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Type 'q()' to quit R. > x <- array(list(1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,1 + ,0 + ,0 + ,1 + ,0 + ,0 + ,0) + ,dim=c(3 + ,154) + ,dimnames=list(c('Tvier' + ,'Ttwee' + ,'CorrectAnalysis ') + ,1:154)) > y <- array(NA,dim=c(3,154),dimnames=list(c('Tvier','Ttwee','CorrectAnalysis '),1:154)) > 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 = '3' > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from 'package:base': as.Date, as.Date.numeric > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x CorrectAnalysis\r\r\r\r Tvier Ttwee 1 0 1 0 2 0 0 0 3 0 0 0 4 0 0 0 5 0 0 0 6 0 0 0 7 0 0 0 8 0 1 0 9 0 0 0 10 0 0 0 11 0 1 0 12 0 0 0 13 0 0 0 14 0 1 0 15 0 0 0 16 0 1 0 17 1 1 0 18 0 1 0 19 0 0 0 20 1 1 0 21 0 0 0 22 0 0 0 23 0 0 0 24 0 0 0 25 0 1 0 26 0 0 0 27 0 0 0 28 0 0 0 29 0 0 0 30 0 0 0 31 0 0 0 32 0 0 0 33 0 0 0 34 0 1 0 35 0 0 0 36 0 0 0 37 0 1 0 38 0 0 0 39 0 0 0 40 0 1 0 41 1 0 0 42 0 0 0 43 0 0 0 44 0 1 0 45 0 0 0 46 0 0 0 47 0 0 0 48 0 0 0 49 0 0 0 50 0 0 0 51 0 1 0 52 1 1 0 53 0 0 0 54 1 0 0 55 0 0 0 56 0 1 0 57 0 0 0 58 0 0 0 59 0 0 0 60 1 1 0 61 0 1 0 62 0 0 0 63 0 0 0 64 0 1 0 65 0 0 0 66 0 0 0 67 1 1 0 68 0 0 0 69 0 0 0 70 0 0 0 71 0 0 0 72 0 0 0 73 0 0 0 74 0 0 0 75 0 0 0 76 0 1 0 77 0 0 0 78 0 0 0 79 1 1 0 80 0 1 0 81 0 0 0 82 0 0 0 83 0 0 0 84 1 0 0 85 0 0 0 86 0 0 0 87 0 0 0 88 0 0 1 89 0 0 0 90 0 0 0 91 0 0 0 92 0 0 1 93 0 0 0 94 0 0 0 95 0 0 1 96 0 0 0 97 0 0 1 98 0 0 0 99 0 0 0 100 0 0 0 101 0 0 0 102 0 0 0 103 0 0 0 104 0 0 0 105 0 0 1 106 0 0 0 107 0 0 0 108 0 0 1 109 0 0 0 110 0 0 0 111 0 0 1 112 0 0 1 113 0 0 0 114 0 0 1 115 0 0 0 116 0 0 0 117 0 0 0 118 0 0 0 119 0 0 0 120 0 0 0 121 0 0 0 122 0 0 0 123 0 0 1 124 0 0 0 125 0 0 0 126 0 0 1 127 0 0 0 128 0 0 0 129 0 0 0 130 0 0 0 131 0 0 0 132 0 0 0 133 0 0 0 134 0 0 0 135 0 0 0 136 0 0 0 137 0 0 0 138 0 0 1 139 0 0 1 140 0 0 0 141 1 0 0 142 0 0 1 143 0 0 0 144 0 0 0 145 0 0 0 146 0 0 1 147 0 0 1 148 0 0 1 149 0 0 0 150 0 0 0 151 0 0 0 152 1 0 0 153 1 0 0 154 0 0 0 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Tvier Ttwee 0.05263 0.20824 -0.05263 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.26087 -0.05263 -0.05263 -0.05263 0.94737 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.05263 0.02425 2.171 0.031509 * Tvier 0.20824 0.05917 3.519 0.000572 *** Ttwee -0.05263 0.06730 -0.782 0.435438 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.2589 on 151 degrees of freedom Multiple R-squared: 0.08549, Adjusted R-squared: 0.07338 F-statistic: 7.058 on 2 and 151 DF, p-value: 0.001174 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 0.000000e+00 0.0000000000 1.0000000000 [2,] 0.000000e+00 0.0000000000 1.0000000000 [3,] 0.000000e+00 0.0000000000 1.0000000000 [4,] 0.000000e+00 0.0000000000 1.0000000000 [5,] 0.000000e+00 0.0000000000 1.0000000000 [6,] 0.000000e+00 0.0000000000 1.0000000000 [7,] 0.000000e+00 0.0000000000 1.0000000000 [8,] 0.000000e+00 0.0000000000 1.0000000000 [9,] 0.000000e+00 0.0000000000 1.0000000000 [10,] 0.000000e+00 0.0000000000 1.0000000000 [11,] 0.000000e+00 0.0000000000 1.0000000000 [12,] 4.062265e-01 0.8124529965 0.5937735017 [13,] 3.639672e-01 0.7279344688 0.6360327656 [14,] 2.925932e-01 0.5851864972 0.7074067514 [15,] 8.259593e-01 0.3480814065 0.1740407033 [16,] 7.771617e-01 0.4456766764 0.2228383382 [17,] 7.223594e-01 0.5552811231 0.2776405616 [18,] 6.626770e-01 0.6746460222 0.3373230111 [19,] 5.995593e-01 0.8008813709 0.4004406854 [20,] 5.887875e-01 0.8224249169 0.4112124585 [21,] 5.248229e-01 0.9503542056 0.4751771028 [22,] 4.610248e-01 0.9220495362 0.5389752319 [23,] 3.989631e-01 0.7979261868 0.6010369066 [24,] 3.400297e-01 0.6800593453 0.6599703273 [25,] 2.853574e-01 0.5707148044 0.7146425978 [26,] 2.357716e-01 0.4715431164 0.7642284418 [27,] 1.917741e-01 0.3835482343 0.8082258828 [28,] 1.535578e-01 0.3071155914 0.8464422043 [29,] 1.477816e-01 0.2955631713 0.8522184144 [30,] 1.165199e-01 0.2330398808 0.8834800596 [31,] 9.047308e-02 0.1809461571 0.9095269214 [32,] 8.562806e-02 0.1712561146 0.9143719427 [33,] 6.544823e-02 0.1308964640 0.9345517680 [34,] 4.928263e-02 0.0985652633 0.9507173684 [35,] 4.629813e-02 0.0925962652 0.9537018674 [36,] 5.907129e-01 0.8185741374 0.4092870687 [37,] 5.396923e-01 0.9206153560 0.4603076780 [38,] 4.882895e-01 0.9765789323 0.5117105338 [39,] 4.813457e-01 0.9626913306 0.5186543347 [40,] 4.309010e-01 0.8618020836 0.5690989582 [41,] 3.818008e-01 0.7636015535 0.6181992232 [42,] 3.347566e-01 0.6695131192 0.6652434404 [43,] 2.903774e-01 0.5807547705 0.7096226147 [44,] 2.491491e-01 0.4982981311 0.7508509344 [45,] 2.114228e-01 0.4228455015 0.7885772493 [46,] 2.125978e-01 0.4251956203 0.7874021899 [47,] 5.745171e-01 0.8509657814 0.4254828907 [48,] 5.269271e-01 0.9461457837 0.4730728919 [49,] 9.389624e-01 0.1220751643 0.0610375822 [50,] 9.236220e-01 0.1527560672 0.0763780336 [51,] 9.288450e-01 0.1423100226 0.0711550113 [52,] 9.117731e-01 0.1764538733 0.0882269367 [53,] 8.918639e-01 0.2162721605 0.1081360802 [54,] 8.689582e-01 0.2620836736 0.1310418368 [55,] 9.696791e-01 0.0606418595 0.0303209298 [56,] 9.722668e-01 0.0554664813 0.0277332407 [57,] 9.641904e-01 0.0716192485 0.0358096243 [58,] 9.542977e-01 0.0914045599 0.0457022799 [59,] 9.629129e-01 0.0741741244 0.0370870622 [60,] 9.527920e-01 0.0944160751 0.0472080375 [61,] 9.405863e-01 0.1188274224 0.0594137112 [62,] 9.869761e-01 0.0260478909 0.0130239455 [63,] 9.827036e-01 0.0345928764 0.0172964382 [64,] 9.772935e-01 0.0454129079 0.0227064540 [65,] 9.705304e-01 0.0589392590 0.0294696295 [66,] 9.621829e-01 0.0756342849 0.0378171424 [67,] 9.520102e-01 0.0959796897 0.0479898448 [68,] 9.397695e-01 0.1204610750 0.0602305375 [69,] 9.252255e-01 0.1495490054 0.0747745027 [70,] 9.081614e-01 0.1836771592 0.0918385796 [71,] 9.224785e-01 0.1550430629 0.0775215314 [72,] 9.049884e-01 0.1900232522 0.0950116261 [73,] 8.847692e-01 0.2304616680 0.1152308340 [74,] 9.776056e-01 0.0447887558 0.0223943779 [75,] 9.735737e-01 0.0528525726 0.0264262863 [76,] 9.659746e-01 0.0680507893 0.0340253946 [77,] 9.566692e-01 0.0866615256 0.0433307628 [78,] 9.454162e-01 0.1091676212 0.0545838106 [79,] 9.991716e-01 0.0016567151 0.0008283575 [80,] 9.987830e-01 0.0024340352 0.0012170176 [81,] 9.982331e-01 0.0035338885 0.0017669442 [82,] 9.974648e-01 0.0050703088 0.0025351544 [83,] 9.963358e-01 0.0073284758 0.0036642379 [84,] 9.948662e-01 0.0102675220 0.0051337610 [85,] 9.928915e-01 0.0142170301 0.0071085150 [86,] 9.902719e-01 0.0194561108 0.0097280554 [87,] 9.866039e-01 0.0267921434 0.0133960717 [88,] 9.820936e-01 0.0358127038 0.0179063519 [89,] 9.763413e-01 0.0473174327 0.0236587163 [90,] 9.685781e-01 0.0628438971 0.0314219486 [91,] 9.594387e-01 0.0811225168 0.0405612584 [92,] 9.474168e-01 0.1051664271 0.0525832136 [93,] 9.336695e-01 0.1326610620 0.0663305310 [94,] 9.172695e-01 0.1654610487 0.0827305244 [95,] 8.979667e-01 0.2040665428 0.1020332714 [96,] 8.755530e-01 0.2488940720 0.1244470360 [97,] 8.498785e-01 0.3002429292 0.1501214646 [98,] 8.208686e-01 0.3582628062 0.1791314031 [99,] 7.885373e-01 0.4229253076 0.2114626538 [100,] 7.497376e-01 0.5005247060 0.2502623530 [101,] 7.107889e-01 0.5784221735 0.2892110868 [102,] 6.691751e-01 0.6616498574 0.3308249287 [103,] 6.210238e-01 0.7579523948 0.3789761974 [104,] 5.751123e-01 0.8497754363 0.4248877182 [105,] 5.281332e-01 0.9437336860 0.4718668430 [106,] 4.757182e-01 0.9514363318 0.5242818341 [107,] 4.234427e-01 0.8468853348 0.5765573326 [108,] 3.769615e-01 0.7539230027 0.6230384987 [109,] 3.273612e-01 0.6547224942 0.6726387529 [110,] 2.848475e-01 0.5696950179 0.7151524910 [111,] 2.451422e-01 0.4902843017 0.7548578491 [112,] 2.086156e-01 0.4172312896 0.7913843552 [113,] 1.755191e-01 0.3510381298 0.8244809351 [114,] 1.459826e-01 0.2919652548 0.8540173726 [115,] 1.200213e-01 0.2400426792 0.8799786604 [116,] 9.754675e-02 0.1950934962 0.9024532519 [117,] 7.838333e-02 0.1567666691 0.9216166655 [118,] 5.948874e-02 0.1189774864 0.9405112568 [119,] 4.645512e-02 0.0929102436 0.9535448782 [120,] 3.587144e-02 0.0717428877 0.9641285561 [121,] 2.570919e-02 0.0514183737 0.9742908132 [122,] 1.926371e-02 0.0385274139 0.9807362931 [123,] 1.428466e-02 0.0285693237 0.9857153381 [124,] 1.049475e-02 0.0209894977 0.9895052512 [125,] 7.650980e-03 0.0153019607 0.9923490196 [126,] 5.546407e-03 0.0110928148 0.9944535926 [127,] 4.009406e-03 0.0080188123 0.9959905939 [128,] 2.901212e-03 0.0058024240 0.9970987880 [129,] 2.112371e-03 0.0042247420 0.9978876290 [130,] 1.558714e-03 0.0031174283 0.9984412859 [131,] 1.177389e-03 0.0023547776 0.9988226112 [132,] 9.234670e-04 0.0018469341 0.9990765330 [133,] 4.980701e-04 0.0009961403 0.9995019299 [134,] 2.570790e-04 0.0005141581 0.9997429210 [135,] 2.020577e-04 0.0004041153 0.9997979423 [136,] 6.547347e-03 0.0130946941 0.9934526529 [137,] 3.558694e-03 0.0071173886 0.9964413057 [138,] 2.486049e-03 0.0049720985 0.9975139508 [139,] 1.832355e-03 0.0036647105 0.9981676447 [140,] 1.504019e-03 0.0030080376 0.9984959812 [141,] 6.359523e-04 0.0012719046 0.9993640477 [142,] 2.373018e-04 0.0004746036 0.9997626982 [143,] 7.505823e-05 0.0001501165 0.9999249418 > postscript(file="/var/wessaorg/rcomp/tmp/1gj3f1356206641.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/2whih1356206641.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/35zr51356206641.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4f2yf1356206641.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5lw5x1356206641.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$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 = 154 Frequency = 1 1 2 3 4 5 -2.608696e-01 -5.263158e-02 -5.263158e-02 -5.263158e-02 -5.263158e-02 6 7 8 9 10 -5.263158e-02 -5.263158e-02 -2.608696e-01 -5.263158e-02 -5.263158e-02 11 12 13 14 15 -2.608696e-01 -5.263158e-02 -5.263158e-02 -2.608696e-01 -5.263158e-02 16 17 18 19 20 -2.608696e-01 7.391304e-01 -2.608696e-01 -5.263158e-02 7.391304e-01 21 22 23 24 25 -5.263158e-02 -5.263158e-02 -5.263158e-02 -5.263158e-02 -2.608696e-01 26 27 28 29 30 -5.263158e-02 -5.263158e-02 -5.263158e-02 -5.263158e-02 -5.263158e-02 31 32 33 34 35 -5.263158e-02 -5.263158e-02 -5.263158e-02 -2.608696e-01 -5.263158e-02 36 37 38 39 40 -5.263158e-02 -2.608696e-01 -5.263158e-02 -5.263158e-02 -2.608696e-01 41 42 43 44 45 9.473684e-01 -5.263158e-02 -5.263158e-02 -2.608696e-01 -5.263158e-02 46 47 48 49 50 -5.263158e-02 -5.263158e-02 -5.263158e-02 -5.263158e-02 -5.263158e-02 51 52 53 54 55 -2.608696e-01 7.391304e-01 -5.263158e-02 9.473684e-01 -5.263158e-02 56 57 58 59 60 -2.608696e-01 -5.263158e-02 -5.263158e-02 -5.263158e-02 7.391304e-01 61 62 63 64 65 -2.608696e-01 -5.263158e-02 -5.263158e-02 -2.608696e-01 -5.263158e-02 66 67 68 69 70 -5.263158e-02 7.391304e-01 -5.263158e-02 -5.263158e-02 -5.263158e-02 71 72 73 74 75 -5.263158e-02 -5.263158e-02 -5.263158e-02 -5.263158e-02 -5.263158e-02 76 77 78 79 80 -2.608696e-01 -5.263158e-02 -5.263158e-02 7.391304e-01 -2.608696e-01 81 82 83 84 85 -5.263158e-02 -5.263158e-02 -5.263158e-02 9.473684e-01 -5.263158e-02 86 87 88 89 90 -5.263158e-02 -5.263158e-02 -3.301734e-18 -5.263158e-02 -5.263158e-02 91 92 93 94 95 -5.263158e-02 -3.301734e-18 -5.263158e-02 -5.263158e-02 -3.301734e-18 96 97 98 99 100 -5.263158e-02 -3.301734e-18 -5.263158e-02 -5.263158e-02 -5.263158e-02 101 102 103 104 105 -5.263158e-02 -5.263158e-02 -5.263158e-02 -5.263158e-02 -3.301734e-18 106 107 108 109 110 -5.263158e-02 -5.263158e-02 -3.301734e-18 -5.263158e-02 -5.263158e-02 111 112 113 114 115 -3.301734e-18 -3.301734e-18 -5.263158e-02 -3.301734e-18 -5.263158e-02 116 117 118 119 120 -5.263158e-02 -5.263158e-02 -5.263158e-02 -5.263158e-02 -5.263158e-02 121 122 123 124 125 -5.263158e-02 -5.263158e-02 -3.301734e-18 -5.263158e-02 -5.263158e-02 126 127 128 129 130 -3.301734e-18 -5.263158e-02 -5.263158e-02 -5.263158e-02 -5.263158e-02 131 132 133 134 135 -5.263158e-02 -5.263158e-02 -5.263158e-02 -5.263158e-02 -5.263158e-02 136 137 138 139 140 -5.263158e-02 -5.263158e-02 -3.301734e-18 -3.301734e-18 -5.263158e-02 141 142 143 144 145 9.473684e-01 -3.301734e-18 -5.263158e-02 -5.263158e-02 -5.263158e-02 146 147 148 149 150 -3.301734e-18 -3.301734e-18 -3.301734e-18 -5.263158e-02 -5.263158e-02 151 152 153 154 -5.263158e-02 9.473684e-01 9.473684e-01 -5.263158e-02 > postscript(file="/var/wessaorg/rcomp/tmp/6nmz21356206641.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 = 154 Frequency = 1 lag(myerror, k = 1) myerror 0 -2.608696e-01 NA 1 -5.263158e-02 -2.608696e-01 2 -5.263158e-02 -5.263158e-02 3 -5.263158e-02 -5.263158e-02 4 -5.263158e-02 -5.263158e-02 5 -5.263158e-02 -5.263158e-02 6 -5.263158e-02 -5.263158e-02 7 -2.608696e-01 -5.263158e-02 8 -5.263158e-02 -2.608696e-01 9 -5.263158e-02 -5.263158e-02 10 -2.608696e-01 -5.263158e-02 11 -5.263158e-02 -2.608696e-01 12 -5.263158e-02 -5.263158e-02 13 -2.608696e-01 -5.263158e-02 14 -5.263158e-02 -2.608696e-01 15 -2.608696e-01 -5.263158e-02 16 7.391304e-01 -2.608696e-01 17 -2.608696e-01 7.391304e-01 18 -5.263158e-02 -2.608696e-01 19 7.391304e-01 -5.263158e-02 20 -5.263158e-02 7.391304e-01 21 -5.263158e-02 -5.263158e-02 22 -5.263158e-02 -5.263158e-02 23 -5.263158e-02 -5.263158e-02 24 -2.608696e-01 -5.263158e-02 25 -5.263158e-02 -2.608696e-01 26 -5.263158e-02 -5.263158e-02 27 -5.263158e-02 -5.263158e-02 28 -5.263158e-02 -5.263158e-02 29 -5.263158e-02 -5.263158e-02 30 -5.263158e-02 -5.263158e-02 31 -5.263158e-02 -5.263158e-02 32 -5.263158e-02 -5.263158e-02 33 -2.608696e-01 -5.263158e-02 34 -5.263158e-02 -2.608696e-01 35 -5.263158e-02 -5.263158e-02 36 -2.608696e-01 -5.263158e-02 37 -5.263158e-02 -2.608696e-01 38 -5.263158e-02 -5.263158e-02 39 -2.608696e-01 -5.263158e-02 40 9.473684e-01 -2.608696e-01 41 -5.263158e-02 9.473684e-01 42 -5.263158e-02 -5.263158e-02 43 -2.608696e-01 -5.263158e-02 44 -5.263158e-02 -2.608696e-01 45 -5.263158e-02 -5.263158e-02 46 -5.263158e-02 -5.263158e-02 47 -5.263158e-02 -5.263158e-02 48 -5.263158e-02 -5.263158e-02 49 -5.263158e-02 -5.263158e-02 50 -2.608696e-01 -5.263158e-02 51 7.391304e-01 -2.608696e-01 52 -5.263158e-02 7.391304e-01 53 9.473684e-01 -5.263158e-02 54 -5.263158e-02 9.473684e-01 55 -2.608696e-01 -5.263158e-02 56 -5.263158e-02 -2.608696e-01 57 -5.263158e-02 -5.263158e-02 58 -5.263158e-02 -5.263158e-02 59 7.391304e-01 -5.263158e-02 60 -2.608696e-01 7.391304e-01 61 -5.263158e-02 -2.608696e-01 62 -5.263158e-02 -5.263158e-02 63 -2.608696e-01 -5.263158e-02 64 -5.263158e-02 -2.608696e-01 65 -5.263158e-02 -5.263158e-02 66 7.391304e-01 -5.263158e-02 67 -5.263158e-02 7.391304e-01 68 -5.263158e-02 -5.263158e-02 69 -5.263158e-02 -5.263158e-02 70 -5.263158e-02 -5.263158e-02 71 -5.263158e-02 -5.263158e-02 72 -5.263158e-02 -5.263158e-02 73 -5.263158e-02 -5.263158e-02 74 -5.263158e-02 -5.263158e-02 75 -2.608696e-01 -5.263158e-02 76 -5.263158e-02 -2.608696e-01 77 -5.263158e-02 -5.263158e-02 78 7.391304e-01 -5.263158e-02 79 -2.608696e-01 7.391304e-01 80 -5.263158e-02 -2.608696e-01 81 -5.263158e-02 -5.263158e-02 82 -5.263158e-02 -5.263158e-02 83 9.473684e-01 -5.263158e-02 84 -5.263158e-02 9.473684e-01 85 -5.263158e-02 -5.263158e-02 86 -5.263158e-02 -5.263158e-02 87 -3.301734e-18 -5.263158e-02 88 -5.263158e-02 -3.301734e-18 89 -5.263158e-02 -5.263158e-02 90 -5.263158e-02 -5.263158e-02 91 -3.301734e-18 -5.263158e-02 92 -5.263158e-02 -3.301734e-18 93 -5.263158e-02 -5.263158e-02 94 -3.301734e-18 -5.263158e-02 95 -5.263158e-02 -3.301734e-18 96 -3.301734e-18 -5.263158e-02 97 -5.263158e-02 -3.301734e-18 98 -5.263158e-02 -5.263158e-02 99 -5.263158e-02 -5.263158e-02 100 -5.263158e-02 -5.263158e-02 101 -5.263158e-02 -5.263158e-02 102 -5.263158e-02 -5.263158e-02 103 -5.263158e-02 -5.263158e-02 104 -3.301734e-18 -5.263158e-02 105 -5.263158e-02 -3.301734e-18 106 -5.263158e-02 -5.263158e-02 107 -3.301734e-18 -5.263158e-02 108 -5.263158e-02 -3.301734e-18 109 -5.263158e-02 -5.263158e-02 110 -3.301734e-18 -5.263158e-02 111 -3.301734e-18 -3.301734e-18 112 -5.263158e-02 -3.301734e-18 113 -3.301734e-18 -5.263158e-02 114 -5.263158e-02 -3.301734e-18 115 -5.263158e-02 -5.263158e-02 116 -5.263158e-02 -5.263158e-02 117 -5.263158e-02 -5.263158e-02 118 -5.263158e-02 -5.263158e-02 119 -5.263158e-02 -5.263158e-02 120 -5.263158e-02 -5.263158e-02 121 -5.263158e-02 -5.263158e-02 122 -3.301734e-18 -5.263158e-02 123 -5.263158e-02 -3.301734e-18 124 -5.263158e-02 -5.263158e-02 125 -3.301734e-18 -5.263158e-02 126 -5.263158e-02 -3.301734e-18 127 -5.263158e-02 -5.263158e-02 128 -5.263158e-02 -5.263158e-02 129 -5.263158e-02 -5.263158e-02 130 -5.263158e-02 -5.263158e-02 131 -5.263158e-02 -5.263158e-02 132 -5.263158e-02 -5.263158e-02 133 -5.263158e-02 -5.263158e-02 134 -5.263158e-02 -5.263158e-02 135 -5.263158e-02 -5.263158e-02 136 -5.263158e-02 -5.263158e-02 137 -3.301734e-18 -5.263158e-02 138 -3.301734e-18 -3.301734e-18 139 -5.263158e-02 -3.301734e-18 140 9.473684e-01 -5.263158e-02 141 -3.301734e-18 9.473684e-01 142 -5.263158e-02 -3.301734e-18 143 -5.263158e-02 -5.263158e-02 144 -5.263158e-02 -5.263158e-02 145 -3.301734e-18 -5.263158e-02 146 -3.301734e-18 -3.301734e-18 147 -3.301734e-18 -3.301734e-18 148 -5.263158e-02 -3.301734e-18 149 -5.263158e-02 -5.263158e-02 150 -5.263158e-02 -5.263158e-02 151 9.473684e-01 -5.263158e-02 152 9.473684e-01 9.473684e-01 153 -5.263158e-02 9.473684e-01 154 NA -5.263158e-02 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -5.263158e-02 -2.608696e-01 [2,] -5.263158e-02 -5.263158e-02 [3,] -5.263158e-02 -5.263158e-02 [4,] -5.263158e-02 -5.263158e-02 [5,] -5.263158e-02 -5.263158e-02 [6,] -5.263158e-02 -5.263158e-02 [7,] -2.608696e-01 -5.263158e-02 [8,] -5.263158e-02 -2.608696e-01 [9,] -5.263158e-02 -5.263158e-02 [10,] -2.608696e-01 -5.263158e-02 [11,] -5.263158e-02 -2.608696e-01 [12,] -5.263158e-02 -5.263158e-02 [13,] -2.608696e-01 -5.263158e-02 [14,] -5.263158e-02 -2.608696e-01 [15,] -2.608696e-01 -5.263158e-02 [16,] 7.391304e-01 -2.608696e-01 [17,] -2.608696e-01 7.391304e-01 [18,] -5.263158e-02 -2.608696e-01 [19,] 7.391304e-01 -5.263158e-02 [20,] -5.263158e-02 7.391304e-01 [21,] -5.263158e-02 -5.263158e-02 [22,] -5.263158e-02 -5.263158e-02 [23,] -5.263158e-02 -5.263158e-02 [24,] -2.608696e-01 -5.263158e-02 [25,] -5.263158e-02 -2.608696e-01 [26,] -5.263158e-02 -5.263158e-02 [27,] -5.263158e-02 -5.263158e-02 [28,] -5.263158e-02 -5.263158e-02 [29,] -5.263158e-02 -5.263158e-02 [30,] -5.263158e-02 -5.263158e-02 [31,] -5.263158e-02 -5.263158e-02 [32,] -5.263158e-02 -5.263158e-02 [33,] -2.608696e-01 -5.263158e-02 [34,] -5.263158e-02 -2.608696e-01 [35,] -5.263158e-02 -5.263158e-02 [36,] -2.608696e-01 -5.263158e-02 [37,] -5.263158e-02 -2.608696e-01 [38,] -5.263158e-02 -5.263158e-02 [39,] -2.608696e-01 -5.263158e-02 [40,] 9.473684e-01 -2.608696e-01 [41,] -5.263158e-02 9.473684e-01 [42,] -5.263158e-02 -5.263158e-02 [43,] -2.608696e-01 -5.263158e-02 [44,] -5.263158e-02 -2.608696e-01 [45,] -5.263158e-02 -5.263158e-02 [46,] -5.263158e-02 -5.263158e-02 [47,] -5.263158e-02 -5.263158e-02 [48,] -5.263158e-02 -5.263158e-02 [49,] -5.263158e-02 -5.263158e-02 [50,] -2.608696e-01 -5.263158e-02 [51,] 7.391304e-01 -2.608696e-01 [52,] -5.263158e-02 7.391304e-01 [53,] 9.473684e-01 -5.263158e-02 [54,] -5.263158e-02 9.473684e-01 [55,] -2.608696e-01 -5.263158e-02 [56,] -5.263158e-02 -2.608696e-01 [57,] -5.263158e-02 -5.263158e-02 [58,] -5.263158e-02 -5.263158e-02 [59,] 7.391304e-01 -5.263158e-02 [60,] -2.608696e-01 7.391304e-01 [61,] -5.263158e-02 -2.608696e-01 [62,] -5.263158e-02 -5.263158e-02 [63,] -2.608696e-01 -5.263158e-02 [64,] -5.263158e-02 -2.608696e-01 [65,] -5.263158e-02 -5.263158e-02 [66,] 7.391304e-01 -5.263158e-02 [67,] -5.263158e-02 7.391304e-01 [68,] -5.263158e-02 -5.263158e-02 [69,] -5.263158e-02 -5.263158e-02 [70,] -5.263158e-02 -5.263158e-02 [71,] -5.263158e-02 -5.263158e-02 [72,] -5.263158e-02 -5.263158e-02 [73,] -5.263158e-02 -5.263158e-02 [74,] -5.263158e-02 -5.263158e-02 [75,] -2.608696e-01 -5.263158e-02 [76,] -5.263158e-02 -2.608696e-01 [77,] -5.263158e-02 -5.263158e-02 [78,] 7.391304e-01 -5.263158e-02 [79,] -2.608696e-01 7.391304e-01 [80,] -5.263158e-02 -2.608696e-01 [81,] -5.263158e-02 -5.263158e-02 [82,] -5.263158e-02 -5.263158e-02 [83,] 9.473684e-01 -5.263158e-02 [84,] -5.263158e-02 9.473684e-01 [85,] -5.263158e-02 -5.263158e-02 [86,] -5.263158e-02 -5.263158e-02 [87,] -3.301734e-18 -5.263158e-02 [88,] -5.263158e-02 -3.301734e-18 [89,] -5.263158e-02 -5.263158e-02 [90,] -5.263158e-02 -5.263158e-02 [91,] -3.301734e-18 -5.263158e-02 [92,] -5.263158e-02 -3.301734e-18 [93,] -5.263158e-02 -5.263158e-02 [94,] -3.301734e-18 -5.263158e-02 [95,] -5.263158e-02 -3.301734e-18 [96,] -3.301734e-18 -5.263158e-02 [97,] -5.263158e-02 -3.301734e-18 [98,] -5.263158e-02 -5.263158e-02 [99,] -5.263158e-02 -5.263158e-02 [100,] -5.263158e-02 -5.263158e-02 [101,] -5.263158e-02 -5.263158e-02 [102,] -5.263158e-02 -5.263158e-02 [103,] -5.263158e-02 -5.263158e-02 [104,] -3.301734e-18 -5.263158e-02 [105,] -5.263158e-02 -3.301734e-18 [106,] -5.263158e-02 -5.263158e-02 [107,] -3.301734e-18 -5.263158e-02 [108,] -5.263158e-02 -3.301734e-18 [109,] -5.263158e-02 -5.263158e-02 [110,] -3.301734e-18 -5.263158e-02 [111,] -3.301734e-18 -3.301734e-18 [112,] -5.263158e-02 -3.301734e-18 [113,] -3.301734e-18 -5.263158e-02 [114,] -5.263158e-02 -3.301734e-18 [115,] -5.263158e-02 -5.263158e-02 [116,] -5.263158e-02 -5.263158e-02 [117,] -5.263158e-02 -5.263158e-02 [118,] -5.263158e-02 -5.263158e-02 [119,] -5.263158e-02 -5.263158e-02 [120,] -5.263158e-02 -5.263158e-02 [121,] -5.263158e-02 -5.263158e-02 [122,] -3.301734e-18 -5.263158e-02 [123,] -5.263158e-02 -3.301734e-18 [124,] -5.263158e-02 -5.263158e-02 [125,] -3.301734e-18 -5.263158e-02 [126,] -5.263158e-02 -3.301734e-18 [127,] -5.263158e-02 -5.263158e-02 [128,] -5.263158e-02 -5.263158e-02 [129,] -5.263158e-02 -5.263158e-02 [130,] -5.263158e-02 -5.263158e-02 [131,] -5.263158e-02 -5.263158e-02 [132,] -5.263158e-02 -5.263158e-02 [133,] -5.263158e-02 -5.263158e-02 [134,] -5.263158e-02 -5.263158e-02 [135,] -5.263158e-02 -5.263158e-02 [136,] -5.263158e-02 -5.263158e-02 [137,] -3.301734e-18 -5.263158e-02 [138,] -3.301734e-18 -3.301734e-18 [139,] -5.263158e-02 -3.301734e-18 [140,] 9.473684e-01 -5.263158e-02 [141,] -3.301734e-18 9.473684e-01 [142,] -5.263158e-02 -3.301734e-18 [143,] -5.263158e-02 -5.263158e-02 [144,] -5.263158e-02 -5.263158e-02 [145,] -3.301734e-18 -5.263158e-02 [146,] -3.301734e-18 -3.301734e-18 [147,] -3.301734e-18 -3.301734e-18 [148,] -5.263158e-02 -3.301734e-18 [149,] -5.263158e-02 -5.263158e-02 [150,] -5.263158e-02 -5.263158e-02 [151,] 9.473684e-01 -5.263158e-02 [152,] 9.473684e-01 9.473684e-01 [153,] -5.263158e-02 9.473684e-01 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -5.263158e-02 -2.608696e-01 2 -5.263158e-02 -5.263158e-02 3 -5.263158e-02 -5.263158e-02 4 -5.263158e-02 -5.263158e-02 5 -5.263158e-02 -5.263158e-02 6 -5.263158e-02 -5.263158e-02 7 -2.608696e-01 -5.263158e-02 8 -5.263158e-02 -2.608696e-01 9 -5.263158e-02 -5.263158e-02 10 -2.608696e-01 -5.263158e-02 11 -5.263158e-02 -2.608696e-01 12 -5.263158e-02 -5.263158e-02 13 -2.608696e-01 -5.263158e-02 14 -5.263158e-02 -2.608696e-01 15 -2.608696e-01 -5.263158e-02 16 7.391304e-01 -2.608696e-01 17 -2.608696e-01 7.391304e-01 18 -5.263158e-02 -2.608696e-01 19 7.391304e-01 -5.263158e-02 20 -5.263158e-02 7.391304e-01 21 -5.263158e-02 -5.263158e-02 22 -5.263158e-02 -5.263158e-02 23 -5.263158e-02 -5.263158e-02 24 -2.608696e-01 -5.263158e-02 25 -5.263158e-02 -2.608696e-01 26 -5.263158e-02 -5.263158e-02 27 -5.263158e-02 -5.263158e-02 28 -5.263158e-02 -5.263158e-02 29 -5.263158e-02 -5.263158e-02 30 -5.263158e-02 -5.263158e-02 31 -5.263158e-02 -5.263158e-02 32 -5.263158e-02 -5.263158e-02 33 -2.608696e-01 -5.263158e-02 34 -5.263158e-02 -2.608696e-01 35 -5.263158e-02 -5.263158e-02 36 -2.608696e-01 -5.263158e-02 37 -5.263158e-02 -2.608696e-01 38 -5.263158e-02 -5.263158e-02 39 -2.608696e-01 -5.263158e-02 40 9.473684e-01 -2.608696e-01 41 -5.263158e-02 9.473684e-01 42 -5.263158e-02 -5.263158e-02 43 -2.608696e-01 -5.263158e-02 44 -5.263158e-02 -2.608696e-01 45 -5.263158e-02 -5.263158e-02 46 -5.263158e-02 -5.263158e-02 47 -5.263158e-02 -5.263158e-02 48 -5.263158e-02 -5.263158e-02 49 -5.263158e-02 -5.263158e-02 50 -2.608696e-01 -5.263158e-02 51 7.391304e-01 -2.608696e-01 52 -5.263158e-02 7.391304e-01 53 9.473684e-01 -5.263158e-02 54 -5.263158e-02 9.473684e-01 55 -2.608696e-01 -5.263158e-02 56 -5.263158e-02 -2.608696e-01 57 -5.263158e-02 -5.263158e-02 58 -5.263158e-02 -5.263158e-02 59 7.391304e-01 -5.263158e-02 60 -2.608696e-01 7.391304e-01 61 -5.263158e-02 -2.608696e-01 62 -5.263158e-02 -5.263158e-02 63 -2.608696e-01 -5.263158e-02 64 -5.263158e-02 -2.608696e-01 65 -5.263158e-02 -5.263158e-02 66 7.391304e-01 -5.263158e-02 67 -5.263158e-02 7.391304e-01 68 -5.263158e-02 -5.263158e-02 69 -5.263158e-02 -5.263158e-02 70 -5.263158e-02 -5.263158e-02 71 -5.263158e-02 -5.263158e-02 72 -5.263158e-02 -5.263158e-02 73 -5.263158e-02 -5.263158e-02 74 -5.263158e-02 -5.263158e-02 75 -2.608696e-01 -5.263158e-02 76 -5.263158e-02 -2.608696e-01 77 -5.263158e-02 -5.263158e-02 78 7.391304e-01 -5.263158e-02 79 -2.608696e-01 7.391304e-01 80 -5.263158e-02 -2.608696e-01 81 -5.263158e-02 -5.263158e-02 82 -5.263158e-02 -5.263158e-02 83 9.473684e-01 -5.263158e-02 84 -5.263158e-02 9.473684e-01 85 -5.263158e-02 -5.263158e-02 86 -5.263158e-02 -5.263158e-02 87 -3.301734e-18 -5.263158e-02 88 -5.263158e-02 -3.301734e-18 89 -5.263158e-02 -5.263158e-02 90 -5.263158e-02 -5.263158e-02 91 -3.301734e-18 -5.263158e-02 92 -5.263158e-02 -3.301734e-18 93 -5.263158e-02 -5.263158e-02 94 -3.301734e-18 -5.263158e-02 95 -5.263158e-02 -3.301734e-18 96 -3.301734e-18 -5.263158e-02 97 -5.263158e-02 -3.301734e-18 98 -5.263158e-02 -5.263158e-02 99 -5.263158e-02 -5.263158e-02 100 -5.263158e-02 -5.263158e-02 101 -5.263158e-02 -5.263158e-02 102 -5.263158e-02 -5.263158e-02 103 -5.263158e-02 -5.263158e-02 104 -3.301734e-18 -5.263158e-02 105 -5.263158e-02 -3.301734e-18 106 -5.263158e-02 -5.263158e-02 107 -3.301734e-18 -5.263158e-02 108 -5.263158e-02 -3.301734e-18 109 -5.263158e-02 -5.263158e-02 110 -3.301734e-18 -5.263158e-02 111 -3.301734e-18 -3.301734e-18 112 -5.263158e-02 -3.301734e-18 113 -3.301734e-18 -5.263158e-02 114 -5.263158e-02 -3.301734e-18 115 -5.263158e-02 -5.263158e-02 116 -5.263158e-02 -5.263158e-02 117 -5.263158e-02 -5.263158e-02 118 -5.263158e-02 -5.263158e-02 119 -5.263158e-02 -5.263158e-02 120 -5.263158e-02 -5.263158e-02 121 -5.263158e-02 -5.263158e-02 122 -3.301734e-18 -5.263158e-02 123 -5.263158e-02 -3.301734e-18 124 -5.263158e-02 -5.263158e-02 125 -3.301734e-18 -5.263158e-02 126 -5.263158e-02 -3.301734e-18 127 -5.263158e-02 -5.263158e-02 128 -5.263158e-02 -5.263158e-02 129 -5.263158e-02 -5.263158e-02 130 -5.263158e-02 -5.263158e-02 131 -5.263158e-02 -5.263158e-02 132 -5.263158e-02 -5.263158e-02 133 -5.263158e-02 -5.263158e-02 134 -5.263158e-02 -5.263158e-02 135 -5.263158e-02 -5.263158e-02 136 -5.263158e-02 -5.263158e-02 137 -3.301734e-18 -5.263158e-02 138 -3.301734e-18 -3.301734e-18 139 -5.263158e-02 -3.301734e-18 140 9.473684e-01 -5.263158e-02 141 -3.301734e-18 9.473684e-01 142 -5.263158e-02 -3.301734e-18 143 -5.263158e-02 -5.263158e-02 144 -5.263158e-02 -5.263158e-02 145 -3.301734e-18 -5.263158e-02 146 -3.301734e-18 -3.301734e-18 147 -3.301734e-18 -3.301734e-18 148 -5.263158e-02 -3.301734e-18 149 -5.263158e-02 -5.263158e-02 150 -5.263158e-02 -5.263158e-02 151 9.473684e-01 -5.263158e-02 152 9.473684e-01 9.473684e-01 153 -5.263158e-02 9.473684e-01 > 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/7rehz1356206642.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/85zvd1356206642.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/9wi7n1356206642.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/10qr1y1356206642.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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/11fpe91356206642.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/12efkf1356206642.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$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$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/13i3uc1356206642.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$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/14f6ls1356206642.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/15rge21356206642.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/164c0z1356206642.tab") + } > > try(system("convert tmp/1gj3f1356206641.ps tmp/1gj3f1356206641.png",intern=TRUE)) character(0) > try(system("convert tmp/2whih1356206641.ps tmp/2whih1356206641.png",intern=TRUE)) character(0) > try(system("convert tmp/35zr51356206641.ps tmp/35zr51356206641.png",intern=TRUE)) character(0) > try(system("convert tmp/4f2yf1356206641.ps tmp/4f2yf1356206641.png",intern=TRUE)) character(0) > try(system("convert tmp/5lw5x1356206641.ps tmp/5lw5x1356206641.png",intern=TRUE)) character(0) > try(system("convert tmp/6nmz21356206641.ps tmp/6nmz21356206641.png",intern=TRUE)) character(0) > try(system("convert tmp/7rehz1356206642.ps tmp/7rehz1356206642.png",intern=TRUE)) character(0) > try(system("convert tmp/85zvd1356206642.ps tmp/85zvd1356206642.png",intern=TRUE)) character(0) > try(system("convert tmp/9wi7n1356206642.ps tmp/9wi7n1356206642.png",intern=TRUE)) character(0) > try(system("convert tmp/10qr1y1356206642.ps tmp/10qr1y1356206642.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 10.035 1.146 11.218