700 23505.56750 9 72151.81637 -4069.38700 10 -47495.66348 72151.81637 11 -12576.29381 -47495.66348 12 -59418.21448 -12576.29381 13 -34652.27622 -59418.21448 14 44411.87677 -34652.27622 15 7597.28229 44411.87677 16 -44964.92001 7597.28229 17 -5773.07229 -44964.92001 18 -68977.67482 -5773.07229 19 -50475.32819 -68977.67482 20 -17256.22571 -50475.32819 21 -16971.90085 -17256.22571 22 40794.90159 -16971.90085 23 -49989.10419 40794.90159 24 -13075.66083 -49989.10419 25 48399.99673 -13075.66083 26 5288.55207 48399.99673 27 36107.65643 5288.55207 28 129622.84625 36107.65643 29 31275.87965 129622.84625 30 24448.54824 31275.87965 31 37050.55557 24448.54824 32 -50938.60304 37050.55557 33 -35611.34523 -50938.60304 34 23846.75505 -35611.34523 35 -5877.06899 23846.75505 36 43383.80872 -5877.06899 37 -15525.15516 43383.80872 38 -11110.59528 -15525.15516 39 37512.48323 -11110.59528 40 48538.31674 37512.48323 41 -7456.70072 48538.31674 42 -6265.02955 -7456.70072 43 2689.79223 -6265.02955 44 -3128.72455 2689.79223 45 45622.52738 -3128.72455 46 -7026.83730 45622.52738 47 32659.86439 -7026.83730 48 31412.95980 32659.86439 49 -37566.82852 31412.95980 50 -23748.25424 -37566.82852 51 -21563.32573 -23748.25424 52 84625.26554 -21563.32573 53 56023.54559 84625.26554 54 21113.24687 56023.54559 55 35319.49311 21113.24687 56 48312.47631 35319.49311 57 1531.63116 48312.47631 58 26420.41803 1531.63116 59 -10476.36895 26420.41803 60 19469.50382 -10476.36895 61 -37599.43850 19469.50382 62 27467.37901 -37599.43850 63 2485.04484 27467.37901 64 45061.19614 2485.04484 65 -26443.46011 45061.19614 66 -3262.53975 -26443.46011 67 -95576.49529 -3262.53975 68 -11949.18398 -95576.49529 69 -12163.65746 -11949.18398 70 31308.58958 -12163.65746 71 18529.78261 31308.58958 72 -26521.88759 18529.78261 73 -26897.52399 -26521.88759 74 -79185.22158 -26897.52399 75 -25401.35608 -79185.22158 76 -30435.23666 -25401.35608 77 -70459.95278 -30435.23666 78 -8174.04131 -70459.95278 79 -44863.12551 -8174.04131 80 -29894.12982 -44863.12551 81 112746.19528 -29894.12982 82 -23851.67253 112746.19528 83 -4641.09956 -23851.67253 84 -24077.55852 -4641.09956 85 9425.09058 -24077.55852 86 -13693.35986 9425.09058 87 -17518.81413 -13693.35986 88 -1803.95811 -17518.81413 89 17659.62831 -1803.95811 90 182.74907 17659.62831 91 -37689.07232 182.74907 92 28104.57646 -37689.07232 93 12457.94247 28104.57646 94 -33057.46648 12457.94247 95 32698.28753 -33057.46648 96 5963.28185 32698.28753 97 -7027.87541 5963.28185 98 45199.59345 -7027.87541 99 -20757.74346 45199.59345 100 3369.05811 -20757.74346 101 -16380.06574 3369.05811 102 3905.39657 -16380.06574 103 14786.46201 3905.39657 104 5803.97635 14786.46201 105 -28568.73856 5803.97635 106 -6675.53097 -28568.73856 107 25268.28990 -6675.53097 108 -5684.36365 25268.28990 109 -34836.95935 -5684.36365 110 -4430.31661 -34836.95935 111 16607.96281 -4430.31661 112 4681.24311 16607.96281 113 -14964.96345 4681.24311 114 -7326.34687 -14964.96345 115 -5684.36365 -7326.34687 116 80832.98230 -5684.36365 117 -19583.07192 80832.98230 118 40.49702 -19583.07192 119 26663.77043 40.49702 120 -14265.09242 26663.77043 121 6362.35858 -14265.09242 122 5984.08378 6362.35858 123 -40535.96349 5984.08378 124 -2216.86625 -40535.96349 125 -7678.06149 -2216.86625 126 26267.68337 -7678.06149 127 24911.27651 26267.68337 128 -1976.09748 24911.27651 129 -11801.07766 -1976.09748 130 -1980.41896 -11801.07766 131 1997.27425 -1980.41896 132 -2317.28925 1997.27425 133 17791.96550 -2317.28925 134 -5124.42562 17791.96550 135 -2587.75145 -5124.42562 136 -5684.36365 -2587.75145 137 10695.18194 -5684.36365 138 -37580.12642 10695.18194 139 -1184.79394 -37580.12642 140 -17190.73115 -1184.79394 141 -3624.14132 -17190.73115 142 14058.09243 -3624.14132 143 6543.76134 14058.09243 > 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/wessaorg/rcomp/tmp/7t8lh1324572921.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/wessaorg/rcomp/tmp/8sbcr1324572921.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/wessaorg/rcomp/tmp/9qwgq1324572921.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/wessaorg/rcomp/tmp/10v8fo1324572921.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/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/11xdp81324572921.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/12yip81324572921.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$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$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/1355h91324572921.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/144ary1324572921.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/wessaorg/rcomp/tmp/15jcfb1324572921.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/wessaorg/rcomp/tmp/16or3e1324572921.tab") + } > > try(system("convert tmp/1zeko1324572921.ps tmp/1zeko1324572921.png",intern=TRUE)) character(0) > try(system("convert tmp/20yso1324572921.ps tmp/20yso1324572921.png",intern=TRUE)) character(0) > try(system("convert tmp/3toy01324572921.ps tmp/3toy01324572921.png",intern=TRUE)) character(0) > try(system("convert tmp/4bltg1324572921.ps tmp/4bltg1324572921.png",intern=TRUE)) character(0) > try(system("convert tmp/59mf91324572921.ps tmp/59mf91324572921.png",intern=TRUE)) character(0) > try(system("convert tmp/64zsh1324572921.ps tmp/64zsh1324572921.png",intern=TRUE)) character(0) > try(system("convert tmp/7t8lh1324572921.ps tmp/7t8lh1324572921.png",intern=TRUE)) character(0) > try(system("convert tmp/8sbcr1324572921.ps tmp/8sbcr1324572921.png",intern=TRUE)) character(0) > try(system("convert tmp/9qwgq1324572921.ps tmp/9qwgq1324572921.png",intern=TRUE)) character(0) > try(system("convert tmp/10v8fo1324572921.ps tmp/10v8fo1324572921.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.870 0.745 5.628