R version 2.9.0 (2009-04-17) Copyright (C) 2009 The R Foundation for Statistical Computing ISBN 3-900051-07-0 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(7969 + ,0 + ,8255 + ,8776 + ,8823 + ,9051 + ,8758 + ,0 + ,7969 + ,8255 + ,8776 + ,8823 + ,8693 + ,0 + ,8758 + ,7969 + ,8255 + ,8776 + ,8271 + ,0 + ,8693 + ,8758 + ,7969 + ,8255 + ,7790 + ,0 + ,8271 + ,8693 + ,8758 + ,7969 + ,7769 + ,0 + ,7790 + ,8271 + ,8693 + ,8758 + ,8170 + ,0 + ,7769 + ,7790 + ,8271 + ,8693 + ,8209 + ,0 + ,8170 + ,7769 + ,7790 + ,8271 + ,9395 + ,0 + ,8209 + ,8170 + ,7769 + ,7790 + ,9260 + ,0 + ,9395 + ,8209 + ,8170 + ,7769 + ,9018 + ,0 + ,9260 + ,9395 + ,8209 + ,8170 + ,8501 + ,0 + ,9018 + ,9260 + ,9395 + ,8209 + ,8500 + ,0 + ,8501 + ,9018 + ,9260 + ,9395 + ,9649 + ,0 + ,8500 + ,8501 + ,9018 + ,9260 + ,9319 + ,0 + ,9649 + ,8500 + ,8501 + ,9018 + ,8830 + ,0 + ,9319 + ,9649 + ,8500 + ,8501 + ,8436 + ,0 + ,8830 + ,9319 + ,9649 + ,8500 + ,8169 + ,0 + ,8436 + ,8830 + ,9319 + ,9649 + ,8269 + ,0 + ,8169 + ,8436 + ,8830 + ,9319 + ,7945 + ,0 + ,8269 + ,8169 + ,8436 + ,8830 + ,9144 + ,0 + ,7945 + ,8269 + ,8169 + ,8436 + ,8770 + ,0 + ,9144 + ,7945 + ,8269 + ,8169 + ,8834 + ,0 + ,8770 + ,9144 + ,7945 + ,8269 + ,7837 + ,0 + ,8834 + ,8770 + ,9144 + ,7945 + ,7792 + ,0 + ,7837 + ,8834 + ,8770 + ,9144 + ,8616 + ,0 + ,7792 + ,7837 + ,8834 + ,8770 + ,8518 + ,0 + ,8616 + ,7792 + ,7837 + ,8834 + ,7940 + ,0 + ,8518 + ,8616 + ,7792 + ,7837 + ,7545 + ,0 + ,7940 + ,8518 + ,8616 + ,7792 + ,7531 + ,0 + ,7545 + ,7940 + ,8518 + ,8616 + ,7665 + ,0 + ,7531 + ,7545 + ,7940 + ,8518 + ,7599 + ,0 + ,7665 + ,7531 + ,7545 + ,7940 + ,8444 + ,0 + ,7599 + ,7665 + ,7531 + ,7545 + ,8549 + ,0 + ,8444 + ,7599 + ,7665 + ,7531 + ,7986 + ,0 + ,8549 + ,8444 + ,7599 + ,7665 + ,7335 + ,0 + ,7986 + ,8549 + ,8444 + ,7599 + ,7287 + ,0 + ,7335 + ,7986 + ,8549 + ,8444 + ,7870 + ,0 + ,7287 + ,7335 + ,7986 + ,8549 + ,7839 + ,0 + ,7870 + ,7287 + ,7335 + ,7986 + ,7327 + ,0 + ,7839 + ,7870 + ,7287 + ,7335 + ,7259 + ,0 + ,7327 + ,7839 + ,7870 + ,7287 + ,6964 + ,0 + ,7259 + ,7327 + ,7839 + ,7870 + ,7271 + ,0 + ,6964 + ,7259 + ,7327 + ,7839 + ,6956 + ,0 + ,7271 + ,6964 + ,7259 + ,7327 + ,7608 + ,0 + ,6956 + ,7271 + ,6964 + ,7259 + ,7692 + ,0 + ,7608 + ,6956 + ,7271 + ,6964 + ,7255 + ,0 + ,7692 + ,7608 + ,6956 + ,7271 + ,6804 + ,0 + ,7255 + ,7692 + ,7608 + ,6956 + ,6655 + ,0 + ,6804 + ,7255 + ,7692 + ,7608 + ,7341 + ,0 + ,6655 + ,6804 + ,7255 + ,7692 + ,7602 + ,0 + ,7341 + ,6655 + ,6804 + ,7255 + ,7086 + ,0 + ,7602 + ,7341 + ,6655 + ,6804 + ,6625 + ,0 + ,7086 + ,7602 + ,7341 + ,6655 + ,6272 + ,0 + ,6625 + ,7086 + ,7602 + ,7341 + ,6576 + ,0 + ,6272 + ,6625 + ,7086 + ,7602 + ,6491 + ,0 + ,6576 + ,6272 + ,6625 + ,7086 + ,7649 + ,0 + ,6491 + ,6576 + ,6272 + ,6625 + ,7400 + ,0 + ,7649 + ,6491 + ,6576 + ,6272 + ,6913 + ,0 + ,7400 + ,7649 + ,6491 + ,6576 + ,6532 + ,0 + ,6913 + ,7400 + ,7649 + ,6491 + ,6486 + ,0 + ,6532 + ,6913 + ,7400 + ,7649 + ,7295 + ,0 + ,6486 + ,6532 + ,6913 + ,7400 + ,7556 + ,0 + ,7295 + ,6486 + ,6532 + ,6913 + ,7088 + ,1 + ,7556 + ,7295 + ,6486 + ,6532 + ,6952 + ,1 + ,7088 + ,7556 + ,7295 + ,6486 + ,6773 + ,1 + ,6952 + ,7088 + ,7556 + ,7295 + ,6917 + ,1 + ,6773 + ,6952 + ,7088 + ,7556 + ,7371 + ,1 + ,6917 + ,6773 + ,6952 + ,7088 + ,8221 + ,1 + ,7371 + ,6917 + ,6773 + ,6952 + ,7953 + ,1 + ,8221 + ,7371 + ,6917 + ,6773 + ,8027 + ,1 + ,7953 + ,8221 + ,7371 + ,6917 + ,7287 + ,1 + ,8027 + ,7953 + ,8221 + ,7371 + ,8076 + ,1 + ,7287 + ,8027 + ,7953 + ,8221 + ,8933 + ,1 + ,8076 + ,7287 + ,8027 + ,7953 + ,9433 + ,1 + ,8933 + ,8076 + ,7287 + ,8027 + ,9479 + ,1 + ,9433 + ,8933 + ,8076 + ,7287 + ,9199 + ,1 + ,9479 + ,9433 + ,8933 + ,8076 + ,9469 + ,1 + ,9199 + ,9479 + ,9433 + ,8933 + ,10015 + ,1 + ,9469 + ,9199 + ,9479 + ,9433 + ,10999 + ,1 + ,10015 + ,9469 + ,9199 + ,9479 + ,13009 + ,1 + ,10999 + ,10015 + ,9469 + ,9199 + ,13699 + ,1 + ,13009 + ,10999 + ,10015 + ,9469 + ,13895 + ,1 + ,13699 + ,13009 + ,10999 + ,10015 + ,13248 + ,1 + ,13895 + ,13699 + ,13009 + ,10999 + ,13973 + ,1 + ,13248 + ,13895 + ,13699 + ,13009 + ,15095 + ,1 + ,13973 + ,13248 + ,13895 + ,13699 + ,15201 + ,1 + ,15095 + ,13973 + ,13248 + ,13895 + ,14823 + ,1 + ,15201 + ,15095 + ,13973 + ,13248 + ,14538 + ,1 + ,14823 + ,15201 + ,15095 + ,13973 + ,14547 + ,1 + ,14538 + ,14823 + ,15201 + ,15095 + ,14407 + ,1 + ,14547 + ,14538 + ,14823 + ,15201) + ,dim=c(6 + ,91) + ,dimnames=list(c('Y' + ,'X' + ,'Y1' + ,'Y2' + ,'Y3' + ,'Y4') + ,1:91)) > y <- array(NA,dim=c(6,91),dimnames=list(c('Y','X','Y1','Y2','Y3','Y4'),1:91)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = '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 Y X Y1 Y2 Y3 Y4 t 1 7969 0 8255 8776 8823 9051 1 2 8758 0 7969 8255 8776 8823 2 3 8693 0 8758 7969 8255 8776 3 4 8271 0 8693 8758 7969 8255 4 5 7790 0 8271 8693 8758 7969 5 6 7769 0 7790 8271 8693 8758 6 7 8170 0 7769 7790 8271 8693 7 8 8209 0 8170 7769 7790 8271 8 9 9395 0 8209 8170 7769 7790 9 10 9260 0 9395 8209 8170 7769 10 11 9018 0 9260 9395 8209 8170 11 12 8501 0 9018 9260 9395 8209 12 13 8500 0 8501 9018 9260 9395 13 14 9649 0 8500 8501 9018 9260 14 15 9319 0 9649 8500 8501 9018 15 16 8830 0 9319 9649 8500 8501 16 17 8436 0 8830 9319 9649 8500 17 18 8169 0 8436 8830 9319 9649 18 19 8269 0 8169 8436 8830 9319 19 20 7945 0 8269 8169 8436 8830 20 21 9144 0 7945 8269 8169 8436 21 22 8770 0 9144 7945 8269 8169 22 23 8834 0 8770 9144 7945 8269 23 24 7837 0 8834 8770 9144 7945 24 25 7792 0 7837 8834 8770 9144 25 26 8616 0 7792 7837 8834 8770 26 27 8518 0 8616 7792 7837 8834 27 28 7940 0 8518 8616 7792 7837 28 29 7545 0 7940 8518 8616 7792 29 30 7531 0 7545 7940 8518 8616 30 31 7665 0 7531 7545 7940 8518 31 32 7599 0 7665 7531 7545 7940 32 33 8444 0 7599 7665 7531 7545 33 34 8549 0 8444 7599 7665 7531 34 35 7986 0 8549 8444 7599 7665 35 36 7335 0 7986 8549 8444 7599 36 37 7287 0 7335 7986 8549 8444 37 38 7870 0 7287 7335 7986 8549 38 39 7839 0 7870 7287 7335 7986 39 40 7327 0 7839 7870 7287 7335 40 41 7259 0 7327 7839 7870 7287 41 42 6964 0 7259 7327 7839 7870 42 43 7271 0 6964 7259 7327 7839 43 44 6956 0 7271 6964 7259 7327 44 45 7608 0 6956 7271 6964 7259 45 46 7692 0 7608 6956 7271 6964 46 47 7255 0 7692 7608 6956 7271 47 48 6804 0 7255 7692 7608 6956 48 49 6655 0 6804 7255 7692 7608 49 50 7341 0 6655 6804 7255 7692 50 51 7602 0 7341 6655 6804 7255 51 52 7086 0 7602 7341 6655 6804 52 53 6625 0 7086 7602 7341 6655 53 54 6272 0 6625 7086 7602 7341 54 55 6576 0 6272 6625 7086 7602 55 56 6491 0 6576 6272 6625 7086 56 57 7649 0 6491 6576 6272 6625 57 58 7400 0 7649 6491 6576 6272 58 59 6913 0 7400 7649 6491 6576 59 60 6532 0 6913 7400 7649 6491 60 61 6486 0 6532 6913 7400 7649 61 62 7295 0 6486 6532 6913 7400 62 63 7556 0 7295 6486 6532 6913 63 64 7088 1 7556 7295 6486 6532 64 65 6952 1 7088 7556 7295 6486 65 66 6773 1 6952 7088 7556 7295 66 67 6917 1 6773 6952 7088 7556 67 68 7371 1 6917 6773 6952 7088 68 69 8221 1 7371 6917 6773 6952 69 70 7953 1 8221 7371 6917 6773 70 71 8027 1 7953 8221 7371 6917 71 72 7287 1 8027 7953 8221 7371 72 73 8076 1 7287 8027 7953 8221 73 74 8933 1 8076 7287 8027 7953 74 75 9433 1 8933 8076 7287 8027 75 76 9479 1 9433 8933 8076 7287 76 77 9199 1 9479 9433 8933 8076 77 78 9469 1 9199 9479 9433 8933 78 79 10015 1 9469 9199 9479 9433 79 80 10999 1 10015 9469 9199 9479 80 81 13009 1 10999 10015 9469 9199 81 82 13699 1 13009 10999 10015 9469 82 83 13895 1 13699 13009 10999 10015 83 84 13248 1 13895 13699 13009 10999 84 85 13973 1 13248 13895 13699 13009 85 86 15095 1 13973 13248 13895 13699 86 87 15201 1 15095 13973 13248 13895 87 88 14823 1 15201 15095 13973 13248 88 89 14538 1 14823 15201 15095 13973 89 90 14547 1 14538 14823 15201 15095 90 91 14407 1 14547 14538 14823 15201 91 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) X Y1 Y2 Y3 Y4 -53.6519 389.3134 1.0648 -0.2535 -0.2026 0.3902 t 0.9382 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -858.00 -317.83 -98.75 168.83 1753.18 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -53.6519 278.5856 -0.193 0.847747 X 389.3134 203.3308 1.915 0.058937 . Y1 1.0648 0.1008 10.563 < 2e-16 *** Y2 -0.2535 0.1517 -1.671 0.098412 . Y3 -0.2026 0.1520 -1.333 0.186207 Y4 0.3902 0.1049 3.722 0.000357 *** t 0.9382 3.2853 0.286 0.775916 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 493.4 on 84 degrees of freedom Multiple R-squared: 0.9551, Adjusted R-squared: 0.9519 F-statistic: 297.8 on 6 and 84 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,] 0.89397314 0.21205372 0.1060269 [2,] 0.84936587 0.30126826 0.1506341 [3,] 0.75530629 0.48938741 0.2446937 [4,] 0.65213701 0.69572599 0.3478630 [5,] 0.77444569 0.45110861 0.2255543 [6,] 0.73823516 0.52352968 0.2617648 [7,] 0.66478217 0.67043567 0.3352178 [8,] 0.59692119 0.80615762 0.4030788 [9,] 0.61819285 0.76361430 0.3818072 [10,] 0.57077265 0.85845469 0.4292273 [11,] 0.62771591 0.74456817 0.3722841 [12,] 0.75187794 0.49624412 0.2481221 [13,] 0.73621062 0.52757876 0.2637894 [14,] 0.68034147 0.63931705 0.3196585 [15,] 0.72168743 0.55662513 0.2783126 [16,] 0.68840416 0.62319169 0.3115958 [17,] 0.70594436 0.58811128 0.2940556 [18,] 0.69015443 0.61969113 0.3098456 [19,] 0.69432536 0.61134927 0.3056746 [20,] 0.65374175 0.69251650 0.3462583 [21,] 0.60799399 0.78401201 0.3920060 [22,] 0.55408374 0.89183252 0.4459163 [23,] 0.50246966 0.99506067 0.4975303 [24,] 0.62224118 0.75551764 0.3777588 [25,] 0.56824202 0.86351596 0.4317580 [26,] 0.52534079 0.94931842 0.4746592 [27,] 0.48129295 0.96258590 0.5187070 [28,] 0.42760313 0.85520626 0.5723969 [29,] 0.39969467 0.79938933 0.6003053 [30,] 0.34867666 0.69735332 0.6513233 [31,] 0.32080019 0.64160038 0.6791998 [32,] 0.28747697 0.57495394 0.7125230 [33,] 0.26249201 0.52498403 0.7375080 [34,] 0.22602404 0.45204808 0.7739760 [35,] 0.20287430 0.40574861 0.7971257 [36,] 0.25969355 0.51938709 0.7403065 [37,] 0.22815559 0.45631117 0.7718444 [38,] 0.19388996 0.38777993 0.8061100 [39,] 0.16107588 0.32215175 0.8389241 [40,] 0.13386803 0.26773606 0.8661320 [41,] 0.16989208 0.33978416 0.8301079 [42,] 0.15109272 0.30218543 0.8489073 [43,] 0.12322360 0.24644719 0.8767764 [44,] 0.09976259 0.19952517 0.9002374 [45,] 0.08292249 0.16584498 0.9170775 [46,] 0.06893520 0.13787041 0.9310648 [47,] 0.05524226 0.11048452 0.9447577 [48,] 0.20881755 0.41763510 0.7911824 [49,] 0.16565200 0.33130400 0.8343480 [50,] 0.12956311 0.25912621 0.8704369 [51,] 0.09764660 0.19529320 0.9023534 [52,] 0.07396989 0.14793977 0.9260301 [53,] 0.08032351 0.16064702 0.9196765 [54,] 0.06023771 0.12047541 0.9397623 [55,] 0.04391085 0.08782170 0.9560891 [56,] 0.03719720 0.07439440 0.9628028 [57,] 0.02474037 0.04948073 0.9752596 [58,] 0.01583007 0.03166014 0.9841699 [59,] 0.01175524 0.02351049 0.9882448 [60,] 0.01992187 0.03984374 0.9800781 [61,] 0.01519107 0.03038213 0.9848089 [62,] 0.01198080 0.02396160 0.9880192 [63,] 0.02448534 0.04897069 0.9755147 [64,] 0.02888427 0.05776854 0.9711157 [65,] 0.02566301 0.05132602 0.9743370 [66,] 0.01878293 0.03756586 0.9812171 [67,] 0.01741069 0.03482138 0.9825893 [68,] 0.02751493 0.05502986 0.9724851 [69,] 0.02866314 0.05732628 0.9713369 [70,] 0.09568509 0.19137018 0.9043149 [71,] 0.57271480 0.85457039 0.4272852 [72,] 0.52067898 0.95864203 0.4793210 > postscript(file="/var/www/html/rcomp/tmp/1e8i61260038780.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2mnz91260038780.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3aa1l1260038780.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4tz4y1260038780.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5hgzj1260038780.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 = 91 Frequency = 1 1 2 3 4 5 6 -287.823881 752.149125 -313.658872 -322.009839 -99.597157 -37.397836 7 8 9 10 11 12 202.947420 -124.091613 1304.542653 5.063508 57.952446 -11.430435 13 14 15 16 17 18 -14.371443 1007.339528 -557.649129 -203.374953 71.931017 -415.671291 19 20 21 22 23 24 -102.490933 -490.608173 1177.455026 -431.882121 228.700604 -562.816949 25 26 27 28 29 30 -74.572825 702.575541 -512.170681 -397.928734 -18.723437 -100.989755 31 32 33 34 35 36 -132.028534 -199.685226 899.927953 120.101830 -407.094890 -235.950580 37 38 39 40 41 42 -42.883134 270.207640 -306.896602 -394.719154 210.531392 -376.578232 43 44 45 46 47 48 134.720636 -396.881622 634.185490 120.454903 -425.269818 -135.555467 49 50 51 52 53 54 -153.451000 454.612642 25.583989 -449.565308 -98.748874 -307.426524 55 56 57 58 59 60 48.247205 -342.933911 1090.072360 -215.124833 -280.217814 61.095224 61 62 63 64 65 66 -205.942283 553.005495 52.810237 -738.917300 -129.483062 -546.056604 67 68 69 70 71 72 -443.546407 -34.125252 384.815310 -575.098605 34.611249 -857.996780 73 74 75 76 77 78 350.792117 298.694651 -93.596020 84.949271 -252.460865 93.296650 79 80 81 82 83 84 94.082486 489.514673 1753.181194 556.677179 512.874524 -145.562464 85 86 87 88 89 90 672.573328 628.080745 -485.375012 -293.371876 -205.509954 -406.158500 91 -746.884677 > postscript(file="/var/www/html/rcomp/tmp/6373u1260038780.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 = 91 Frequency = 1 lag(myerror, k = 1) myerror 0 -287.823881 NA 1 752.149125 -287.823881 2 -313.658872 752.149125 3 -322.009839 -313.658872 4 -99.597157 -322.009839 5 -37.397836 -99.597157 6 202.947420 -37.397836 7 -124.091613 202.947420 8 1304.542653 -124.091613 9 5.063508 1304.542653 10 57.952446 5.063508 11 -11.430435 57.952446 12 -14.371443 -11.430435 13 1007.339528 -14.371443 14 -557.649129 1007.339528 15 -203.374953 -557.649129 16 71.931017 -203.374953 17 -415.671291 71.931017 18 -102.490933 -415.671291 19 -490.608173 -102.490933 20 1177.455026 -490.608173 21 -431.882121 1177.455026 22 228.700604 -431.882121 23 -562.816949 228.700604 24 -74.572825 -562.816949 25 702.575541 -74.572825 26 -512.170681 702.575541 27 -397.928734 -512.170681 28 -18.723437 -397.928734 29 -100.989755 -18.723437 30 -132.028534 -100.989755 31 -199.685226 -132.028534 32 899.927953 -199.685226 33 120.101830 899.927953 34 -407.094890 120.101830 35 -235.950580 -407.094890 36 -42.883134 -235.950580 37 270.207640 -42.883134 38 -306.896602 270.207640 39 -394.719154 -306.896602 40 210.531392 -394.719154 41 -376.578232 210.531392 42 134.720636 -376.578232 43 -396.881622 134.720636 44 634.185490 -396.881622 45 120.454903 634.185490 46 -425.269818 120.454903 47 -135.555467 -425.269818 48 -153.451000 -135.555467 49 454.612642 -153.451000 50 25.583989 454.612642 51 -449.565308 25.583989 52 -98.748874 -449.565308 53 -307.426524 -98.748874 54 48.247205 -307.426524 55 -342.933911 48.247205 56 1090.072360 -342.933911 57 -215.124833 1090.072360 58 -280.217814 -215.124833 59 61.095224 -280.217814 60 -205.942283 61.095224 61 553.005495 -205.942283 62 52.810237 553.005495 63 -738.917300 52.810237 64 -129.483062 -738.917300 65 -546.056604 -129.483062 66 -443.546407 -546.056604 67 -34.125252 -443.546407 68 384.815310 -34.125252 69 -575.098605 384.815310 70 34.611249 -575.098605 71 -857.996780 34.611249 72 350.792117 -857.996780 73 298.694651 350.792117 74 -93.596020 298.694651 75 84.949271 -93.596020 76 -252.460865 84.949271 77 93.296650 -252.460865 78 94.082486 93.296650 79 489.514673 94.082486 80 1753.181194 489.514673 81 556.677179 1753.181194 82 512.874524 556.677179 83 -145.562464 512.874524 84 672.573328 -145.562464 85 628.080745 672.573328 86 -485.375012 628.080745 87 -293.371876 -485.375012 88 -205.509954 -293.371876 89 -406.158500 -205.509954 90 -746.884677 -406.158500 91 NA -746.884677 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 752.149125 -287.823881 [2,] -313.658872 752.149125 [3,] -322.009839 -313.658872 [4,] -99.597157 -322.009839 [5,] -37.397836 -99.597157 [6,] 202.947420 -37.397836 [7,] -124.091613 202.947420 [8,] 1304.542653 -124.091613 [9,] 5.063508 1304.542653 [10,] 57.952446 5.063508 [11,] -11.430435 57.952446 [12,] -14.371443 -11.430435 [13,] 1007.339528 -14.371443 [14,] -557.649129 1007.339528 [15,] -203.374953 -557.649129 [16,] 71.931017 -203.374953 [17,] -415.671291 71.931017 [18,] -102.490933 -415.671291 [19,] -490.608173 -102.490933 [20,] 1177.455026 -490.608173 [21,] -431.882121 1177.455026 [22,] 228.700604 -431.882121 [23,] -562.816949 228.700604 [24,] -74.572825 -562.816949 [25,] 702.575541 -74.572825 [26,] -512.170681 702.575541 [27,] -397.928734 -512.170681 [28,] -18.723437 -397.928734 [29,] -100.989755 -18.723437 [30,] -132.028534 -100.989755 [31,] -199.685226 -132.028534 [32,] 899.927953 -199.685226 [33,] 120.101830 899.927953 [34,] -407.094890 120.101830 [35,] -235.950580 -407.094890 [36,] -42.883134 -235.950580 [37,] 270.207640 -42.883134 [38,] -306.896602 270.207640 [39,] -394.719154 -306.896602 [40,] 210.531392 -394.719154 [41,] -376.578232 210.531392 [42,] 134.720636 -376.578232 [43,] -396.881622 134.720636 [44,] 634.185490 -396.881622 [45,] 120.454903 634.185490 [46,] -425.269818 120.454903 [47,] -135.555467 -425.269818 [48,] -153.451000 -135.555467 [49,] 454.612642 -153.451000 [50,] 25.583989 454.612642 [51,] -449.565308 25.583989 [52,] -98.748874 -449.565308 [53,] -307.426524 -98.748874 [54,] 48.247205 -307.426524 [55,] -342.933911 48.247205 [56,] 1090.072360 -342.933911 [57,] -215.124833 1090.072360 [58,] -280.217814 -215.124833 [59,] 61.095224 -280.217814 [60,] -205.942283 61.095224 [61,] 553.005495 -205.942283 [62,] 52.810237 553.005495 [63,] -738.917300 52.810237 [64,] -129.483062 -738.917300 [65,] -546.056604 -129.483062 [66,] -443.546407 -546.056604 [67,] -34.125252 -443.546407 [68,] 384.815310 -34.125252 [69,] -575.098605 384.815310 [70,] 34.611249 -575.098605 [71,] -857.996780 34.611249 [72,] 350.792117 -857.996780 [73,] 298.694651 350.792117 [74,] -93.596020 298.694651 [75,] 84.949271 -93.596020 [76,] -252.460865 84.949271 [77,] 93.296650 -252.460865 [78,] 94.082486 93.296650 [79,] 489.514673 94.082486 [80,] 1753.181194 489.514673 [81,] 556.677179 1753.181194 [82,] 512.874524 556.677179 [83,] -145.562464 512.874524 [84,] 672.573328 -145.562464 [85,] 628.080745 672.573328 [86,] -485.375012 628.080745 [87,] -293.371876 -485.375012 [88,] -205.509954 -293.371876 [89,] -406.158500 -205.509954 [90,] -746.884677 -406.158500 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 752.149125 -287.823881 2 -313.658872 752.149125 3 -322.009839 -313.658872 4 -99.597157 -322.009839 5 -37.397836 -99.597157 6 202.947420 -37.397836 7 -124.091613 202.947420 8 1304.542653 -124.091613 9 5.063508 1304.542653 10 57.952446 5.063508 11 -11.430435 57.952446 12 -14.371443 -11.430435 13 1007.339528 -14.371443 14 -557.649129 1007.339528 15 -203.374953 -557.649129 16 71.931017 -203.374953 17 -415.671291 71.931017 18 -102.490933 -415.671291 19 -490.608173 -102.490933 20 1177.455026 -490.608173 21 -431.882121 1177.455026 22 228.700604 -431.882121 23 -562.816949 228.700604 24 -74.572825 -562.816949 25 702.575541 -74.572825 26 -512.170681 702.575541 27 -397.928734 -512.170681 28 -18.723437 -397.928734 29 -100.989755 -18.723437 30 -132.028534 -100.989755 31 -199.685226 -132.028534 32 899.927953 -199.685226 33 120.101830 899.927953 34 -407.094890 120.101830 35 -235.950580 -407.094890 36 -42.883134 -235.950580 37 270.207640 -42.883134 38 -306.896602 270.207640 39 -394.719154 -306.896602 40 210.531392 -394.719154 41 -376.578232 210.531392 42 134.720636 -376.578232 43 -396.881622 134.720636 44 634.185490 -396.881622 45 120.454903 634.185490 46 -425.269818 120.454903 47 -135.555467 -425.269818 48 -153.451000 -135.555467 49 454.612642 -153.451000 50 25.583989 454.612642 51 -449.565308 25.583989 52 -98.748874 -449.565308 53 -307.426524 -98.748874 54 48.247205 -307.426524 55 -342.933911 48.247205 56 1090.072360 -342.933911 57 -215.124833 1090.072360 58 -280.217814 -215.124833 59 61.095224 -280.217814 60 -205.942283 61.095224 61 553.005495 -205.942283 62 52.810237 553.005495 63 -738.917300 52.810237 64 -129.483062 -738.917300 65 -546.056604 -129.483062 66 -443.546407 -546.056604 67 -34.125252 -443.546407 68 384.815310 -34.125252 69 -575.098605 384.815310 70 34.611249 -575.098605 71 -857.996780 34.611249 72 350.792117 -857.996780 73 298.694651 350.792117 74 -93.596020 298.694651 75 84.949271 -93.596020 76 -252.460865 84.949271 77 93.296650 -252.460865 78 94.082486 93.296650 79 489.514673 94.082486 80 1753.181194 489.514673 81 556.677179 1753.181194 82 512.874524 556.677179 83 -145.562464 512.874524 84 672.573328 -145.562464 85 628.080745 672.573328 86 -485.375012 628.080745 87 -293.371876 -485.375012 88 -205.509954 -293.371876 89 -406.158500 -205.509954 90 -746.884677 -406.158500 > 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/7wumi1260038780.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8pmyj1260038780.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9xgdl1260038780.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10sedt1260038780.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11wgoi1260038780.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/12r3o01260038780.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/13unvv1260038780.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/141hri1260038780.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/15w0m01260038780.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/166b591260038780.tab") + } > > system("convert tmp/1e8i61260038780.ps tmp/1e8i61260038780.png") > system("convert tmp/2mnz91260038780.ps tmp/2mnz91260038780.png") > system("convert tmp/3aa1l1260038780.ps tmp/3aa1l1260038780.png") > system("convert tmp/4tz4y1260038780.ps tmp/4tz4y1260038780.png") > system("convert tmp/5hgzj1260038780.ps tmp/5hgzj1260038780.png") > system("convert tmp/6373u1260038780.ps tmp/6373u1260038780.png") > system("convert tmp/7wumi1260038780.ps tmp/7wumi1260038780.png") > system("convert tmp/8pmyj1260038780.ps tmp/8pmyj1260038780.png") > system("convert tmp/9xgdl1260038780.ps tmp/9xgdl1260038780.png") > system("convert tmp/10sedt1260038780.ps tmp/10sedt1260038780.png") > > > proc.time() user system elapsed 2.882 1.586 3.360