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Type 'q()' to quit R. > x <- array(list(95556 + ,114468 + ,54565 + ,88594 + ,63016 + ,74151 + ,79774 + ,77921 + ,31258 + ,53212 + ,52491 + ,34956 + ,91256 + ,149703 + ,22807 + ,6853 + ,77411 + ,58907 + ,48821 + ,67067 + ,52295 + ,110563 + ,63262 + ,58126 + ,50466 + ,57113 + ,62932 + ,77993 + ,38439 + ,68091 + ,70817 + ,124676 + ,105965 + ,109522 + ,73795 + ,75865 + ,82043 + ,79746 + ,74349 + ,77844 + ,82204 + ,98681 + ,55709 + ,105531 + ,37137 + ,51428 + ,70780 + ,65703 + ,55027 + ,72562 + ,56699 + ,81728 + ,65911 + ,95580 + ,56316 + ,98278 + ,26982 + ,46629 + ,54628 + ,115189 + ,96750 + ,124865 + ,53009 + ,59392 + ,64664 + ,127818 + ,36990 + ,17821 + ,85224 + ,154076 + ,37048 + ,64881 + ,59635 + ,136506 + ,42051 + ,66524 + ,26998 + ,45988 + ,63717 + ,107445 + ,55071 + ,102772 + ,40001 + ,46657 + ,54506 + ,97563 + ,35838 + ,36663 + ,50838 + ,55369 + ,86997 + ,77921 + ,33032 + ,56968 + ,61704 + ,77519 + ,117986 + ,129805 + ,56733 + ,72761 + ,55064 + ,81278 + ,5950 + ,15049 + ,84607 + ,113935 + ,32551 + ,25109 + ,31701 + ,45824 + ,71170 + ,89644 + ,101773 + ,109011 + ,101653 + ,134245 + ,81493 + ,136692 + ,55901 + ,50741 + ,109104 + ,149510 + ,114425 + ,147888 + ,36311 + ,54987 + ,70027 + ,74467 + ,73713 + ,100033 + ,40671 + ,85505 + ,89041 + ,62426 + ,57231 + ,82932 + ,68608 + ,72002 + ,59155 + ,65469 + ,55827 + ,63572 + ,22618 + ,23824 + ,58425 + ,73831 + ,65724 + ,63551 + ,56979 + ,56756 + ,72369 + ,81399 + ,79194 + ,117881 + ,202316 + ,70711 + ,44970 + ,50495 + ,49319 + ,53845 + ,36252 + ,51390 + ,75741 + ,104953 + ,38417 + ,65983 + ,64102 + ,76839 + ,56622 + ,55792 + ,15430 + ,25155 + ,72571 + ,55291 + ,67271 + ,84279 + ,43460 + ,99692 + ,99501 + ,59633 + ,28340 + ,63249 + ,76013 + ,82928 + ,37361 + ,50000 + ,48204 + ,69455 + ,76168 + ,84068 + ,85168 + ,76195 + ,125410 + ,114634 + ,123328 + ,139357 + ,83038 + ,110044 + ,120087 + ,155118 + ,91939 + ,83061 + ,103646 + ,127122 + ,29467 + ,45653 + ,43750 + ,19630 + ,34497 + ,67229 + ,66477 + ,86060 + ,71181 + ,88003 + ,74482 + ,95815 + ,174949 + ,85499 + ,46765 + ,27220 + ,90257 + ,109882 + ,51370 + ,72579 + ,1168 + ,5841 + ,51360 + ,68369 + ,25162 + ,24610 + ,21067 + ,30995 + ,58233 + ,150662 + ,855 + ,6622 + ,85903 + ,93694 + ,14116 + ,13155 + ,57637 + ,111908 + ,94137 + ,57550 + ,62147 + ,16356 + ,62832 + ,40174 + ,8773 + ,13983 + ,63785 + ,52316 + ,65196 + ,99585 + ,73087 + ,86271 + ,72631 + ,131012 + ,86281 + ,130274 + ,162365 + ,159051 + ,56530 + ,76506 + ,35606 + ,49145 + ,70111 + ,66398 + ,92046 + ,127546 + ,63989 + ,6802 + ,104911 + ,99509 + ,43448 + ,43106 + ,60029 + ,108303 + ,38650 + ,64167 + ,47261 + ,8579 + ,73586 + ,97811 + ,83042 + ,84365 + ,37238 + ,10901 + ,63958 + ,91346 + ,78956 + ,33660 + ,99518 + ,93634 + ,111436 + ,109348 + ,0 + ,0 + ,6023 + ,7953 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,0 + ,42564 + ,63538 + ,38885 + ,108281 + ,0 + ,0 + ,0 + ,0 + ,1644 + ,4245 + ,6179 + ,21509 + ,3926 + ,7670 + ,23238 + ,10641 + ,0 + ,0 + ,49288 + ,41243) + ,dim=c(2 + ,164) + ,dimnames=list(c('NumberCharacter' + ,'Numberseconds') + ,1:164)) > y <- array(NA,dim=c(2,164),dimnames=list(c('NumberCharacter','Numberseconds'),1:164)) > 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 NumberCharacter Numberseconds 1 95556 114468 2 54565 88594 3 63016 74151 4 79774 77921 5 31258 53212 6 52491 34956 7 91256 149703 8 22807 6853 9 77411 58907 10 48821 67067 11 52295 110563 12 63262 58126 13 50466 57113 14 62932 77993 15 38439 68091 16 70817 124676 17 105965 109522 18 73795 75865 19 82043 79746 20 74349 77844 21 82204 98681 22 55709 105531 23 37137 51428 24 70780 65703 25 55027 72562 26 56699 81728 27 65911 95580 28 56316 98278 29 26982 46629 30 54628 115189 31 96750 124865 32 53009 59392 33 64664 127818 34 36990 17821 35 85224 154076 36 37048 64881 37 59635 136506 38 42051 66524 39 26998 45988 40 63717 107445 41 55071 102772 42 40001 46657 43 54506 97563 44 35838 36663 45 50838 55369 46 86997 77921 47 33032 56968 48 61704 77519 49 117986 129805 50 56733 72761 51 55064 81278 52 5950 15049 53 84607 113935 54 32551 25109 55 31701 45824 56 71170 89644 57 101773 109011 58 101653 134245 59 81493 136692 60 55901 50741 61 109104 149510 62 114425 147888 63 36311 54987 64 70027 74467 65 73713 100033 66 40671 85505 67 89041 62426 68 57231 82932 69 68608 72002 70 59155 65469 71 55827 63572 72 22618 23824 73 58425 73831 74 65724 63551 75 56979 56756 76 72369 81399 77 79194 117881 78 202316 70711 79 44970 50495 80 49319 53845 81 36252 51390 82 75741 104953 83 38417 65983 84 64102 76839 85 56622 55792 86 15430 25155 87 72571 55291 88 67271 84279 89 43460 99692 90 99501 59633 91 28340 63249 92 76013 82928 93 37361 50000 94 48204 69455 95 76168 84068 96 85168 76195 97 125410 114634 98 123328 139357 99 83038 110044 100 120087 155118 101 91939 83061 102 103646 127122 103 29467 45653 104 43750 19630 105 34497 67229 106 66477 86060 107 71181 88003 108 74482 95815 109 174949 85499 110 46765 27220 111 90257 109882 112 51370 72579 113 1168 5841 114 51360 68369 115 25162 24610 116 21067 30995 117 58233 150662 118 855 6622 119 85903 93694 120 14116 13155 121 57637 111908 122 94137 57550 123 62147 16356 124 62832 40174 125 8773 13983 126 63785 52316 127 65196 99585 128 73087 86271 129 72631 131012 130 86281 130274 131 162365 159051 132 56530 76506 133 35606 49145 134 70111 66398 135 92046 127546 136 63989 6802 137 104911 99509 138 43448 43106 139 60029 108303 140 38650 64167 141 47261 8579 142 73586 97811 143 83042 84365 144 37238 10901 145 63958 91346 146 78956 33660 147 99518 93634 148 111436 109348 149 0 0 150 6023 7953 151 0 0 152 0 0 153 0 0 154 0 0 155 42564 63538 156 38885 108281 157 0 0 158 0 0 159 1644 4245 160 6179 21509 161 3926 7670 162 23238 10641 163 0 0 164 49288 41243 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Numberseconds 1.585e+04 6.093e-01 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -49412 -15854 -1834 10041 143381 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.585e+04 3.706e+03 4.278 3.21e-05 *** Numberseconds 6.092e-01 4.547e-02 13.400 < 2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 23150 on 162 degrees of freedom Multiple R-squared: 0.5257, Adjusted R-squared: 0.5228 F-statistic: 179.6 on 1 and 162 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,] 2.639984e-01 5.279968e-01 0.7360015821 [2,] 2.680800e-01 5.361600e-01 0.7319199750 [3,] 1.840000e-01 3.679999e-01 0.8160000337 [4,] 1.069639e-01 2.139277e-01 0.8930361408 [5,] 1.353308e-01 2.706615e-01 0.8646692434 [6,] 9.398276e-02 1.879655e-01 0.9060172356 [7,] 1.336704e-01 2.673408e-01 0.8663295762 [8,] 9.425398e-02 1.885080e-01 0.9057460237 [9,] 5.846330e-02 1.169266e-01 0.9415366994 [10,] 3.450430e-02 6.900860e-02 0.9654956999 [11,] 3.483121e-02 6.966241e-02 0.9651687934 [12,] 2.375339e-02 4.750677e-02 0.9762466131 [13,] 5.098044e-02 1.019609e-01 0.9490195642 [14,] 3.854846e-02 7.709692e-02 0.9614515413 [15,] 3.549078e-02 7.098157e-02 0.9645092161 [16,] 2.548548e-02 5.097096e-02 0.9745145216 [17,] 1.719281e-02 3.438562e-02 0.9828071912 [18,] 1.883161e-02 3.766323e-02 0.9811683856 [19,] 1.519560e-02 3.039121e-02 0.9848043967 [20,] 1.168505e-02 2.337010e-02 0.9883149480 [21,] 7.547671e-03 1.509534e-02 0.9924523290 [22,] 5.024362e-03 1.004872e-02 0.9949756375 [23,] 3.110884e-03 6.221767e-03 0.9968891163 [24,] 2.631212e-03 5.262425e-03 0.9973687876 [25,] 2.918241e-03 5.836482e-03 0.9970817591 [26,] 3.860993e-03 7.721986e-03 0.9961390071 [27,] 3.099488e-03 6.198977e-03 0.9969005117 [28,] 1.877681e-03 3.755363e-03 0.9981223186 [29,] 1.922563e-03 3.845126e-03 0.9980774372 [30,] 1.174872e-03 2.349743e-03 0.9988251284 [31,] 8.244590e-04 1.648918e-03 0.9991755410 [32,] 7.901084e-04 1.580217e-03 0.9992098916 [33,] 1.243050e-03 2.486099e-03 0.9987569503 [34,] 9.640316e-04 1.928063e-03 0.9990359684 [35,] 9.641461e-04 1.928292e-03 0.9990358539 [36,] 6.636353e-04 1.327271e-03 0.9993363647 [37,] 5.577814e-04 1.115563e-03 0.9994422186 [38,] 3.503455e-04 7.006911e-04 0.9996496545 [39,] 2.715016e-04 5.430031e-04 0.9997284984 [40,] 1.667068e-04 3.334137e-04 0.9998332932 [41,] 9.729453e-05 1.945891e-04 0.9999027055 [42,] 1.836994e-04 3.673988e-04 0.9998163006 [43,] 1.653632e-04 3.307264e-04 0.9998346368 [44,] 9.961357e-05 1.992271e-04 0.9999003864 [45,] 3.284253e-04 6.568506e-04 0.9996715747 [46,] 2.018194e-04 4.036388e-04 0.9997981806 [47,] 1.298040e-04 2.596080e-04 0.9998701960 [48,] 1.578371e-04 3.156743e-04 0.9998421629 [49,] 1.054937e-04 2.109874e-04 0.9998945063 [50,] 6.290603e-05 1.258121e-04 0.9999370940 [51,] 4.452969e-05 8.905938e-05 0.9999554703 [52,] 2.779402e-05 5.558804e-05 0.9999722060 [53,] 4.261779e-05 8.523557e-05 0.9999573822 [54,] 3.184683e-05 6.369366e-05 0.9999681532 [55,] 2.266474e-05 4.532949e-05 0.9999773353 [56,] 1.518842e-05 3.037684e-05 0.9999848116 [57,] 1.106029e-05 2.212058e-05 0.9999889397 [58,] 9.589863e-06 1.917973e-05 0.9999904101 [59,] 6.677276e-06 1.335455e-05 0.9999933227 [60,] 4.603041e-06 9.206082e-06 0.9999953970 [61,] 2.657895e-06 5.315791e-06 0.9999973421 [62,] 3.625337e-06 7.250673e-06 0.9999963747 [63,] 1.327344e-05 2.654689e-05 0.9999867266 [64,] 8.365740e-06 1.673148e-05 0.9999916343 [65,] 5.684217e-06 1.136843e-05 0.9999943158 [66,] 3.379853e-06 6.759706e-06 0.9999966201 [67,] 1.941810e-06 3.883621e-06 0.9999980582 [68,] 1.219859e-06 2.439719e-06 0.9999987801 [69,] 6.853964e-07 1.370793e-06 0.9999993146 [70,] 4.733949e-07 9.467898e-07 0.9999995266 [71,] 2.794653e-07 5.589306e-07 0.9999997205 [72,] 1.722046e-07 3.444092e-07 0.9999998278 [73,] 9.998433e-08 1.999687e-07 0.9999999000 [74,] 3.396089e-01 6.792178e-01 0.6603911106 [75,] 3.000270e-01 6.000540e-01 0.6999730185 [76,] 2.621214e-01 5.242428e-01 0.7378786022 [77,] 2.361830e-01 4.723659e-01 0.7638170385 [78,] 2.049941e-01 4.099882e-01 0.7950059021 [79,] 1.937198e-01 3.874396e-01 0.8062802026 [80,] 1.646434e-01 3.292869e-01 0.8353565612 [81,] 1.398690e-01 2.797380e-01 0.8601309939 [82,] 1.294014e-01 2.588029e-01 0.8705985581 [83,] 1.275268e-01 2.550536e-01 0.8724732097 [84,] 1.058082e-01 2.116164e-01 0.8941918142 [85,] 1.311974e-01 2.623947e-01 0.8688026281 [86,] 2.174684e-01 4.349369e-01 0.7825315561 [87,] 2.303885e-01 4.607771e-01 0.7696114549 [88,] 2.025011e-01 4.050022e-01 0.7974988837 [89,] 1.778205e-01 3.556411e-01 0.8221794713 [90,] 1.561581e-01 3.123161e-01 0.8438419397 [91,] 1.339649e-01 2.679297e-01 0.8660351487 [92,] 1.313879e-01 2.627758e-01 0.8686121128 [93,] 1.812659e-01 3.625319e-01 0.8187340632 [94,] 1.790776e-01 3.581552e-01 0.8209224150 [95,] 1.513409e-01 3.026818e-01 0.8486591112 [96,] 1.307726e-01 2.615452e-01 0.8692273823 [97,] 1.331916e-01 2.663833e-01 0.8668083587 [98,] 1.139485e-01 2.278970e-01 0.8860515113 [99,] 1.010644e-01 2.021288e-01 0.8989355922 [100,] 9.010293e-02 1.802059e-01 0.9098970737 [101,] 8.919939e-02 1.783988e-01 0.9108006138 [102,] 7.218668e-02 1.443734e-01 0.9278133212 [103,] 5.757744e-02 1.151549e-01 0.9424225568 [104,] 4.540983e-02 9.081967e-02 0.9545901662 [105,] 7.343563e-01 5.312874e-01 0.2656436791 [106,] 7.115250e-01 5.769500e-01 0.2884750018 [107,] 6.736774e-01 6.526453e-01 0.3263226251 [108,] 6.345459e-01 7.309081e-01 0.3654540541 [109,] 6.151181e-01 7.697638e-01 0.3848819091 [110,] 5.704051e-01 8.591899e-01 0.4295949265 [111,] 5.241066e-01 9.517868e-01 0.4758934159 [112,] 4.903858e-01 9.807716e-01 0.5096142098 [113,] 6.816902e-01 6.366197e-01 0.3183098441 [114,] 6.640129e-01 6.719741e-01 0.3359870726 [115,] 6.276855e-01 7.446291e-01 0.3723145351 [116,] 5.859755e-01 8.280489e-01 0.4140244580 [117,] 6.179620e-01 7.640760e-01 0.3820379847 [118,] 7.307378e-01 5.385245e-01 0.2692622293 [119,] 8.055561e-01 3.888879e-01 0.1944439454 [120,] 8.101916e-01 3.796168e-01 0.1898083787 [121,] 7.849969e-01 4.300062e-01 0.2150031245 [122,] 7.669961e-01 4.660078e-01 0.2330038755 [123,] 7.390208e-01 5.219584e-01 0.2609791922 [124,] 6.928153e-01 6.143695e-01 0.3071847399 [125,] 7.234985e-01 5.530030e-01 0.2765014991 [126,] 7.043951e-01 5.912097e-01 0.2956048525 [127,] 8.111233e-01 3.777534e-01 0.1888766757 [128,] 7.725333e-01 4.549335e-01 0.2274667251 [129,] 7.338576e-01 5.322849e-01 0.2661424393 [130,] 7.015080e-01 5.969841e-01 0.2984920304 [131,] 6.504380e-01 6.991240e-01 0.3495619798 [132,] 8.364775e-01 3.270450e-01 0.1635224892 [133,] 8.565696e-01 2.868608e-01 0.1434303882 [134,] 8.192356e-01 3.615289e-01 0.1807644353 [135,] 8.283873e-01 3.432253e-01 0.1716126574 [136,] 8.082108e-01 3.835783e-01 0.1917891518 [137,] 8.684324e-01 2.631352e-01 0.1315676031 [138,] 8.312181e-01 3.375638e-01 0.1687818877 [139,] 8.014357e-01 3.971287e-01 0.1985643464 [140,] 8.128497e-01 3.743005e-01 0.1871502592 [141,] 7.722753e-01 4.554494e-01 0.2277246854 [142,] 9.565792e-01 8.684153e-02 0.0434207657 [143,] 9.764389e-01 4.712218e-02 0.0235610906 [144,] 9.995426e-01 9.148727e-04 0.0004574363 [145,] 9.989684e-01 2.063205e-03 0.0010316027 [146,] 9.976535e-01 4.692960e-03 0.0023464799 [147,] 9.950173e-01 9.965355e-03 0.0049826777 [148,] 9.897924e-01 2.041514e-02 0.0102075715 [149,] 9.799059e-01 4.018827e-02 0.0200941344 [150,] 9.621648e-01 7.567030e-02 0.0378351518 [151,] 9.419738e-01 1.160525e-01 0.0580262362 [152,] 9.901899e-01 1.962011e-02 0.0098100558 [153,] 9.728232e-01 5.435354e-02 0.0271767684 [154,] 9.302938e-01 1.394124e-01 0.0697062206 [155,] 8.365745e-01 3.268510e-01 0.1634254859 > postscript(file="/var/www/rcomp/tmp/1h5r71321897242.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/28mh31321897242.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/rcomp/tmp/3yre31321897242.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/4w2jq1321897242.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/58zlb1321897242.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 = 164 Frequency = 1 1 2 3 4 5 6 9962.08755 -15265.11974 1985.31049 16446.42951 -17015.55666 15339.95241 7 8 9 10 11 12 -15804.91545 2777.76837 25667.75178 -7893.74657 -30919.78241 11994.57779 13 14 15 16 17 18 -184.24968 -439.43665 -18899.62088 -20996.15941 23384.44918 11720.05214 19 20 21 22 23 24 17603.54416 11068.34194 6228.35282 -24440.02509 -10049.65064 14896.27350 25 26 27 28 29 30 -5035.58768 -8947.99380 -8175.35596 -19414.11853 -17280.84910 -31405.18332 31 32 33 34 35 36 4821.69192 970.26444 -29063.42998 10278.48970 -24501.17554 -18334.92115 37 38 39 40 41 42 -39385.61352 -14332.92260 -16874.31841 -17598.13390 -23397.09814 -4278.90816 43 44 45 46 47 48 -20788.50317 -2353.04118 1250.28624 23669.42951 -17529.90810 -1378.65108 49 50 51 52 53 54 23047.98580 -3450.82888 -10308.83029 -19072.66306 -662.18100 1399.25931 55 56 57 58 59 60 -12071.40104 700.16539 19503.77708 4009.90582 -17640.93444 9132.90565 61 62 63 64 65 66 2160.67023 8469.87738 -13043.97940 8803.78678 -3086.35623 -27277.13955 67 68 69 70 71 72 35153.79312 -9149.53351 8886.59358 3413.83852 1241.59004 -7750.85155 73 74 75 76 77 78 -2410.72879 11151.38434 6546.25337 6922.45019 -8479.29037 143381.13823 79 80 81 82 83 84 -1648.21829 659.78667 -10911.49906 -4055.87729 -17637.31713 1433.64045 85 86 87 88 89 90 6776.57254 -15749.76629 23030.80792 69.80371 -33131.60121 47315.43465 91 92 93 94 95 96 -26048.62148 9634.90350 -8955.63843 -9965.64094 9095.35594 22891.99890 97 98 99 100 101 102 39714.95168 22570.40832 139.41951 9726.98362 25479.87295 10342.60959 103 104 105 106 107 108 -14201.21890 15936.35238 -22316.44544 -1809.27454 1710.94833 252.46976 109 110 111 112 113 114 107004.51597 14327.12781 7457.11837 -8702.94497 -18244.66835 -6147.99300 115 116 117 118 119 120 -5685.72382 -13670.79943 -49412.18836 -19033.49436 12965.69378 -9752.73930 121 122 123 124 125 126 -26397.22669 43220.50709 36328.04425 22501.87417 -15600.20016 16057.33336 127 128 129 130 131 132 -11330.41122 4672.17323 -23042.38166 -8942.75350 49608.79452 -5935.47855 133 134 135 136 137 138 -10189.72776 13803.84318 -1515.71336 43990.84024 28430.89195 1331.54658 139 140 141 142 143 144 -21808.87233 -16297.91505 26180.19899 -1859.59773 15788.40802 14742.51527 145 146 147 148 149 150 -7548.78194 42594.54332 26617.24892 28961.45907 -15854.02596 -14676.40910 151 152 153 154 155 156 -15854.02596 -15854.02596 -15854.02596 -15854.02596 -12000.69538 -42939.46878 157 158 159 160 161 162 -15854.02596 -15854.02596 -16796.30176 -22779.43259 -16600.99071 900.92085 163 164 -15854.02596 8306.58352 > postscript(file="/var/www/rcomp/tmp/6hkd51321897242.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 = 164 Frequency = 1 lag(myerror, k = 1) myerror 0 9962.08755 NA 1 -15265.11974 9962.08755 2 1985.31049 -15265.11974 3 16446.42951 1985.31049 4 -17015.55666 16446.42951 5 15339.95241 -17015.55666 6 -15804.91545 15339.95241 7 2777.76837 -15804.91545 8 25667.75178 2777.76837 9 -7893.74657 25667.75178 10 -30919.78241 -7893.74657 11 11994.57779 -30919.78241 12 -184.24968 11994.57779 13 -439.43665 -184.24968 14 -18899.62088 -439.43665 15 -20996.15941 -18899.62088 16 23384.44918 -20996.15941 17 11720.05214 23384.44918 18 17603.54416 11720.05214 19 11068.34194 17603.54416 20 6228.35282 11068.34194 21 -24440.02509 6228.35282 22 -10049.65064 -24440.02509 23 14896.27350 -10049.65064 24 -5035.58768 14896.27350 25 -8947.99380 -5035.58768 26 -8175.35596 -8947.99380 27 -19414.11853 -8175.35596 28 -17280.84910 -19414.11853 29 -31405.18332 -17280.84910 30 4821.69192 -31405.18332 31 970.26444 4821.69192 32 -29063.42998 970.26444 33 10278.48970 -29063.42998 34 -24501.17554 10278.48970 35 -18334.92115 -24501.17554 36 -39385.61352 -18334.92115 37 -14332.92260 -39385.61352 38 -16874.31841 -14332.92260 39 -17598.13390 -16874.31841 40 -23397.09814 -17598.13390 41 -4278.90816 -23397.09814 42 -20788.50317 -4278.90816 43 -2353.04118 -20788.50317 44 1250.28624 -2353.04118 45 23669.42951 1250.28624 46 -17529.90810 23669.42951 47 -1378.65108 -17529.90810 48 23047.98580 -1378.65108 49 -3450.82888 23047.98580 50 -10308.83029 -3450.82888 51 -19072.66306 -10308.83029 52 -662.18100 -19072.66306 53 1399.25931 -662.18100 54 -12071.40104 1399.25931 55 700.16539 -12071.40104 56 19503.77708 700.16539 57 4009.90582 19503.77708 58 -17640.93444 4009.90582 59 9132.90565 -17640.93444 60 2160.67023 9132.90565 61 8469.87738 2160.67023 62 -13043.97940 8469.87738 63 8803.78678 -13043.97940 64 -3086.35623 8803.78678 65 -27277.13955 -3086.35623 66 35153.79312 -27277.13955 67 -9149.53351 35153.79312 68 8886.59358 -9149.53351 69 3413.83852 8886.59358 70 1241.59004 3413.83852 71 -7750.85155 1241.59004 72 -2410.72879 -7750.85155 73 11151.38434 -2410.72879 74 6546.25337 11151.38434 75 6922.45019 6546.25337 76 -8479.29037 6922.45019 77 143381.13823 -8479.29037 78 -1648.21829 143381.13823 79 659.78667 -1648.21829 80 -10911.49906 659.78667 81 -4055.87729 -10911.49906 82 -17637.31713 -4055.87729 83 1433.64045 -17637.31713 84 6776.57254 1433.64045 85 -15749.76629 6776.57254 86 23030.80792 -15749.76629 87 69.80371 23030.80792 88 -33131.60121 69.80371 89 47315.43465 -33131.60121 90 -26048.62148 47315.43465 91 9634.90350 -26048.62148 92 -8955.63843 9634.90350 93 -9965.64094 -8955.63843 94 9095.35594 -9965.64094 95 22891.99890 9095.35594 96 39714.95168 22891.99890 97 22570.40832 39714.95168 98 139.41951 22570.40832 99 9726.98362 139.41951 100 25479.87295 9726.98362 101 10342.60959 25479.87295 102 -14201.21890 10342.60959 103 15936.35238 -14201.21890 104 -22316.44544 15936.35238 105 -1809.27454 -22316.44544 106 1710.94833 -1809.27454 107 252.46976 1710.94833 108 107004.51597 252.46976 109 14327.12781 107004.51597 110 7457.11837 14327.12781 111 -8702.94497 7457.11837 112 -18244.66835 -8702.94497 113 -6147.99300 -18244.66835 114 -5685.72382 -6147.99300 115 -13670.79943 -5685.72382 116 -49412.18836 -13670.79943 117 -19033.49436 -49412.18836 118 12965.69378 -19033.49436 119 -9752.73930 12965.69378 120 -26397.22669 -9752.73930 121 43220.50709 -26397.22669 122 36328.04425 43220.50709 123 22501.87417 36328.04425 124 -15600.20016 22501.87417 125 16057.33336 -15600.20016 126 -11330.41122 16057.33336 127 4672.17323 -11330.41122 128 -23042.38166 4672.17323 129 -8942.75350 -23042.38166 130 49608.79452 -8942.75350 131 -5935.47855 49608.79452 132 -10189.72776 -5935.47855 133 13803.84318 -10189.72776 134 -1515.71336 13803.84318 135 43990.84024 -1515.71336 136 28430.89195 43990.84024 137 1331.54658 28430.89195 138 -21808.87233 1331.54658 139 -16297.91505 -21808.87233 140 26180.19899 -16297.91505 141 -1859.59773 26180.19899 142 15788.40802 -1859.59773 143 14742.51527 15788.40802 144 -7548.78194 14742.51527 145 42594.54332 -7548.78194 146 26617.24892 42594.54332 147 28961.45907 26617.24892 148 -15854.02596 28961.45907 149 -14676.40910 -15854.02596 150 -15854.02596 -14676.40910 151 -15854.02596 -15854.02596 152 -15854.02596 -15854.02596 153 -15854.02596 -15854.02596 154 -12000.69538 -15854.02596 155 -42939.46878 -12000.69538 156 -15854.02596 -42939.46878 157 -15854.02596 -15854.02596 158 -16796.30176 -15854.02596 159 -22779.43259 -16796.30176 160 -16600.99071 -22779.43259 161 900.92085 -16600.99071 162 -15854.02596 900.92085 163 8306.58352 -15854.02596 164 NA 8306.58352 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -15265.11974 9962.08755 [2,] 1985.31049 -15265.11974 [3,] 16446.42951 1985.31049 [4,] -17015.55666 16446.42951 [5,] 15339.95241 -17015.55666 [6,] -15804.91545 15339.95241 [7,] 2777.76837 -15804.91545 [8,] 25667.75178 2777.76837 [9,] -7893.74657 25667.75178 [10,] -30919.78241 -7893.74657 [11,] 11994.57779 -30919.78241 [12,] -184.24968 11994.57779 [13,] -439.43665 -184.24968 [14,] -18899.62088 -439.43665 [15,] -20996.15941 -18899.62088 [16,] 23384.44918 -20996.15941 [17,] 11720.05214 23384.44918 [18,] 17603.54416 11720.05214 [19,] 11068.34194 17603.54416 [20,] 6228.35282 11068.34194 [21,] -24440.02509 6228.35282 [22,] -10049.65064 -24440.02509 [23,] 14896.27350 -10049.65064 [24,] -5035.58768 14896.27350 [25,] -8947.99380 -5035.58768 [26,] -8175.35596 -8947.99380 [27,] -19414.11853 -8175.35596 [28,] -17280.84910 -19414.11853 [29,] -31405.18332 -17280.84910 [30,] 4821.69192 -31405.18332 [31,] 970.26444 4821.69192 [32,] -29063.42998 970.26444 [33,] 10278.48970 -29063.42998 [34,] -24501.17554 10278.48970 [35,] -18334.92115 -24501.17554 [36,] -39385.61352 -18334.92115 [37,] -14332.92260 -39385.61352 [38,] -16874.31841 -14332.92260 [39,] -17598.13390 -16874.31841 [40,] -23397.09814 -17598.13390 [41,] -4278.90816 -23397.09814 [42,] -20788.50317 -4278.90816 [43,] -2353.04118 -20788.50317 [44,] 1250.28624 -2353.04118 [45,] 23669.42951 1250.28624 [46,] -17529.90810 23669.42951 [47,] -1378.65108 -17529.90810 [48,] 23047.98580 -1378.65108 [49,] -3450.82888 23047.98580 [50,] -10308.83029 -3450.82888 [51,] -19072.66306 -10308.83029 [52,] -662.18100 -19072.66306 [53,] 1399.25931 -662.18100 [54,] -12071.40104 1399.25931 [55,] 700.16539 -12071.40104 [56,] 19503.77708 700.16539 [57,] 4009.90582 19503.77708 [58,] -17640.93444 4009.90582 [59,] 9132.90565 -17640.93444 [60,] 2160.67023 9132.90565 [61,] 8469.87738 2160.67023 [62,] -13043.97940 8469.87738 [63,] 8803.78678 -13043.97940 [64,] -3086.35623 8803.78678 [65,] -27277.13955 -3086.35623 [66,] 35153.79312 -27277.13955 [67,] -9149.53351 35153.79312 [68,] 8886.59358 -9149.53351 [69,] 3413.83852 8886.59358 [70,] 1241.59004 3413.83852 [71,] -7750.85155 1241.59004 [72,] -2410.72879 -7750.85155 [73,] 11151.38434 -2410.72879 [74,] 6546.25337 11151.38434 [75,] 6922.45019 6546.25337 [76,] -8479.29037 6922.45019 [77,] 143381.13823 -8479.29037 [78,] -1648.21829 143381.13823 [79,] 659.78667 -1648.21829 [80,] -10911.49906 659.78667 [81,] -4055.87729 -10911.49906 [82,] -17637.31713 -4055.87729 [83,] 1433.64045 -17637.31713 [84,] 6776.57254 1433.64045 [85,] -15749.76629 6776.57254 [86,] 23030.80792 -15749.76629 [87,] 69.80371 23030.80792 [88,] -33131.60121 69.80371 [89,] 47315.43465 -33131.60121 [90,] -26048.62148 47315.43465 [91,] 9634.90350 -26048.62148 [92,] -8955.63843 9634.90350 [93,] -9965.64094 -8955.63843 [94,] 9095.35594 -9965.64094 [95,] 22891.99890 9095.35594 [96,] 39714.95168 22891.99890 [97,] 22570.40832 39714.95168 [98,] 139.41951 22570.40832 [99,] 9726.98362 139.41951 [100,] 25479.87295 9726.98362 [101,] 10342.60959 25479.87295 [102,] -14201.21890 10342.60959 [103,] 15936.35238 -14201.21890 [104,] -22316.44544 15936.35238 [105,] -1809.27454 -22316.44544 [106,] 1710.94833 -1809.27454 [107,] 252.46976 1710.94833 [108,] 107004.51597 252.46976 [109,] 14327.12781 107004.51597 [110,] 7457.11837 14327.12781 [111,] -8702.94497 7457.11837 [112,] -18244.66835 -8702.94497 [113,] -6147.99300 -18244.66835 [114,] -5685.72382 -6147.99300 [115,] -13670.79943 -5685.72382 [116,] -49412.18836 -13670.79943 [117,] -19033.49436 -49412.18836 [118,] 12965.69378 -19033.49436 [119,] -9752.73930 12965.69378 [120,] -26397.22669 -9752.73930 [121,] 43220.50709 -26397.22669 [122,] 36328.04425 43220.50709 [123,] 22501.87417 36328.04425 [124,] -15600.20016 22501.87417 [125,] 16057.33336 -15600.20016 [126,] -11330.41122 16057.33336 [127,] 4672.17323 -11330.41122 [128,] -23042.38166 4672.17323 [129,] -8942.75350 -23042.38166 [130,] 49608.79452 -8942.75350 [131,] -5935.47855 49608.79452 [132,] -10189.72776 -5935.47855 [133,] 13803.84318 -10189.72776 [134,] -1515.71336 13803.84318 [135,] 43990.84024 -1515.71336 [136,] 28430.89195 43990.84024 [137,] 1331.54658 28430.89195 [138,] -21808.87233 1331.54658 [139,] -16297.91505 -21808.87233 [140,] 26180.19899 -16297.91505 [141,] -1859.59773 26180.19899 [142,] 15788.40802 -1859.59773 [143,] 14742.51527 15788.40802 [144,] -7548.78194 14742.51527 [145,] 42594.54332 -7548.78194 [146,] 26617.24892 42594.54332 [147,] 28961.45907 26617.24892 [148,] -15854.02596 28961.45907 [149,] -14676.40910 -15854.02596 [150,] -15854.02596 -14676.40910 [151,] -15854.02596 -15854.02596 [152,] -15854.02596 -15854.02596 [153,] -15854.02596 -15854.02596 [154,] -12000.69538 -15854.02596 [155,] -42939.46878 -12000.69538 [156,] -15854.02596 -42939.46878 [157,] -15854.02596 -15854.02596 [158,] -16796.30176 -15854.02596 [159,] -22779.43259 -16796.30176 [160,] -16600.99071 -22779.43259 [161,] 900.92085 -16600.99071 [162,] -15854.02596 900.92085 [163,] 8306.58352 -15854.02596 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -15265.11974 9962.08755 2 1985.31049 -15265.11974 3 16446.42951 1985.31049 4 -17015.55666 16446.42951 5 15339.95241 -17015.55666 6 -15804.91545 15339.95241 7 2777.76837 -15804.91545 8 25667.75178 2777.76837 9 -7893.74657 25667.75178 10 -30919.78241 -7893.74657 11 11994.57779 -30919.78241 12 -184.24968 11994.57779 13 -439.43665 -184.24968 14 -18899.62088 -439.43665 15 -20996.15941 -18899.62088 16 23384.44918 -20996.15941 17 11720.05214 23384.44918 18 17603.54416 11720.05214 19 11068.34194 17603.54416 20 6228.35282 11068.34194 21 -24440.02509 6228.35282 22 -10049.65064 -24440.02509 23 14896.27350 -10049.65064 24 -5035.58768 14896.27350 25 -8947.99380 -5035.58768 26 -8175.35596 -8947.99380 27 -19414.11853 -8175.35596 28 -17280.84910 -19414.11853 29 -31405.18332 -17280.84910 30 4821.69192 -31405.18332 31 970.26444 4821.69192 32 -29063.42998 970.26444 33 10278.48970 -29063.42998 34 -24501.17554 10278.48970 35 -18334.92115 -24501.17554 36 -39385.61352 -18334.92115 37 -14332.92260 -39385.61352 38 -16874.31841 -14332.92260 39 -17598.13390 -16874.31841 40 -23397.09814 -17598.13390 41 -4278.90816 -23397.09814 42 -20788.50317 -4278.90816 43 -2353.04118 -20788.50317 44 1250.28624 -2353.04118 45 23669.42951 1250.28624 46 -17529.90810 23669.42951 47 -1378.65108 -17529.90810 48 23047.98580 -1378.65108 49 -3450.82888 23047.98580 50 -10308.83029 -3450.82888 51 -19072.66306 -10308.83029 52 -662.18100 -19072.66306 53 1399.25931 -662.18100 54 -12071.40104 1399.25931 55 700.16539 -12071.40104 56 19503.77708 700.16539 57 4009.90582 19503.77708 58 -17640.93444 4009.90582 59 9132.90565 -17640.93444 60 2160.67023 9132.90565 61 8469.87738 2160.67023 62 -13043.97940 8469.87738 63 8803.78678 -13043.97940 64 -3086.35623 8803.78678 65 -27277.13955 -3086.35623 66 35153.79312 -27277.13955 67 -9149.53351 35153.79312 68 8886.59358 -9149.53351 69 3413.83852 8886.59358 70 1241.59004 3413.83852 71 -7750.85155 1241.59004 72 -2410.72879 -7750.85155 73 11151.38434 -2410.72879 74 6546.25337 11151.38434 75 6922.45019 6546.25337 76 -8479.29037 6922.45019 77 143381.13823 -8479.29037 78 -1648.21829 143381.13823 79 659.78667 -1648.21829 80 -10911.49906 659.78667 81 -4055.87729 -10911.49906 82 -17637.31713 -4055.87729 83 1433.64045 -17637.31713 84 6776.57254 1433.64045 85 -15749.76629 6776.57254 86 23030.80792 -15749.76629 87 69.80371 23030.80792 88 -33131.60121 69.80371 89 47315.43465 -33131.60121 90 -26048.62148 47315.43465 91 9634.90350 -26048.62148 92 -8955.63843 9634.90350 93 -9965.64094 -8955.63843 94 9095.35594 -9965.64094 95 22891.99890 9095.35594 96 39714.95168 22891.99890 97 22570.40832 39714.95168 98 139.41951 22570.40832 99 9726.98362 139.41951 100 25479.87295 9726.98362 101 10342.60959 25479.87295 102 -14201.21890 10342.60959 103 15936.35238 -14201.21890 104 -22316.44544 15936.35238 105 -1809.27454 -22316.44544 106 1710.94833 -1809.27454 107 252.46976 1710.94833 108 107004.51597 252.46976 109 14327.12781 107004.51597 110 7457.11837 14327.12781 111 -8702.94497 7457.11837 112 -18244.66835 -8702.94497 113 -6147.99300 -18244.66835 114 -5685.72382 -6147.99300 115 -13670.79943 -5685.72382 116 -49412.18836 -13670.79943 117 -19033.49436 -49412.18836 118 12965.69378 -19033.49436 119 -9752.73930 12965.69378 120 -26397.22669 -9752.73930 121 43220.50709 -26397.22669 122 36328.04425 43220.50709 123 22501.87417 36328.04425 124 -15600.20016 22501.87417 125 16057.33336 -15600.20016 126 -11330.41122 16057.33336 127 4672.17323 -11330.41122 128 -23042.38166 4672.17323 129 -8942.75350 -23042.38166 130 49608.79452 -8942.75350 131 -5935.47855 49608.79452 132 -10189.72776 -5935.47855 133 13803.84318 -10189.72776 134 -1515.71336 13803.84318 135 43990.84024 -1515.71336 136 28430.89195 43990.84024 137 1331.54658 28430.89195 138 -21808.87233 1331.54658 139 -16297.91505 -21808.87233 140 26180.19899 -16297.91505 141 -1859.59773 26180.19899 142 15788.40802 -1859.59773 143 14742.51527 15788.40802 144 -7548.78194 14742.51527 145 42594.54332 -7548.78194 146 26617.24892 42594.54332 147 28961.45907 26617.24892 148 -15854.02596 28961.45907 149 -14676.40910 -15854.02596 150 -15854.02596 -14676.40910 151 -15854.02596 -15854.02596 152 -15854.02596 -15854.02596 153 -15854.02596 -15854.02596 154 -12000.69538 -15854.02596 155 -42939.46878 -12000.69538 156 -15854.02596 -42939.46878 157 -15854.02596 -15854.02596 158 -16796.30176 -15854.02596 159 -22779.43259 -16796.30176 160 -16600.99071 -22779.43259 161 900.92085 -16600.99071 162 -15854.02596 900.92085 163 8306.58352 -15854.02596 > 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/rcomp/tmp/71ou81321897242.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/8wcld1321897242.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/9hckq1321897242.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/rcomp/tmp/10y2tx1321897242.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/rcomp/tmp/11t70p1321897242.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/rcomp/tmp/12akfi1321897242.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/rcomp/tmp/13k1u21321897242.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/rcomp/tmp/14l77m1321897242.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/rcomp/tmp/15v1vr1321897242.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/rcomp/tmp/16dh4v1321897242.tab") + } > > try(system("convert tmp/1h5r71321897242.ps tmp/1h5r71321897242.png",intern=TRUE)) character(0) > try(system("convert tmp/28mh31321897242.ps tmp/28mh31321897242.png",intern=TRUE)) character(0) > try(system("convert tmp/3yre31321897242.ps tmp/3yre31321897242.png",intern=TRUE)) character(0) > try(system("convert tmp/4w2jq1321897242.ps tmp/4w2jq1321897242.png",intern=TRUE)) character(0) > try(system("convert tmp/58zlb1321897242.ps tmp/58zlb1321897242.png",intern=TRUE)) character(0) > try(system("convert tmp/6hkd51321897242.ps tmp/6hkd51321897242.png",intern=TRUE)) character(0) > try(system("convert tmp/71ou81321897242.ps tmp/71ou81321897242.png",intern=TRUE)) character(0) > try(system("convert tmp/8wcld1321897242.ps tmp/8wcld1321897242.png",intern=TRUE)) character(0) > try(system("convert tmp/9hckq1321897242.ps tmp/9hckq1321897242.png",intern=TRUE)) character(0) > try(system("convert tmp/10y2tx1321897242.ps tmp/10y2tx1321897242.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 5.110 0.290 5.351