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Type 'q()' to quit R. > x <- array(list(205597 + ,0 + ,205471 + ,0 + ,211064 + ,0 + ,212856 + ,0 + ,217036 + ,0 + ,219302 + ,0 + ,219759 + ,0 + ,221388 + ,0 + ,220834 + ,0 + ,221788 + ,0 + ,222358 + ,0 + ,222972 + ,0 + ,224164 + ,0 + ,224915 + ,0 + ,226294 + ,0 + ,224690 + ,0 + ,227021 + ,0 + ,229284 + ,0 + ,229189 + ,0 + ,230032 + ,0 + ,229389 + ,0 + ,231053 + ,0 + ,232560 + ,0 + ,232681 + ,0 + ,231555 + ,0 + ,231428 + ,0 + ,232141 + ,0 + ,234939 + ,0 + ,235424 + ,0 + ,235471 + ,0 + ,236355 + ,0 + ,238693 + ,0 + ,236958 + ,0 + ,237060 + ,0 + ,239282 + ,0 + ,238252 + ,0 + ,241552 + ,0 + ,236230 + ,0 + ,238909 + ,0 + ,240723 + ,0 + ,242120 + ,0 + ,242100 + ,0 + ,243276 + ,0 + ,244677 + ,0 + ,243494 + ,0 + ,244902 + ,0 + ,245247 + ,0 + ,245578 + ,0 + ,243052 + ,0 + ,238121 + ,0 + ,241863 + ,0 + ,241203 + ,0 + ,243634 + ,0 + ,242351 + ,0 + ,245180 + ,0 + ,246126 + ,0 + ,244424 + ,0 + ,245166 + ,0 + ,247258 + ,0 + ,245094 + ,0 + ,246020 + ,0 + ,243082 + ,0 + ,245555 + ,0 + ,243685 + ,0 + ,247277 + ,0 + ,245029 + ,0 + ,246169 + ,0 + ,246778 + ,0 + ,244577 + ,0 + ,246048 + ,0 + ,245775 + ,0 + ,245328 + ,0 + ,245477 + ,0 + ,241903 + ,0 + ,243219 + ,0 + ,248088 + ,0 + ,248521 + ,0 + ,247389 + ,0 + ,249057 + ,0 + ,248916 + ,0 + ,249193 + ,0 + ,250768 + ,1 + ,253106 + ,1 + ,249829 + ,1 + ,249447 + ,1 + ,246755 + ,1 + ,250785 + ,1 + ,250140 + ,1 + ,255755 + ,1 + ,254671 + ,1 + ,253919 + ,1 + ,253741 + ,1 + ,252729 + ,1 + ,253810 + ,1 + ,256653 + ,1 + ,255231 + ,1 + ,258405 + ,1 + ,251061 + ,1 + ,254811 + ,1 + ,254895 + ,1 + ,258325 + ,1 + ,257608 + ,1 + ,258759 + ,1 + ,258621 + ,1 + ,257852 + ,1 + ,260560 + ,1 + ,262358 + ,1 + ,260812 + ,1 + ,261165 + ,1 + ,257164 + ,1 + ,260720 + ,1 + ,259581 + ,1 + ,264743 + ,1 + ,261845 + ,1 + ,262262 + ,1 + ,261631 + ,1 + ,258953 + ,1 + ,259966 + ,1 + ,262850 + ,1 + ,262204 + ,1 + ,263418 + ,1 + ,262752 + ,1 + ,266433 + ,1 + ,267722 + ,1 + ,266003 + ,1 + ,262971 + ,1 + ,265521 + ,1 + ,264676 + ,1 + ,270223 + ,1 + ,269508 + ,1 + ,268457 + ,1 + ,265814 + ,1 + ,266680 + ,1 + ,263018 + ,1 + ,269285 + ,1 + ,269829 + ,1 + ,270911 + ,1 + ,266844 + ,1 + ,271244 + ,1 + ,269907 + ,1 + ,271296 + ,1 + ,270157 + ,1 + ,271322 + ,1 + ,267179 + ,1 + ,264101 + ,1 + ,265518 + ,1 + ,269419 + ,1 + ,268714 + ,1 + ,272482 + ,1 + ,268351 + ,1 + ,268175 + ,1 + ,270674 + ,1 + ,272764 + ,1 + ,272599 + ,1 + ,270333 + ,1 + ,270846 + ,1 + ,270491 + ,1 + ,269160 + ,1 + ,274027 + ,1 + ,273784 + ,1 + ,276663 + ,1 + ,274525 + ,1 + ,271344 + ,1 + ,271115 + ,1 + ,270798 + ,1 + ,273911 + ,1 + ,273985 + ,1 + ,271917 + ,1 + ,273338 + ,1 + ,270601 + ,1 + ,273547 + ,1 + ,275363 + ,1 + ,281229 + ,1 + ,277793 + ,1 + ,279913 + ,1 + ,282500 + ,1 + ,280041 + ,1 + ,282166 + ,1 + ,290304 + ,1 + ,283519 + ,1 + ,287816 + ,1 + ,285226 + ,1 + ,287595 + ,1 + ,289741 + ,1 + ,289148 + ,1 + ,288301 + ,1 + ,290155 + ,1 + ,289648 + ,1 + ,288225 + ,1 + ,289351 + ,1 + ,294735 + ,1 + ,305333 + ,1) + ,dim=c(2 + ,192) + ,dimnames=list(c('Brutoschuld' + ,'Dummy') + ,1:192)) > y <- array(NA,dim=c(2,192),dimnames=list(c('Brutoschuld','Dummy'),1:192)) > 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 Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x Brutoschuld Dummy 1 205597 0 2 205471 0 3 211064 0 4 212856 0 5 217036 0 6 219302 0 7 219759 0 8 221388 0 9 220834 0 10 221788 0 11 222358 0 12 222972 0 13 224164 0 14 224915 0 15 226294 0 16 224690 0 17 227021 0 18 229284 0 19 229189 0 20 230032 0 21 229389 0 22 231053 0 23 232560 0 24 232681 0 25 231555 0 26 231428 0 27 232141 0 28 234939 0 29 235424 0 30 235471 0 31 236355 0 32 238693 0 33 236958 0 34 237060 0 35 239282 0 36 238252 0 37 241552 0 38 236230 0 39 238909 0 40 240723 0 41 242120 0 42 242100 0 43 243276 0 44 244677 0 45 243494 0 46 244902 0 47 245247 0 48 245578 0 49 243052 0 50 238121 0 51 241863 0 52 241203 0 53 243634 0 54 242351 0 55 245180 0 56 246126 0 57 244424 0 58 245166 0 59 247258 0 60 245094 0 61 246020 0 62 243082 0 63 245555 0 64 243685 0 65 247277 0 66 245029 0 67 246169 0 68 246778 0 69 244577 0 70 246048 0 71 245775 0 72 245328 0 73 245477 0 74 241903 0 75 243219 0 76 248088 0 77 248521 0 78 247389 0 79 249057 0 80 248916 0 81 249193 0 82 250768 1 83 253106 1 84 249829 1 85 249447 1 86 246755 1 87 250785 1 88 250140 1 89 255755 1 90 254671 1 91 253919 1 92 253741 1 93 252729 1 94 253810 1 95 256653 1 96 255231 1 97 258405 1 98 251061 1 99 254811 1 100 254895 1 101 258325 1 102 257608 1 103 258759 1 104 258621 1 105 257852 1 106 260560 1 107 262358 1 108 260812 1 109 261165 1 110 257164 1 111 260720 1 112 259581 1 113 264743 1 114 261845 1 115 262262 1 116 261631 1 117 258953 1 118 259966 1 119 262850 1 120 262204 1 121 263418 1 122 262752 1 123 266433 1 124 267722 1 125 266003 1 126 262971 1 127 265521 1 128 264676 1 129 270223 1 130 269508 1 131 268457 1 132 265814 1 133 266680 1 134 263018 1 135 269285 1 136 269829 1 137 270911 1 138 266844 1 139 271244 1 140 269907 1 141 271296 1 142 270157 1 143 271322 1 144 267179 1 145 264101 1 146 265518 1 147 269419 1 148 268714 1 149 272482 1 150 268351 1 151 268175 1 152 270674 1 153 272764 1 154 272599 1 155 270333 1 156 270846 1 157 270491 1 158 269160 1 159 274027 1 160 273784 1 161 276663 1 162 274525 1 163 271344 1 164 271115 1 165 270798 1 166 273911 1 167 273985 1 168 271917 1 169 273338 1 170 270601 1 171 273547 1 172 275363 1 173 281229 1 174 277793 1 175 279913 1 176 282500 1 177 280041 1 178 282166 1 179 290304 1 180 283519 1 181 287816 1 182 285226 1 183 287595 1 184 289741 1 185 289148 1 186 288301 1 187 290155 1 188 289648 1 189 288225 1 190 289351 1 191 294735 1 192 305333 1 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Dummy 236650 31611 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -31179 -7452 1359 7270 37072 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 236650 1242 190.53 <2e-16 *** Dummy 31611 1634 19.35 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 11180 on 190 degrees of freedom Multiple R-squared: 0.6634, Adjusted R-squared: 0.6616 F-statistic: 374.5 on 1 and 190 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,] 0.17620371 0.35240741 0.82379629 [2,] 0.18040086 0.36080171 0.81959914 [3,] 0.16038168 0.32076337 0.83961832 [4,] 0.15279483 0.30558966 0.84720517 [5,] 0.12655301 0.25310601 0.87344699 [6,] 0.10848847 0.21697693 0.89151153 [7,] 0.09330929 0.18661858 0.90669071 [8,] 0.08120413 0.16240826 0.91879587 [9,] 0.07533272 0.15066544 0.92466728 [10,] 0.07142486 0.14284972 0.92857514 [11,] 0.07314394 0.14628788 0.92685606 [12,] 0.06336232 0.12672463 0.93663768 [13,] 0.06397600 0.12795201 0.93602400 [14,] 0.07523389 0.15046779 0.92476611 [15,] 0.08183125 0.16366249 0.91816875 [16,] 0.09043114 0.18086227 0.90956886 [17,] 0.09154054 0.18308109 0.90845946 [18,] 0.10035585 0.20071170 0.89964415 [19,] 0.11679133 0.23358266 0.88320867 [20,] 0.13023553 0.26047105 0.86976447 [21,] 0.13200003 0.26400006 0.86799997 [22,] 0.13070000 0.26140001 0.86930000 [23,] 0.13167540 0.26335081 0.86832460 [24,] 0.14980027 0.29960053 0.85019973 [25,] 0.16836619 0.33673237 0.83163381 [26,] 0.18356157 0.36712315 0.81643843 [27,] 0.20265991 0.40531982 0.79734009 [28,] 0.24116468 0.48232937 0.75883532 [29,] 0.25689117 0.51378234 0.74310883 [30,] 0.26953052 0.53906105 0.73046948 [31,] 0.29972800 0.59945599 0.70027200 [32,] 0.31457278 0.62914555 0.68542722 [33,] 0.36025615 0.72051231 0.63974385 [34,] 0.35138783 0.70277567 0.64861217 [35,] 0.36030476 0.72060952 0.63969524 [36,] 0.38220494 0.76440988 0.61779506 [37,] 0.41363358 0.82726717 0.58636642 [38,] 0.43919952 0.87839903 0.56080048 [39,] 0.47173305 0.94346610 0.52826695 [40,] 0.51351891 0.97296218 0.48648109 [41,] 0.53601824 0.92796352 0.46398176 [42,] 0.56730167 0.86539666 0.43269833 [43,] 0.59596991 0.80806017 0.40403009 [44,] 0.62208846 0.75582307 0.37791154 [45,] 0.62306968 0.75386065 0.37693032 [46,] 0.59855893 0.80288213 0.40144107 [47,] 0.58902808 0.82194384 0.41097192 [48,] 0.57459662 0.85080677 0.42540338 [49,] 0.57284782 0.85430437 0.42715218 [50,] 0.56148423 0.87703154 0.43851577 [51,] 0.56652606 0.86694788 0.43347394 [52,] 0.57597175 0.84805651 0.42402825 [53,] 0.57089307 0.85821387 0.42910693 [54,] 0.56865687 0.86268626 0.43134313 [55,] 0.57917937 0.84164127 0.42082063 [56,] 0.57228862 0.85542275 0.42771138 [57,] 0.56940706 0.86118589 0.43059294 [58,] 0.54958765 0.90082470 0.45041235 [59,] 0.54092154 0.91815692 0.45907846 [60,] 0.52167889 0.95664222 0.47832111 [61,] 0.52089971 0.95820058 0.47910029 [62,] 0.50550156 0.98899688 0.49449844 [63,] 0.49490615 0.98981229 0.50509385 [64,] 0.48641533 0.97283066 0.51358467 [65,] 0.46595400 0.93190800 0.53404600 [66,] 0.45138125 0.90276250 0.54861875 [67,] 0.43460924 0.86921848 0.56539076 [68,] 0.41523208 0.83046416 0.58476792 [69,] 0.39599020 0.79198040 0.60400980 [70,] 0.36751917 0.73503834 0.63248083 [71,] 0.34260684 0.68521368 0.65739316 [72,] 0.33433922 0.66867843 0.66566078 [73,] 0.32706188 0.65412377 0.67293812 [74,] 0.31385996 0.62771992 0.68614004 [75,] 0.30714694 0.61429387 0.69285306 [76,] 0.29872557 0.59745115 0.70127443 [77,] 0.29058222 0.58116443 0.70941778 [78,] 0.28965854 0.57931707 0.71034146 [79,] 0.28171274 0.56342549 0.71828726 [80,] 0.28835937 0.57671874 0.71164063 [81,] 0.29893780 0.59787560 0.70106220 [82,] 0.32933837 0.65867673 0.67066163 [83,] 0.33884195 0.67768391 0.66115805 [84,] 0.35444625 0.70889249 0.64555375 [85,] 0.34974297 0.69948595 0.65025703 [86,] 0.34822238 0.69644476 0.65177762 [87,] 0.35057086 0.70114173 0.64942914 [88,] 0.35529216 0.71058433 0.64470784 [89,] 0.36715653 0.73431305 0.63284347 [90,] 0.37579466 0.75158932 0.62420534 [91,] 0.37438179 0.74876359 0.62561821 [92,] 0.37960885 0.75921770 0.62039115 [93,] 0.37496735 0.74993471 0.62503265 [94,] 0.41185053 0.82370105 0.58814947 [95,] 0.42617693 0.85235386 0.57382307 [96,] 0.44280417 0.88560834 0.55719583 [97,] 0.44470405 0.88940810 0.55529595 [98,] 0.45072304 0.90144609 0.54927696 [99,] 0.45327848 0.90655697 0.54672152 [100,] 0.45755708 0.91511415 0.54244292 [101,] 0.46705612 0.93411224 0.53294388 [102,] 0.46660134 0.93320269 0.53339866 [103,] 0.46193298 0.92386596 0.53806702 [104,] 0.46148879 0.92297758 0.53851121 [105,] 0.46055400 0.92110799 0.53944600 [106,] 0.48274057 0.96548114 0.51725943 [107,] 0.48650430 0.97300861 0.51349570 [108,] 0.49766700 0.99533399 0.50233300 [109,] 0.49171132 0.98342264 0.50828868 [110,] 0.49368232 0.98736464 0.50631768 [111,] 0.49495180 0.98990361 0.50504820 [112,] 0.50026033 0.99947934 0.49973967 [113,] 0.52512246 0.94975509 0.47487754 [114,] 0.54561306 0.90877387 0.45438694 [115,] 0.55088778 0.89822445 0.44911222 [116,] 0.56108372 0.87783255 0.43891628 [117,] 0.56645248 0.86709505 0.43354752 [118,] 0.57686912 0.84626176 0.42313088 [119,] 0.57318494 0.85363013 0.42681506 [120,] 0.56679745 0.86640511 0.43320255 [121,] 0.56410862 0.87178276 0.43589138 [122,] 0.57776146 0.84447708 0.42223854 [123,] 0.57889210 0.84221579 0.42110790 [124,] 0.58540562 0.82918876 0.41459438 [125,] 0.57659227 0.84681546 0.42340773 [126,] 0.56708376 0.86583248 0.43291624 [127,] 0.55876794 0.88246412 0.44123206 [128,] 0.56112607 0.87774786 0.43887393 [129,] 0.56025726 0.87948548 0.43974274 [130,] 0.58703043 0.82593913 0.41296957 [131,] 0.57876059 0.84247883 0.42123941 [132,] 0.56890398 0.86219205 0.43109602 [133,] 0.55655985 0.88688031 0.44344015 [134,] 0.55956448 0.88087105 0.44043552 [135,] 0.54628927 0.90742145 0.45371073 [136,] 0.53581261 0.92837479 0.46418739 [137,] 0.52154923 0.95690154 0.47845077 [138,] 0.51011504 0.97976993 0.48988496 [139,] 0.49523738 0.99047476 0.50476262 [140,] 0.50122292 0.99755417 0.49877708 [141,] 0.54019092 0.91961816 0.45980908 [142,] 0.56932247 0.86135507 0.43067753 [143,] 0.56894011 0.86211978 0.43105989 [144,] 0.57538828 0.84922344 0.42461172 [145,] 0.56220145 0.87559710 0.43779855 [146,] 0.57550086 0.84899828 0.42449914 [147,] 0.59405370 0.81189259 0.40594630 [148,] 0.59480494 0.81039012 0.40519506 [149,] 0.58437563 0.83124873 0.41562437 [150,] 0.57526771 0.84946459 0.42473229 [151,] 0.58379513 0.83240974 0.41620487 [152,] 0.59090619 0.81818762 0.40909381 [153,] 0.60463740 0.79072520 0.39536260 [154,] 0.63777322 0.72445356 0.36222678 [155,] 0.62992640 0.74014720 0.37007360 [156,] 0.62483704 0.75032592 0.37516296 [157,] 0.60483470 0.79033060 0.39516530 [158,] 0.59602000 0.80796000 0.40398000 [159,] 0.62084090 0.75831819 0.37915910 [160,] 0.65542470 0.68915061 0.34457530 [161,] 0.70238649 0.59522703 0.29761351 [162,] 0.71684349 0.56631303 0.28315651 [163,] 0.73552859 0.52894282 0.26447141 [164,] 0.78780846 0.42438308 0.21219154 [165,] 0.82713178 0.34573644 0.17286822 [166,] 0.90585301 0.18829399 0.09414699 [167,] 0.94388265 0.11223469 0.05611735 [168,] 0.96562073 0.06875853 0.03437927 [169,] 0.96299726 0.07400548 0.03700274 [170,] 0.97429331 0.05141338 0.02570669 [171,] 0.97865453 0.04269093 0.02134547 [172,] 0.97699814 0.04600371 0.02300186 [173,] 0.98404111 0.03191777 0.01595889 [174,] 0.98618350 0.02763299 0.01381650 [175,] 0.97782604 0.04434792 0.02217396 [176,] 0.97706667 0.04586666 0.02293333 [177,] 0.96372430 0.07255140 0.03627570 [178,] 0.95558370 0.08883260 0.04441630 [179,] 0.93292438 0.13415123 0.06707562 [180,] 0.88824862 0.22350277 0.11175138 [181,] 0.82327923 0.35344154 0.17672077 [182,] 0.74155161 0.51689678 0.25844839 [183,] 0.60648512 0.78702975 0.39351488 > postscript(file="/var/www/html/rcomp/tmp/1y6gp1229454486.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2jdjn1229454486.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/3n1qb1229454486.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/42tza1229454486.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/53y961229454486.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 192 Frequency = 1 1 2 3 4 5 6 -31052.64198 -31178.64198 -25585.64198 -23793.64198 -19613.64198 -17347.64198 7 8 9 10 11 12 -16890.64198 -15261.64198 -15815.64198 -14861.64198 -14291.64198 -13677.64198 13 14 15 16 17 18 -12485.64198 -11734.64198 -10355.64198 -11959.64198 -9628.64198 -7365.64198 19 20 21 22 23 24 -7460.64198 -6617.64198 -7260.64198 -5596.64198 -4089.64198 -3968.64198 25 26 27 28 29 30 -5094.64198 -5221.64198 -4508.64198 -1710.64198 -1225.64198 -1178.64198 31 32 33 34 35 36 -294.64198 2043.35802 308.35802 410.35802 2632.35802 1602.35802 37 38 39 40 41 42 4902.35802 -419.64198 2259.35802 4073.35802 5470.35802 5450.35802 43 44 45 46 47 48 6626.35802 8027.35802 6844.35802 8252.35802 8597.35802 8928.35802 49 50 51 52 53 54 6402.35802 1471.35802 5213.35802 4553.35802 6984.35802 5701.35802 55 56 57 58 59 60 8530.35802 9476.35802 7774.35802 8516.35802 10608.35802 8444.35802 61 62 63 64 65 66 9370.35802 6432.35802 8905.35802 7035.35802 10627.35802 8379.35802 67 68 69 70 71 72 9519.35802 10128.35802 7927.35802 9398.35802 9125.35802 8678.35802 73 74 75 76 77 78 8827.35802 5253.35802 6569.35802 11438.35802 11871.35802 10739.35802 79 80 81 82 83 84 12407.35802 12266.35802 12543.35802 -17492.75676 -15154.75676 -18431.75676 85 86 87 88 89 90 -18813.75676 -21505.75676 -17475.75676 -18120.75676 -12505.75676 -13589.75676 91 92 93 94 95 96 -14341.75676 -14519.75676 -15531.75676 -14450.75676 -11607.75676 -13029.75676 97 98 99 100 101 102 -9855.75676 -17199.75676 -13449.75676 -13365.75676 -9935.75676 -10652.75676 103 104 105 106 107 108 -9501.75676 -9639.75676 -10408.75676 -7700.75676 -5902.75676 -7448.75676 109 110 111 112 113 114 -7095.75676 -11096.75676 -7540.75676 -8679.75676 -3517.75676 -6415.75676 115 116 117 118 119 120 -5998.75676 -6629.75676 -9307.75676 -8294.75676 -5410.75676 -6056.75676 121 122 123 124 125 126 -4842.75676 -5508.75676 -1827.75676 -538.75676 -2257.75676 -5289.75676 127 128 129 130 131 132 -2739.75676 -3584.75676 1962.24324 1247.24324 196.24324 -2446.75676 133 134 135 136 137 138 -1580.75676 -5242.75676 1024.24324 1568.24324 2650.24324 -1416.75676 139 140 141 142 143 144 2983.24324 1646.24324 3035.24324 1896.24324 3061.24324 -1081.75676 145 146 147 148 149 150 -4159.75676 -2742.75676 1158.24324 453.24324 4221.24324 90.24324 151 152 153 154 155 156 -85.75676 2413.24324 4503.24324 4338.24324 2072.24324 2585.24324 157 158 159 160 161 162 2230.24324 899.24324 5766.24324 5523.24324 8402.24324 6264.24324 163 164 165 166 167 168 3083.24324 2854.24324 2537.24324 5650.24324 5724.24324 3656.24324 169 170 171 172 173 174 5077.24324 2340.24324 5286.24324 7102.24324 12968.24324 9532.24324 175 176 177 178 179 180 11652.24324 14239.24324 11780.24324 13905.24324 22043.24324 15258.24324 181 182 183 184 185 186 19555.24324 16965.24324 19334.24324 21480.24324 20887.24324 20040.24324 187 188 189 190 191 192 21894.24324 21387.24324 19964.24324 21090.24324 26474.24324 37072.24324 > postscript(file="/var/www/html/rcomp/tmp/6v4sl1229454486.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 192 Frequency = 1 lag(myerror, k = 1) myerror 0 -31052.64198 NA 1 -31178.64198 -31052.64198 2 -25585.64198 -31178.64198 3 -23793.64198 -25585.64198 4 -19613.64198 -23793.64198 5 -17347.64198 -19613.64198 6 -16890.64198 -17347.64198 7 -15261.64198 -16890.64198 8 -15815.64198 -15261.64198 9 -14861.64198 -15815.64198 10 -14291.64198 -14861.64198 11 -13677.64198 -14291.64198 12 -12485.64198 -13677.64198 13 -11734.64198 -12485.64198 14 -10355.64198 -11734.64198 15 -11959.64198 -10355.64198 16 -9628.64198 -11959.64198 17 -7365.64198 -9628.64198 18 -7460.64198 -7365.64198 19 -6617.64198 -7460.64198 20 -7260.64198 -6617.64198 21 -5596.64198 -7260.64198 22 -4089.64198 -5596.64198 23 -3968.64198 -4089.64198 24 -5094.64198 -3968.64198 25 -5221.64198 -5094.64198 26 -4508.64198 -5221.64198 27 -1710.64198 -4508.64198 28 -1225.64198 -1710.64198 29 -1178.64198 -1225.64198 30 -294.64198 -1178.64198 31 2043.35802 -294.64198 32 308.35802 2043.35802 33 410.35802 308.35802 34 2632.35802 410.35802 35 1602.35802 2632.35802 36 4902.35802 1602.35802 37 -419.64198 4902.35802 38 2259.35802 -419.64198 39 4073.35802 2259.35802 40 5470.35802 4073.35802 41 5450.35802 5470.35802 42 6626.35802 5450.35802 43 8027.35802 6626.35802 44 6844.35802 8027.35802 45 8252.35802 6844.35802 46 8597.35802 8252.35802 47 8928.35802 8597.35802 48 6402.35802 8928.35802 49 1471.35802 6402.35802 50 5213.35802 1471.35802 51 4553.35802 5213.35802 52 6984.35802 4553.35802 53 5701.35802 6984.35802 54 8530.35802 5701.35802 55 9476.35802 8530.35802 56 7774.35802 9476.35802 57 8516.35802 7774.35802 58 10608.35802 8516.35802 59 8444.35802 10608.35802 60 9370.35802 8444.35802 61 6432.35802 9370.35802 62 8905.35802 6432.35802 63 7035.35802 8905.35802 64 10627.35802 7035.35802 65 8379.35802 10627.35802 66 9519.35802 8379.35802 67 10128.35802 9519.35802 68 7927.35802 10128.35802 69 9398.35802 7927.35802 70 9125.35802 9398.35802 71 8678.35802 9125.35802 72 8827.35802 8678.35802 73 5253.35802 8827.35802 74 6569.35802 5253.35802 75 11438.35802 6569.35802 76 11871.35802 11438.35802 77 10739.35802 11871.35802 78 12407.35802 10739.35802 79 12266.35802 12407.35802 80 12543.35802 12266.35802 81 -17492.75676 12543.35802 82 -15154.75676 -17492.75676 83 -18431.75676 -15154.75676 84 -18813.75676 -18431.75676 85 -21505.75676 -18813.75676 86 -17475.75676 -21505.75676 87 -18120.75676 -17475.75676 88 -12505.75676 -18120.75676 89 -13589.75676 -12505.75676 90 -14341.75676 -13589.75676 91 -14519.75676 -14341.75676 92 -15531.75676 -14519.75676 93 -14450.75676 -15531.75676 94 -11607.75676 -14450.75676 95 -13029.75676 -11607.75676 96 -9855.75676 -13029.75676 97 -17199.75676 -9855.75676 98 -13449.75676 -17199.75676 99 -13365.75676 -13449.75676 100 -9935.75676 -13365.75676 101 -10652.75676 -9935.75676 102 -9501.75676 -10652.75676 103 -9639.75676 -9501.75676 104 -10408.75676 -9639.75676 105 -7700.75676 -10408.75676 106 -5902.75676 -7700.75676 107 -7448.75676 -5902.75676 108 -7095.75676 -7448.75676 109 -11096.75676 -7095.75676 110 -7540.75676 -11096.75676 111 -8679.75676 -7540.75676 112 -3517.75676 -8679.75676 113 -6415.75676 -3517.75676 114 -5998.75676 -6415.75676 115 -6629.75676 -5998.75676 116 -9307.75676 -6629.75676 117 -8294.75676 -9307.75676 118 -5410.75676 -8294.75676 119 -6056.75676 -5410.75676 120 -4842.75676 -6056.75676 121 -5508.75676 -4842.75676 122 -1827.75676 -5508.75676 123 -538.75676 -1827.75676 124 -2257.75676 -538.75676 125 -5289.75676 -2257.75676 126 -2739.75676 -5289.75676 127 -3584.75676 -2739.75676 128 1962.24324 -3584.75676 129 1247.24324 1962.24324 130 196.24324 1247.24324 131 -2446.75676 196.24324 132 -1580.75676 -2446.75676 133 -5242.75676 -1580.75676 134 1024.24324 -5242.75676 135 1568.24324 1024.24324 136 2650.24324 1568.24324 137 -1416.75676 2650.24324 138 2983.24324 -1416.75676 139 1646.24324 2983.24324 140 3035.24324 1646.24324 141 1896.24324 3035.24324 142 3061.24324 1896.24324 143 -1081.75676 3061.24324 144 -4159.75676 -1081.75676 145 -2742.75676 -4159.75676 146 1158.24324 -2742.75676 147 453.24324 1158.24324 148 4221.24324 453.24324 149 90.24324 4221.24324 150 -85.75676 90.24324 151 2413.24324 -85.75676 152 4503.24324 2413.24324 153 4338.24324 4503.24324 154 2072.24324 4338.24324 155 2585.24324 2072.24324 156 2230.24324 2585.24324 157 899.24324 2230.24324 158 5766.24324 899.24324 159 5523.24324 5766.24324 160 8402.24324 5523.24324 161 6264.24324 8402.24324 162 3083.24324 6264.24324 163 2854.24324 3083.24324 164 2537.24324 2854.24324 165 5650.24324 2537.24324 166 5724.24324 5650.24324 167 3656.24324 5724.24324 168 5077.24324 3656.24324 169 2340.24324 5077.24324 170 5286.24324 2340.24324 171 7102.24324 5286.24324 172 12968.24324 7102.24324 173 9532.24324 12968.24324 174 11652.24324 9532.24324 175 14239.24324 11652.24324 176 11780.24324 14239.24324 177 13905.24324 11780.24324 178 22043.24324 13905.24324 179 15258.24324 22043.24324 180 19555.24324 15258.24324 181 16965.24324 19555.24324 182 19334.24324 16965.24324 183 21480.24324 19334.24324 184 20887.24324 21480.24324 185 20040.24324 20887.24324 186 21894.24324 20040.24324 187 21387.24324 21894.24324 188 19964.24324 21387.24324 189 21090.24324 19964.24324 190 26474.24324 21090.24324 191 37072.24324 26474.24324 192 NA 37072.24324 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -31178.64198 -31052.64198 [2,] -25585.64198 -31178.64198 [3,] -23793.64198 -25585.64198 [4,] -19613.64198 -23793.64198 [5,] -17347.64198 -19613.64198 [6,] -16890.64198 -17347.64198 [7,] -15261.64198 -16890.64198 [8,] -15815.64198 -15261.64198 [9,] -14861.64198 -15815.64198 [10,] -14291.64198 -14861.64198 [11,] -13677.64198 -14291.64198 [12,] -12485.64198 -13677.64198 [13,] -11734.64198 -12485.64198 [14,] -10355.64198 -11734.64198 [15,] -11959.64198 -10355.64198 [16,] -9628.64198 -11959.64198 [17,] -7365.64198 -9628.64198 [18,] -7460.64198 -7365.64198 [19,] -6617.64198 -7460.64198 [20,] -7260.64198 -6617.64198 [21,] -5596.64198 -7260.64198 [22,] -4089.64198 -5596.64198 [23,] -3968.64198 -4089.64198 [24,] -5094.64198 -3968.64198 [25,] -5221.64198 -5094.64198 [26,] -4508.64198 -5221.64198 [27,] -1710.64198 -4508.64198 [28,] -1225.64198 -1710.64198 [29,] -1178.64198 -1225.64198 [30,] -294.64198 -1178.64198 [31,] 2043.35802 -294.64198 [32,] 308.35802 2043.35802 [33,] 410.35802 308.35802 [34,] 2632.35802 410.35802 [35,] 1602.35802 2632.35802 [36,] 4902.35802 1602.35802 [37,] -419.64198 4902.35802 [38,] 2259.35802 -419.64198 [39,] 4073.35802 2259.35802 [40,] 5470.35802 4073.35802 [41,] 5450.35802 5470.35802 [42,] 6626.35802 5450.35802 [43,] 8027.35802 6626.35802 [44,] 6844.35802 8027.35802 [45,] 8252.35802 6844.35802 [46,] 8597.35802 8252.35802 [47,] 8928.35802 8597.35802 [48,] 6402.35802 8928.35802 [49,] 1471.35802 6402.35802 [50,] 5213.35802 1471.35802 [51,] 4553.35802 5213.35802 [52,] 6984.35802 4553.35802 [53,] 5701.35802 6984.35802 [54,] 8530.35802 5701.35802 [55,] 9476.35802 8530.35802 [56,] 7774.35802 9476.35802 [57,] 8516.35802 7774.35802 [58,] 10608.35802 8516.35802 [59,] 8444.35802 10608.35802 [60,] 9370.35802 8444.35802 [61,] 6432.35802 9370.35802 [62,] 8905.35802 6432.35802 [63,] 7035.35802 8905.35802 [64,] 10627.35802 7035.35802 [65,] 8379.35802 10627.35802 [66,] 9519.35802 8379.35802 [67,] 10128.35802 9519.35802 [68,] 7927.35802 10128.35802 [69,] 9398.35802 7927.35802 [70,] 9125.35802 9398.35802 [71,] 8678.35802 9125.35802 [72,] 8827.35802 8678.35802 [73,] 5253.35802 8827.35802 [74,] 6569.35802 5253.35802 [75,] 11438.35802 6569.35802 [76,] 11871.35802 11438.35802 [77,] 10739.35802 11871.35802 [78,] 12407.35802 10739.35802 [79,] 12266.35802 12407.35802 [80,] 12543.35802 12266.35802 [81,] -17492.75676 12543.35802 [82,] -15154.75676 -17492.75676 [83,] -18431.75676 -15154.75676 [84,] -18813.75676 -18431.75676 [85,] -21505.75676 -18813.75676 [86,] -17475.75676 -21505.75676 [87,] -18120.75676 -17475.75676 [88,] -12505.75676 -18120.75676 [89,] -13589.75676 -12505.75676 [90,] -14341.75676 -13589.75676 [91,] -14519.75676 -14341.75676 [92,] -15531.75676 -14519.75676 [93,] -14450.75676 -15531.75676 [94,] -11607.75676 -14450.75676 [95,] -13029.75676 -11607.75676 [96,] -9855.75676 -13029.75676 [97,] -17199.75676 -9855.75676 [98,] -13449.75676 -17199.75676 [99,] -13365.75676 -13449.75676 [100,] -9935.75676 -13365.75676 [101,] -10652.75676 -9935.75676 [102,] -9501.75676 -10652.75676 [103,] -9639.75676 -9501.75676 [104,] -10408.75676 -9639.75676 [105,] -7700.75676 -10408.75676 [106,] -5902.75676 -7700.75676 [107,] -7448.75676 -5902.75676 [108,] -7095.75676 -7448.75676 [109,] -11096.75676 -7095.75676 [110,] -7540.75676 -11096.75676 [111,] -8679.75676 -7540.75676 [112,] -3517.75676 -8679.75676 [113,] -6415.75676 -3517.75676 [114,] -5998.75676 -6415.75676 [115,] -6629.75676 -5998.75676 [116,] -9307.75676 -6629.75676 [117,] -8294.75676 -9307.75676 [118,] -5410.75676 -8294.75676 [119,] -6056.75676 -5410.75676 [120,] -4842.75676 -6056.75676 [121,] -5508.75676 -4842.75676 [122,] -1827.75676 -5508.75676 [123,] -538.75676 -1827.75676 [124,] -2257.75676 -538.75676 [125,] -5289.75676 -2257.75676 [126,] -2739.75676 -5289.75676 [127,] -3584.75676 -2739.75676 [128,] 1962.24324 -3584.75676 [129,] 1247.24324 1962.24324 [130,] 196.24324 1247.24324 [131,] -2446.75676 196.24324 [132,] -1580.75676 -2446.75676 [133,] -5242.75676 -1580.75676 [134,] 1024.24324 -5242.75676 [135,] 1568.24324 1024.24324 [136,] 2650.24324 1568.24324 [137,] -1416.75676 2650.24324 [138,] 2983.24324 -1416.75676 [139,] 1646.24324 2983.24324 [140,] 3035.24324 1646.24324 [141,] 1896.24324 3035.24324 [142,] 3061.24324 1896.24324 [143,] -1081.75676 3061.24324 [144,] -4159.75676 -1081.75676 [145,] -2742.75676 -4159.75676 [146,] 1158.24324 -2742.75676 [147,] 453.24324 1158.24324 [148,] 4221.24324 453.24324 [149,] 90.24324 4221.24324 [150,] -85.75676 90.24324 [151,] 2413.24324 -85.75676 [152,] 4503.24324 2413.24324 [153,] 4338.24324 4503.24324 [154,] 2072.24324 4338.24324 [155,] 2585.24324 2072.24324 [156,] 2230.24324 2585.24324 [157,] 899.24324 2230.24324 [158,] 5766.24324 899.24324 [159,] 5523.24324 5766.24324 [160,] 8402.24324 5523.24324 [161,] 6264.24324 8402.24324 [162,] 3083.24324 6264.24324 [163,] 2854.24324 3083.24324 [164,] 2537.24324 2854.24324 [165,] 5650.24324 2537.24324 [166,] 5724.24324 5650.24324 [167,] 3656.24324 5724.24324 [168,] 5077.24324 3656.24324 [169,] 2340.24324 5077.24324 [170,] 5286.24324 2340.24324 [171,] 7102.24324 5286.24324 [172,] 12968.24324 7102.24324 [173,] 9532.24324 12968.24324 [174,] 11652.24324 9532.24324 [175,] 14239.24324 11652.24324 [176,] 11780.24324 14239.24324 [177,] 13905.24324 11780.24324 [178,] 22043.24324 13905.24324 [179,] 15258.24324 22043.24324 [180,] 19555.24324 15258.24324 [181,] 16965.24324 19555.24324 [182,] 19334.24324 16965.24324 [183,] 21480.24324 19334.24324 [184,] 20887.24324 21480.24324 [185,] 20040.24324 20887.24324 [186,] 21894.24324 20040.24324 [187,] 21387.24324 21894.24324 [188,] 19964.24324 21387.24324 [189,] 21090.24324 19964.24324 [190,] 26474.24324 21090.24324 [191,] 37072.24324 26474.24324 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -31178.64198 -31052.64198 2 -25585.64198 -31178.64198 3 -23793.64198 -25585.64198 4 -19613.64198 -23793.64198 5 -17347.64198 -19613.64198 6 -16890.64198 -17347.64198 7 -15261.64198 -16890.64198 8 -15815.64198 -15261.64198 9 -14861.64198 -15815.64198 10 -14291.64198 -14861.64198 11 -13677.64198 -14291.64198 12 -12485.64198 -13677.64198 13 -11734.64198 -12485.64198 14 -10355.64198 -11734.64198 15 -11959.64198 -10355.64198 16 -9628.64198 -11959.64198 17 -7365.64198 -9628.64198 18 -7460.64198 -7365.64198 19 -6617.64198 -7460.64198 20 -7260.64198 -6617.64198 21 -5596.64198 -7260.64198 22 -4089.64198 -5596.64198 23 -3968.64198 -4089.64198 24 -5094.64198 -3968.64198 25 -5221.64198 -5094.64198 26 -4508.64198 -5221.64198 27 -1710.64198 -4508.64198 28 -1225.64198 -1710.64198 29 -1178.64198 -1225.64198 30 -294.64198 -1178.64198 31 2043.35802 -294.64198 32 308.35802 2043.35802 33 410.35802 308.35802 34 2632.35802 410.35802 35 1602.35802 2632.35802 36 4902.35802 1602.35802 37 -419.64198 4902.35802 38 2259.35802 -419.64198 39 4073.35802 2259.35802 40 5470.35802 4073.35802 41 5450.35802 5470.35802 42 6626.35802 5450.35802 43 8027.35802 6626.35802 44 6844.35802 8027.35802 45 8252.35802 6844.35802 46 8597.35802 8252.35802 47 8928.35802 8597.35802 48 6402.35802 8928.35802 49 1471.35802 6402.35802 50 5213.35802 1471.35802 51 4553.35802 5213.35802 52 6984.35802 4553.35802 53 5701.35802 6984.35802 54 8530.35802 5701.35802 55 9476.35802 8530.35802 56 7774.35802 9476.35802 57 8516.35802 7774.35802 58 10608.35802 8516.35802 59 8444.35802 10608.35802 60 9370.35802 8444.35802 61 6432.35802 9370.35802 62 8905.35802 6432.35802 63 7035.35802 8905.35802 64 10627.35802 7035.35802 65 8379.35802 10627.35802 66 9519.35802 8379.35802 67 10128.35802 9519.35802 68 7927.35802 10128.35802 69 9398.35802 7927.35802 70 9125.35802 9398.35802 71 8678.35802 9125.35802 72 8827.35802 8678.35802 73 5253.35802 8827.35802 74 6569.35802 5253.35802 75 11438.35802 6569.35802 76 11871.35802 11438.35802 77 10739.35802 11871.35802 78 12407.35802 10739.35802 79 12266.35802 12407.35802 80 12543.35802 12266.35802 81 -17492.75676 12543.35802 82 -15154.75676 -17492.75676 83 -18431.75676 -15154.75676 84 -18813.75676 -18431.75676 85 -21505.75676 -18813.75676 86 -17475.75676 -21505.75676 87 -18120.75676 -17475.75676 88 -12505.75676 -18120.75676 89 -13589.75676 -12505.75676 90 -14341.75676 -13589.75676 91 -14519.75676 -14341.75676 92 -15531.75676 -14519.75676 93 -14450.75676 -15531.75676 94 -11607.75676 -14450.75676 95 -13029.75676 -11607.75676 96 -9855.75676 -13029.75676 97 -17199.75676 -9855.75676 98 -13449.75676 -17199.75676 99 -13365.75676 -13449.75676 100 -9935.75676 -13365.75676 101 -10652.75676 -9935.75676 102 -9501.75676 -10652.75676 103 -9639.75676 -9501.75676 104 -10408.75676 -9639.75676 105 -7700.75676 -10408.75676 106 -5902.75676 -7700.75676 107 -7448.75676 -5902.75676 108 -7095.75676 -7448.75676 109 -11096.75676 -7095.75676 110 -7540.75676 -11096.75676 111 -8679.75676 -7540.75676 112 -3517.75676 -8679.75676 113 -6415.75676 -3517.75676 114 -5998.75676 -6415.75676 115 -6629.75676 -5998.75676 116 -9307.75676 -6629.75676 117 -8294.75676 -9307.75676 118 -5410.75676 -8294.75676 119 -6056.75676 -5410.75676 120 -4842.75676 -6056.75676 121 -5508.75676 -4842.75676 122 -1827.75676 -5508.75676 123 -538.75676 -1827.75676 124 -2257.75676 -538.75676 125 -5289.75676 -2257.75676 126 -2739.75676 -5289.75676 127 -3584.75676 -2739.75676 128 1962.24324 -3584.75676 129 1247.24324 1962.24324 130 196.24324 1247.24324 131 -2446.75676 196.24324 132 -1580.75676 -2446.75676 133 -5242.75676 -1580.75676 134 1024.24324 -5242.75676 135 1568.24324 1024.24324 136 2650.24324 1568.24324 137 -1416.75676 2650.24324 138 2983.24324 -1416.75676 139 1646.24324 2983.24324 140 3035.24324 1646.24324 141 1896.24324 3035.24324 142 3061.24324 1896.24324 143 -1081.75676 3061.24324 144 -4159.75676 -1081.75676 145 -2742.75676 -4159.75676 146 1158.24324 -2742.75676 147 453.24324 1158.24324 148 4221.24324 453.24324 149 90.24324 4221.24324 150 -85.75676 90.24324 151 2413.24324 -85.75676 152 4503.24324 2413.24324 153 4338.24324 4503.24324 154 2072.24324 4338.24324 155 2585.24324 2072.24324 156 2230.24324 2585.24324 157 899.24324 2230.24324 158 5766.24324 899.24324 159 5523.24324 5766.24324 160 8402.24324 5523.24324 161 6264.24324 8402.24324 162 3083.24324 6264.24324 163 2854.24324 3083.24324 164 2537.24324 2854.24324 165 5650.24324 2537.24324 166 5724.24324 5650.24324 167 3656.24324 5724.24324 168 5077.24324 3656.24324 169 2340.24324 5077.24324 170 5286.24324 2340.24324 171 7102.24324 5286.24324 172 12968.24324 7102.24324 173 9532.24324 12968.24324 174 11652.24324 9532.24324 175 14239.24324 11652.24324 176 11780.24324 14239.24324 177 13905.24324 11780.24324 178 22043.24324 13905.24324 179 15258.24324 22043.24324 180 19555.24324 15258.24324 181 16965.24324 19555.24324 182 19334.24324 16965.24324 183 21480.24324 19334.24324 184 20887.24324 21480.24324 185 20040.24324 20887.24324 186 21894.24324 20040.24324 187 21387.24324 21894.24324 188 19964.24324 21387.24324 189 21090.24324 19964.24324 190 26474.24324 21090.24324 191 37072.24324 26474.24324 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/75qzj1229454486.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8av2q1229454486.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9r46y1229454486.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10rti71229454486.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/11y5fx1229454486.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/12tebu1229454487.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/13wggg1229454487.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/rcomp/tmp/14q4w81229454487.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/15pyvl1229454487.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/rcomp/tmp/16geev1229454487.tab") + } > > system("convert tmp/1y6gp1229454486.ps tmp/1y6gp1229454486.png") > system("convert tmp/2jdjn1229454486.ps tmp/2jdjn1229454486.png") > system("convert tmp/3n1qb1229454486.ps tmp/3n1qb1229454486.png") > system("convert tmp/42tza1229454486.ps tmp/42tza1229454486.png") > system("convert tmp/53y961229454486.ps tmp/53y961229454486.png") > system("convert tmp/6v4sl1229454486.ps tmp/6v4sl1229454486.png") > system("convert tmp/75qzj1229454486.ps tmp/75qzj1229454486.png") > system("convert tmp/8av2q1229454486.ps tmp/8av2q1229454486.png") > system("convert tmp/9r46y1229454486.ps tmp/9r46y1229454486.png") > system("convert tmp/10rti71229454486.ps tmp/10rti71229454486.png") > > > proc.time() user system elapsed 4.364 1.725 4.998