R version 2.13.0 (2011-04-13) Copyright (C) 2011 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i486-pc-linux-gnu (32-bit) R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(41 + ,1966 + ,4 + ,3 + ,39 + ,1966 + ,2 + ,1 + ,50 + ,1966 + ,3 + ,2 + ,40 + ,1966 + ,6 + ,3 + ,43 + ,1966 + ,5 + ,1 + ,38 + ,1966 + ,1 + ,2 + ,44 + ,1966 + ,3 + ,3 + ,35 + ,1966 + ,5 + ,3 + ,39 + ,1966 + ,2 + ,2 + ,35 + ,1966 + ,3 + ,1 + ,29 + ,1966 + ,6 + ,2 + ,49 + ,1966 + ,2 + ,1 + ,50 + ,1967 + ,5 + ,2 + ,59 + ,1967 + ,3 + ,1 + ,63 + ,1967 + ,1 + ,3 + ,32 + ,1967 + ,2 + ,2 + ,39 + ,1967 + ,4 + ,1 + ,47 + ,1967 + ,3 + ,2 + ,53 + ,1967 + ,4 + ,3 + ,60 + ,1967 + ,6 + ,2 + ,57 + ,1967 + ,2 + ,1 + ,52 + ,1967 + ,1 + ,2 + ,70 + ,1967 + ,4 + ,3 + ,90 + ,1967 + ,2 + ,2 + ,74 + ,1968 + ,1 + ,3 + ,62 + ,1968 + ,2 + ,3 + ,55 + ,1968 + ,5 + ,2 + ,84 + ,1968 + ,3 + ,1 + ,94 + ,1968 + ,6 + ,2 + ,70 + ,1968 + ,3 + ,1 + ,108 + ,1968 + ,1 + ,2 + ,139 + ,1968 + ,3 + ,3 + ,120 + ,1968 + ,5 + ,2 + ,97 + ,1968 + ,2 + ,1 + ,126 + ,1968 + ,3 + ,1 + ,149 + ,1968 + ,5 + ,1 + ,158 + ,1969 + ,6 + ,2 + ,124 + ,1969 + ,2 + ,1 + ,140 + ,1969 + ,1 + ,2 + ,109 + ,1969 + ,6 + ,3 + ,114 + ,1969 + ,4 + ,3 + ,77 + ,1969 + ,3 + ,2 + ,120 + ,1969 + ,2 + ,3 + ,133 + ,1969 + ,1 + ,1 + ,110 + ,1969 + ,2 + ,3 + ,92 + ,1969 + ,3 + ,1 + ,97 + ,1969 + ,5 + ,2 + ,78 + ,1969 + ,4 + ,3 + ,99 + ,1970 + ,6 + ,2 + ,107 + ,1970 + ,5 + ,1 + ,112 + ,1970 + ,2 + ,2 + ,90 + ,1970 + ,3 + ,3 + ,98 + ,1970 + ,1 + ,2 + ,125 + ,1970 + ,3 + ,1 + ,155 + ,1970 + ,2 + ,2 + ,190 + ,1970 + ,4 + ,3 + ,236 + ,1970 + ,5 + ,2 + ,189 + ,1970 + ,2 + ,3 + ,174 + ,1970 + ,3 + ,2 + ,178 + ,1970 + ,6 + ,1 + ,136 + ,1971 + ,4 + ,2 + ,161 + ,1971 + ,1 + ,3 + ,171 + ,1971 + ,3 + ,2 + ,149 + ,1971 + ,1 + ,3 + ,184 + ,1971 + ,2 + ,1 + ,155 + ,1971 + ,4 + ,2 + ,276 + ,1971 + ,2 + ,3 + ,224 + ,1971 + ,3 + ,2 + ,213 + ,1971 + ,4 + ,1 + ,279 + ,1971 + ,3 + ,2 + ,268 + ,1971 + ,5 + ,3 + ,287 + ,1971 + ,6 + ,1 + ,238 + ,1972 + ,6 + ,2 + ,213 + ,1972 + ,6 + ,3 + ,257 + ,1972 + ,3 + ,1 + ,293 + ,1972 + ,1 + ,3 + ,212 + ,1972 + ,1 + ,2 + ,246 + ,1972 + ,2 + ,3 + ,353 + ,1972 + ,4 + ,2 + ,339 + ,1972 + ,3 + ,1 + ,308 + ,1972 + ,2 + ,2 + ,247 + ,1972 + ,1 + ,3 + ,257 + ,1972 + ,2 + ,2 + ,322 + ,1972 + ,4 + ,2 + ,298 + ,1973 + ,4 + ,3 + ,273 + ,1973 + ,3 + ,2 + ,312 + ,1973 + ,5 + ,3 + ,249 + ,1973 + ,6 + ,1 + ,286 + ,1973 + ,2 + ,2 + ,279 + ,1973 + ,3 + ,3 + ,309 + ,1973 + ,4 + ,2 + ,401 + ,1973 + ,2 + ,1 + ,309 + ,1973 + ,3 + ,2 + ,328 + ,1973 + ,1 + ,3 + ,353 + ,1973 + ,2 + ,2 + ,354 + ,1973 + ,5 + ,1 + ,327 + ,1974 + ,3 + ,2 + ,324 + ,1974 + ,6 + ,3 + ,285 + ,1974 + ,3 + ,2 + ,243 + ,1974 + ,2 + ,1 + ,241 + ,1974 + ,1 + ,2 + ,287 + ,1974 + ,4 + ,3 + ,355 + ,1974 + ,2 + ,2 + ,460 + ,1974 + ,4 + ,2 + ,364 + ,1974 + ,6 + ,2 + ,487 + ,1974 + ,3 + ,2 + ,452 + ,1974 + ,5 + ,1 + ,391 + ,1974 + ,1 + ,2 + ,500 + ,1975 + ,3 + ,3 + ,451 + ,1975 + ,2 + ,2 + ,375 + ,1975 + ,4 + ,3 + ,372 + ,1975 + ,2 + ,1 + ,302 + ,1975 + ,3 + ,3 + ,316 + ,1975 + ,1 + ,3 + ,398 + ,1975 + ,4 + ,3 + ,394 + ,1975 + ,6 + ,2 + ,431 + ,1975 + ,2 + ,1 + ,431 + ,1975 + ,5 + ,2) + ,dim=c(4 + ,118) + ,dimnames=list(c('Kilometers' + ,'Bouwjaar' + ,'Model' + ,'Kleur') + ,1:118)) > y <- array(NA,dim=c(4,118),dimnames=list(c('Kilometers','Bouwjaar','Model','Kleur'),1:118)) > 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 Kilometers Bouwjaar Model Kleur 1 41 1966 4 3 2 39 1966 2 1 3 50 1966 3 2 4 40 1966 6 3 5 43 1966 5 1 6 38 1966 1 2 7 44 1966 3 3 8 35 1966 5 3 9 39 1966 2 2 10 35 1966 3 1 11 29 1966 6 2 12 49 1966 2 1 13 50 1967 5 2 14 59 1967 3 1 15 63 1967 1 3 16 32 1967 2 2 17 39 1967 4 1 18 47 1967 3 2 19 53 1967 4 3 20 60 1967 6 2 21 57 1967 2 1 22 52 1967 1 2 23 70 1967 4 3 24 90 1967 2 2 25 74 1968 1 3 26 62 1968 2 3 27 55 1968 5 2 28 84 1968 3 1 29 94 1968 6 2 30 70 1968 3 1 31 108 1968 1 2 32 139 1968 3 3 33 120 1968 5 2 34 97 1968 2 1 35 126 1968 3 1 36 149 1968 5 1 37 158 1969 6 2 38 124 1969 2 1 39 140 1969 1 2 40 109 1969 6 3 41 114 1969 4 3 42 77 1969 3 2 43 120 1969 2 3 44 133 1969 1 1 45 110 1969 2 3 46 92 1969 3 1 47 97 1969 5 2 48 78 1969 4 3 49 99 1970 6 2 50 107 1970 5 1 51 112 1970 2 2 52 90 1970 3 3 53 98 1970 1 2 54 125 1970 3 1 55 155 1970 2 2 56 190 1970 4 3 57 236 1970 5 2 58 189 1970 2 3 59 174 1970 3 2 60 178 1970 6 1 61 136 1971 4 2 62 161 1971 1 3 63 171 1971 3 2 64 149 1971 1 3 65 184 1971 2 1 66 155 1971 4 2 67 276 1971 2 3 68 224 1971 3 2 69 213 1971 4 1 70 279 1971 3 2 71 268 1971 5 3 72 287 1971 6 1 73 238 1972 6 2 74 213 1972 6 3 75 257 1972 3 1 76 293 1972 1 3 77 212 1972 1 2 78 246 1972 2 3 79 353 1972 4 2 80 339 1972 3 1 81 308 1972 2 2 82 247 1972 1 3 83 257 1972 2 2 84 322 1972 4 2 85 298 1973 4 3 86 273 1973 3 2 87 312 1973 5 3 88 249 1973 6 1 89 286 1973 2 2 90 279 1973 3 3 91 309 1973 4 2 92 401 1973 2 1 93 309 1973 3 2 94 328 1973 1 3 95 353 1973 2 2 96 354 1973 5 1 97 327 1974 3 2 98 324 1974 6 3 99 285 1974 3 2 100 243 1974 2 1 101 241 1974 1 2 102 287 1974 4 3 103 355 1974 2 2 104 460 1974 4 2 105 364 1974 6 2 106 487 1974 3 2 107 452 1974 5 1 108 391 1974 1 2 109 500 1975 3 3 110 451 1975 2 2 111 375 1975 4 3 112 372 1975 2 1 113 302 1975 3 3 114 316 1975 1 3 115 398 1975 4 3 116 394 1975 6 2 117 431 1975 2 1 118 431 1975 5 2 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Bouwjaar Model Kleur -82371.921 41.907 2.756 -7.197 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -107.325 -27.189 -1.711 32.443 141.116 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -82371.921 3077.104 -26.769 <2e-16 *** Bouwjaar 41.907 1.562 26.827 <2e-16 *** Model 2.756 2.786 0.989 0.325 Kleur -7.197 5.899 -1.220 0.225 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 47.92 on 114 degrees of freedom Multiple R-squared: 0.8635, Adjusted R-squared: 0.8599 F-statistic: 240.4 on 3 and 114 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,] 2.204672e-03 4.409344e-03 0.9977953 [2,] 4.333911e-04 8.667821e-04 0.9995666 [3,] 4.940244e-05 9.880489e-05 0.9999506 [4,] 9.015985e-06 1.803197e-05 0.9999910 [5,] 3.543834e-06 7.087667e-06 0.9999965 [6,] 9.808138e-07 1.961628e-06 0.9999990 [7,] 1.168891e-07 2.337782e-07 0.9999999 [8,] 1.759890e-08 3.519779e-08 1.0000000 [9,] 2.230010e-09 4.460020e-09 1.0000000 [10,] 5.300151e-08 1.060030e-07 0.9999999 [11,] 1.410134e-08 2.820268e-08 1.0000000 [12,] 2.324850e-09 4.649699e-09 1.0000000 [13,] 4.205597e-10 8.411194e-10 1.0000000 [14,] 2.213562e-10 4.427125e-10 1.0000000 [15,] 4.608021e-11 9.216042e-11 1.0000000 [16,] 7.362652e-12 1.472530e-11 1.0000000 [17,] 8.745822e-12 1.749164e-11 1.0000000 [18,] 4.511055e-10 9.022110e-10 1.0000000 [19,] 9.913692e-11 1.982738e-10 1.0000000 [20,] 3.188853e-11 6.377706e-11 1.0000000 [21,] 9.474367e-12 1.894873e-11 1.0000000 [22,] 6.200344e-12 1.240069e-11 1.0000000 [23,] 1.109734e-11 2.219467e-11 1.0000000 [24,] 2.590486e-12 5.180973e-12 1.0000000 [25,] 1.166788e-11 2.333575e-11 1.0000000 [26,] 2.844151e-09 5.688301e-09 1.0000000 [27,] 7.353772e-09 1.470754e-08 1.0000000 [28,] 3.143040e-09 6.286079e-09 1.0000000 [29,] 8.219978e-09 1.643996e-08 1.0000000 [30,] 9.660535e-08 1.932107e-07 0.9999999 [31,] 8.565191e-08 1.713038e-07 0.9999999 [32,] 3.370413e-08 6.740826e-08 1.0000000 [33,] 1.752059e-08 3.504118e-08 1.0000000 [34,] 9.749589e-09 1.949918e-08 1.0000000 [35,] 4.093170e-09 8.186340e-09 1.0000000 [36,] 1.071497e-08 2.142995e-08 1.0000000 [37,] 4.361384e-09 8.722768e-09 1.0000000 [38,] 1.900457e-09 3.800914e-09 1.0000000 [39,] 7.678451e-10 1.535690e-09 1.0000000 [40,] 6.994112e-10 1.398822e-09 1.0000000 [41,] 4.220157e-10 8.440314e-10 1.0000000 [42,] 5.049735e-10 1.009947e-09 1.0000000 [43,] 1.083927e-09 2.167854e-09 1.0000000 [44,] 1.361481e-09 2.722962e-09 1.0000000 [45,] 9.375186e-10 1.875037e-09 1.0000000 [46,] 1.583160e-09 3.166320e-09 1.0000000 [47,] 1.728462e-09 3.456924e-09 1.0000000 [48,] 1.020898e-09 2.041797e-09 1.0000000 [49,] 7.312443e-10 1.462489e-09 1.0000000 [50,] 3.694038e-09 7.388076e-09 1.0000000 [51,] 2.896125e-07 5.792250e-07 0.9999997 [52,] 4.472446e-07 8.944893e-07 0.9999996 [53,] 3.244154e-07 6.488308e-07 0.9999997 [54,] 2.328527e-07 4.657055e-07 0.9999998 [55,] 3.814727e-07 7.629455e-07 0.9999996 [56,] 2.186896e-07 4.373793e-07 0.9999998 [57,] 1.458789e-07 2.917578e-07 0.9999999 [58,] 1.136829e-07 2.273657e-07 0.9999999 [59,] 8.977035e-08 1.795407e-07 0.9999999 [60,] 1.120824e-07 2.241649e-07 0.9999999 [61,] 3.535874e-06 7.071747e-06 0.9999965 [62,] 3.747758e-06 7.495517e-06 0.9999963 [63,] 3.582981e-06 7.165962e-06 0.9999964 [64,] 2.308436e-05 4.616872e-05 0.9999769 [65,] 5.792444e-05 1.158489e-04 0.9999421 [66,] 1.524622e-04 3.049245e-04 0.9998475 [67,] 1.113494e-04 2.226989e-04 0.9998887 [68,] 1.022304e-04 2.044608e-04 0.9998978 [69,] 8.440564e-05 1.688113e-04 0.9999156 [70,] 1.364941e-04 2.729882e-04 0.9998635 [71,] 1.195635e-04 2.391271e-04 0.9998804 [72,] 7.584013e-05 1.516803e-04 0.9999242 [73,] 4.762551e-04 9.525102e-04 0.9995237 [74,] 1.046161e-03 2.092322e-03 0.9989538 [75,] 1.202187e-03 2.404374e-03 0.9987978 [76,] 7.519750e-04 1.503950e-03 0.9992480 [77,] 4.729898e-04 9.459795e-04 0.9995270 [78,] 6.281992e-04 1.256398e-03 0.9993718 [79,] 3.827740e-04 7.655481e-04 0.9996172 [80,] 2.681549e-04 5.363099e-04 0.9997318 [81,] 1.657548e-04 3.315096e-04 0.9998342 [82,] 4.265049e-04 8.530099e-04 0.9995735 [83,] 2.731286e-04 5.462572e-04 0.9997269 [84,] 1.670615e-04 3.341229e-04 0.9998329 [85,] 1.083960e-04 2.167920e-04 0.9998916 [86,] 3.302370e-04 6.604739e-04 0.9996698 [87,] 1.954932e-04 3.909864e-04 0.9998045 [88,] 1.657577e-04 3.315155e-04 0.9998342 [89,] 1.957610e-04 3.915220e-04 0.9998042 [90,] 1.335628e-04 2.671257e-04 0.9998664 [91,] 7.427221e-05 1.485444e-04 0.9999257 [92,] 5.088964e-05 1.017793e-04 0.9999491 [93,] 6.703076e-05 1.340615e-04 0.9999330 [94,] 1.105956e-03 2.211912e-03 0.9988940 [95,] 1.068557e-02 2.137113e-02 0.9893144 [96,] 2.534860e-02 5.069720e-02 0.9746514 [97,] 2.761849e-02 5.523698e-02 0.9723815 [98,] 3.572714e-02 7.145428e-02 0.9642729 [99,] 5.375718e-02 1.075144e-01 0.9462428 [100,] 9.534648e-02 1.906930e-01 0.9046535 [101,] 7.309121e-02 1.461824e-01 0.9269088 [102,] 4.534000e-02 9.068000e-02 0.9546600 [103,] 3.724764e-01 7.449528e-01 0.6275236 [104,] 5.859742e-01 8.280516e-01 0.4140258 [105,] 4.331702e-01 8.663403e-01 0.5668298 > postscript(file="/var/wessaorg/rcomp/tmp/1fm2q1322152098.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2ch4l1322152098.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/39mfk1322152098.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4iuoc1322152098.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5tgsk1322152098.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 = 118 Frequency = 1 1 2 3 4 5 34.81061098 23.92890178 39.36975638 28.29825765 19.66037178 6 7 8 9 10 32.88210972 40.56678765 26.05443432 31.12593305 17.17272511 11 12 13 14 15 10.10122638 33.92890178 -8.04935016 -0.73402809 23.17238778 16 17 18 19 20 -17.78082015 -23.49020476 -5.53699682 4.90385778 -0.80552682 21 22 23 24 25 0.02214858 4.97535651 21.90385778 40.21917985 -7.73436542 26 27 28 29 30 -22.49054209 -44.95610336 -17.64078129 -8.71228003 -31.64078129 31 32 33 34 35 19.06860331 51.75328125 20.04389664 -1.88460463 24.35921871 36 37 38 39 40 41.84686537 13.38096677 -16.79135783 9.16185011 -28.42200196 41 42 43 44 45 -17.90964862 -59.35050323 -6.39729529 -5.03518116 -16.39729529 46 47 48 49 50 -51.54753450 -44.86285656 -53.90964862 -87.52578643 -83.96664103 51 52 53 54 55 -63.50107976 -81.06022516 -74.74490309 -60.45428770 -20.50107976 56 57 58 59 60 16.18359817 52.23039024 20.69595151 -4.25725643 -15.72281770 61 62 63 64 65 -86.92018630 -46.45462503 -49.16400963 -58.45462503 -40.60486424 66 67 68 69 70 -67.92018630 65.78919830 3.83599037 -17.11721757 58.83599037 71 72 73 74 75 49.52066830 51.37042910 -32.33929284 -50.14226157 -12.26779411 76 77 78 79 80 43.63862177 -44.55840950 -6.11755490 88.17306050 69.73220589 81 82 83 84 85 48.68541383 -2.36137823 -2.31458617 57.17306050 -1.53666144 86 87 88 89 90 -30.97751604 9.70716190 -70.44307731 -15.22133937 -17.78048477 91 92 93 94 95 2.26630729 92.58162936 5.02248396 36.73186857 51.77866063 96 97 98 99 100 37.31309936 -18.88426924 -22.95576797 -60.88426924 -107.32512384 101 102 103 104 105 -99.37191591 -54.44341464 11.87190743 111.35955409 9.84720076 106 107 108 109 110 141.11573076 93.40634615 50.62808409 119.40600883 65.96515422 111 112 113 114 115 -8.35016784 -20.23187705 -78.59399117 -59.08163784 14.64983216 116 117 118 -2.05955245 38.76812295 37.69662422 > postscript(file="/var/wessaorg/rcomp/tmp/6sl1m1322152098.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 = 118 Frequency = 1 lag(myerror, k = 1) myerror 0 34.81061098 NA 1 23.92890178 34.81061098 2 39.36975638 23.92890178 3 28.29825765 39.36975638 4 19.66037178 28.29825765 5 32.88210972 19.66037178 6 40.56678765 32.88210972 7 26.05443432 40.56678765 8 31.12593305 26.05443432 9 17.17272511 31.12593305 10 10.10122638 17.17272511 11 33.92890178 10.10122638 12 -8.04935016 33.92890178 13 -0.73402809 -8.04935016 14 23.17238778 -0.73402809 15 -17.78082015 23.17238778 16 -23.49020476 -17.78082015 17 -5.53699682 -23.49020476 18 4.90385778 -5.53699682 19 -0.80552682 4.90385778 20 0.02214858 -0.80552682 21 4.97535651 0.02214858 22 21.90385778 4.97535651 23 40.21917985 21.90385778 24 -7.73436542 40.21917985 25 -22.49054209 -7.73436542 26 -44.95610336 -22.49054209 27 -17.64078129 -44.95610336 28 -8.71228003 -17.64078129 29 -31.64078129 -8.71228003 30 19.06860331 -31.64078129 31 51.75328125 19.06860331 32 20.04389664 51.75328125 33 -1.88460463 20.04389664 34 24.35921871 -1.88460463 35 41.84686537 24.35921871 36 13.38096677 41.84686537 37 -16.79135783 13.38096677 38 9.16185011 -16.79135783 39 -28.42200196 9.16185011 40 -17.90964862 -28.42200196 41 -59.35050323 -17.90964862 42 -6.39729529 -59.35050323 43 -5.03518116 -6.39729529 44 -16.39729529 -5.03518116 45 -51.54753450 -16.39729529 46 -44.86285656 -51.54753450 47 -53.90964862 -44.86285656 48 -87.52578643 -53.90964862 49 -83.96664103 -87.52578643 50 -63.50107976 -83.96664103 51 -81.06022516 -63.50107976 52 -74.74490309 -81.06022516 53 -60.45428770 -74.74490309 54 -20.50107976 -60.45428770 55 16.18359817 -20.50107976 56 52.23039024 16.18359817 57 20.69595151 52.23039024 58 -4.25725643 20.69595151 59 -15.72281770 -4.25725643 60 -86.92018630 -15.72281770 61 -46.45462503 -86.92018630 62 -49.16400963 -46.45462503 63 -58.45462503 -49.16400963 64 -40.60486424 -58.45462503 65 -67.92018630 -40.60486424 66 65.78919830 -67.92018630 67 3.83599037 65.78919830 68 -17.11721757 3.83599037 69 58.83599037 -17.11721757 70 49.52066830 58.83599037 71 51.37042910 49.52066830 72 -32.33929284 51.37042910 73 -50.14226157 -32.33929284 74 -12.26779411 -50.14226157 75 43.63862177 -12.26779411 76 -44.55840950 43.63862177 77 -6.11755490 -44.55840950 78 88.17306050 -6.11755490 79 69.73220589 88.17306050 80 48.68541383 69.73220589 81 -2.36137823 48.68541383 82 -2.31458617 -2.36137823 83 57.17306050 -2.31458617 84 -1.53666144 57.17306050 85 -30.97751604 -1.53666144 86 9.70716190 -30.97751604 87 -70.44307731 9.70716190 88 -15.22133937 -70.44307731 89 -17.78048477 -15.22133937 90 2.26630729 -17.78048477 91 92.58162936 2.26630729 92 5.02248396 92.58162936 93 36.73186857 5.02248396 94 51.77866063 36.73186857 95 37.31309936 51.77866063 96 -18.88426924 37.31309936 97 -22.95576797 -18.88426924 98 -60.88426924 -22.95576797 99 -107.32512384 -60.88426924 100 -99.37191591 -107.32512384 101 -54.44341464 -99.37191591 102 11.87190743 -54.44341464 103 111.35955409 11.87190743 104 9.84720076 111.35955409 105 141.11573076 9.84720076 106 93.40634615 141.11573076 107 50.62808409 93.40634615 108 119.40600883 50.62808409 109 65.96515422 119.40600883 110 -8.35016784 65.96515422 111 -20.23187705 -8.35016784 112 -78.59399117 -20.23187705 113 -59.08163784 -78.59399117 114 14.64983216 -59.08163784 115 -2.05955245 14.64983216 116 38.76812295 -2.05955245 117 37.69662422 38.76812295 118 NA 37.69662422 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 23.92890178 34.81061098 [2,] 39.36975638 23.92890178 [3,] 28.29825765 39.36975638 [4,] 19.66037178 28.29825765 [5,] 32.88210972 19.66037178 [6,] 40.56678765 32.88210972 [7,] 26.05443432 40.56678765 [8,] 31.12593305 26.05443432 [9,] 17.17272511 31.12593305 [10,] 10.10122638 17.17272511 [11,] 33.92890178 10.10122638 [12,] -8.04935016 33.92890178 [13,] -0.73402809 -8.04935016 [14,] 23.17238778 -0.73402809 [15,] -17.78082015 23.17238778 [16,] -23.49020476 -17.78082015 [17,] -5.53699682 -23.49020476 [18,] 4.90385778 -5.53699682 [19,] -0.80552682 4.90385778 [20,] 0.02214858 -0.80552682 [21,] 4.97535651 0.02214858 [22,] 21.90385778 4.97535651 [23,] 40.21917985 21.90385778 [24,] -7.73436542 40.21917985 [25,] -22.49054209 -7.73436542 [26,] -44.95610336 -22.49054209 [27,] -17.64078129 -44.95610336 [28,] -8.71228003 -17.64078129 [29,] -31.64078129 -8.71228003 [30,] 19.06860331 -31.64078129 [31,] 51.75328125 19.06860331 [32,] 20.04389664 51.75328125 [33,] -1.88460463 20.04389664 [34,] 24.35921871 -1.88460463 [35,] 41.84686537 24.35921871 [36,] 13.38096677 41.84686537 [37,] -16.79135783 13.38096677 [38,] 9.16185011 -16.79135783 [39,] -28.42200196 9.16185011 [40,] -17.90964862 -28.42200196 [41,] -59.35050323 -17.90964862 [42,] -6.39729529 -59.35050323 [43,] -5.03518116 -6.39729529 [44,] -16.39729529 -5.03518116 [45,] -51.54753450 -16.39729529 [46,] -44.86285656 -51.54753450 [47,] -53.90964862 -44.86285656 [48,] -87.52578643 -53.90964862 [49,] -83.96664103 -87.52578643 [50,] -63.50107976 -83.96664103 [51,] -81.06022516 -63.50107976 [52,] -74.74490309 -81.06022516 [53,] -60.45428770 -74.74490309 [54,] -20.50107976 -60.45428770 [55,] 16.18359817 -20.50107976 [56,] 52.23039024 16.18359817 [57,] 20.69595151 52.23039024 [58,] -4.25725643 20.69595151 [59,] -15.72281770 -4.25725643 [60,] -86.92018630 -15.72281770 [61,] -46.45462503 -86.92018630 [62,] -49.16400963 -46.45462503 [63,] -58.45462503 -49.16400963 [64,] -40.60486424 -58.45462503 [65,] -67.92018630 -40.60486424 [66,] 65.78919830 -67.92018630 [67,] 3.83599037 65.78919830 [68,] -17.11721757 3.83599037 [69,] 58.83599037 -17.11721757 [70,] 49.52066830 58.83599037 [71,] 51.37042910 49.52066830 [72,] -32.33929284 51.37042910 [73,] -50.14226157 -32.33929284 [74,] -12.26779411 -50.14226157 [75,] 43.63862177 -12.26779411 [76,] -44.55840950 43.63862177 [77,] -6.11755490 -44.55840950 [78,] 88.17306050 -6.11755490 [79,] 69.73220589 88.17306050 [80,] 48.68541383 69.73220589 [81,] -2.36137823 48.68541383 [82,] -2.31458617 -2.36137823 [83,] 57.17306050 -2.31458617 [84,] -1.53666144 57.17306050 [85,] -30.97751604 -1.53666144 [86,] 9.70716190 -30.97751604 [87,] -70.44307731 9.70716190 [88,] -15.22133937 -70.44307731 [89,] -17.78048477 -15.22133937 [90,] 2.26630729 -17.78048477 [91,] 92.58162936 2.26630729 [92,] 5.02248396 92.58162936 [93,] 36.73186857 5.02248396 [94,] 51.77866063 36.73186857 [95,] 37.31309936 51.77866063 [96,] -18.88426924 37.31309936 [97,] -22.95576797 -18.88426924 [98,] -60.88426924 -22.95576797 [99,] -107.32512384 -60.88426924 [100,] -99.37191591 -107.32512384 [101,] -54.44341464 -99.37191591 [102,] 11.87190743 -54.44341464 [103,] 111.35955409 11.87190743 [104,] 9.84720076 111.35955409 [105,] 141.11573076 9.84720076 [106,] 93.40634615 141.11573076 [107,] 50.62808409 93.40634615 [108,] 119.40600883 50.62808409 [109,] 65.96515422 119.40600883 [110,] -8.35016784 65.96515422 [111,] -20.23187705 -8.35016784 [112,] -78.59399117 -20.23187705 [113,] -59.08163784 -78.59399117 [114,] 14.64983216 -59.08163784 [115,] -2.05955245 14.64983216 [116,] 38.76812295 -2.05955245 [117,] 37.69662422 38.76812295 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 23.92890178 34.81061098 2 39.36975638 23.92890178 3 28.29825765 39.36975638 4 19.66037178 28.29825765 5 32.88210972 19.66037178 6 40.56678765 32.88210972 7 26.05443432 40.56678765 8 31.12593305 26.05443432 9 17.17272511 31.12593305 10 10.10122638 17.17272511 11 33.92890178 10.10122638 12 -8.04935016 33.92890178 13 -0.73402809 -8.04935016 14 23.17238778 -0.73402809 15 -17.78082015 23.17238778 16 -23.49020476 -17.78082015 17 -5.53699682 -23.49020476 18 4.90385778 -5.53699682 19 -0.80552682 4.90385778 20 0.02214858 -0.80552682 21 4.97535651 0.02214858 22 21.90385778 4.97535651 23 40.21917985 21.90385778 24 -7.73436542 40.21917985 25 -22.49054209 -7.73436542 26 -44.95610336 -22.49054209 27 -17.64078129 -44.95610336 28 -8.71228003 -17.64078129 29 -31.64078129 -8.71228003 30 19.06860331 -31.64078129 31 51.75328125 19.06860331 32 20.04389664 51.75328125 33 -1.88460463 20.04389664 34 24.35921871 -1.88460463 35 41.84686537 24.35921871 36 13.38096677 41.84686537 37 -16.79135783 13.38096677 38 9.16185011 -16.79135783 39 -28.42200196 9.16185011 40 -17.90964862 -28.42200196 41 -59.35050323 -17.90964862 42 -6.39729529 -59.35050323 43 -5.03518116 -6.39729529 44 -16.39729529 -5.03518116 45 -51.54753450 -16.39729529 46 -44.86285656 -51.54753450 47 -53.90964862 -44.86285656 48 -87.52578643 -53.90964862 49 -83.96664103 -87.52578643 50 -63.50107976 -83.96664103 51 -81.06022516 -63.50107976 52 -74.74490309 -81.06022516 53 -60.45428770 -74.74490309 54 -20.50107976 -60.45428770 55 16.18359817 -20.50107976 56 52.23039024 16.18359817 57 20.69595151 52.23039024 58 -4.25725643 20.69595151 59 -15.72281770 -4.25725643 60 -86.92018630 -15.72281770 61 -46.45462503 -86.92018630 62 -49.16400963 -46.45462503 63 -58.45462503 -49.16400963 64 -40.60486424 -58.45462503 65 -67.92018630 -40.60486424 66 65.78919830 -67.92018630 67 3.83599037 65.78919830 68 -17.11721757 3.83599037 69 58.83599037 -17.11721757 70 49.52066830 58.83599037 71 51.37042910 49.52066830 72 -32.33929284 51.37042910 73 -50.14226157 -32.33929284 74 -12.26779411 -50.14226157 75 43.63862177 -12.26779411 76 -44.55840950 43.63862177 77 -6.11755490 -44.55840950 78 88.17306050 -6.11755490 79 69.73220589 88.17306050 80 48.68541383 69.73220589 81 -2.36137823 48.68541383 82 -2.31458617 -2.36137823 83 57.17306050 -2.31458617 84 -1.53666144 57.17306050 85 -30.97751604 -1.53666144 86 9.70716190 -30.97751604 87 -70.44307731 9.70716190 88 -15.22133937 -70.44307731 89 -17.78048477 -15.22133937 90 2.26630729 -17.78048477 91 92.58162936 2.26630729 92 5.02248396 92.58162936 93 36.73186857 5.02248396 94 51.77866063 36.73186857 95 37.31309936 51.77866063 96 -18.88426924 37.31309936 97 -22.95576797 -18.88426924 98 -60.88426924 -22.95576797 99 -107.32512384 -60.88426924 100 -99.37191591 -107.32512384 101 -54.44341464 -99.37191591 102 11.87190743 -54.44341464 103 111.35955409 11.87190743 104 9.84720076 111.35955409 105 141.11573076 9.84720076 106 93.40634615 141.11573076 107 50.62808409 93.40634615 108 119.40600883 50.62808409 109 65.96515422 119.40600883 110 -8.35016784 65.96515422 111 -20.23187705 -8.35016784 112 -78.59399117 -20.23187705 113 -59.08163784 -78.59399117 114 14.64983216 -59.08163784 115 -2.05955245 14.64983216 116 38.76812295 -2.05955245 117 37.69662422 38.76812295 > 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/7j1wm1322152098.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8tyd91322152098.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9lgzy1322152098.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10x3j61322152098.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11qyr91322152098.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/12tglm1322152098.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/13we6o1322152098.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/14z8bj1322152098.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/1598531322152098.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/166jcr1322152098.tab") + } > > try(system("convert tmp/1fm2q1322152098.ps tmp/1fm2q1322152098.png",intern=TRUE)) character(0) > try(system("convert tmp/2ch4l1322152098.ps tmp/2ch4l1322152098.png",intern=TRUE)) character(0) > try(system("convert tmp/39mfk1322152098.ps tmp/39mfk1322152098.png",intern=TRUE)) character(0) > try(system("convert tmp/4iuoc1322152098.ps tmp/4iuoc1322152098.png",intern=TRUE)) character(0) > try(system("convert tmp/5tgsk1322152098.ps tmp/5tgsk1322152098.png",intern=TRUE)) character(0) > try(system("convert tmp/6sl1m1322152098.ps tmp/6sl1m1322152098.png",intern=TRUE)) character(0) > try(system("convert tmp/7j1wm1322152098.ps tmp/7j1wm1322152098.png",intern=TRUE)) character(0) > try(system("convert tmp/8tyd91322152098.ps tmp/8tyd91322152098.png",intern=TRUE)) character(0) > try(system("convert tmp/9lgzy1322152098.ps tmp/9lgzy1322152098.png",intern=TRUE)) character(0) > try(system("convert tmp/10x3j61322152098.ps tmp/10x3j61322152098.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.980 0.530 4.648