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Type 'q()' to quit R. > x <- array(list(6340.5 + ,0 + ,7901.5 + ,0 + ,8191.1 + ,0 + ,7181.7 + ,0 + ,7594.4 + ,0 + ,7384.7 + ,0 + ,7876.7 + ,0 + ,8463.4 + ,0 + ,8317.2 + ,0 + ,7778.7 + ,0 + ,8532.8 + ,0 + ,7272.2 + ,0 + ,6680.1 + ,0 + ,8427.6 + ,0 + ,8752.8 + ,0 + ,7952.7 + ,0 + ,8694.3 + ,0 + ,7787 + ,0 + ,8474.2 + ,0 + ,9154.7 + ,0 + ,8557.2 + ,0 + ,7951.1 + ,0 + ,9156.7 + ,0 + ,7865.7 + ,0 + ,7337.4 + ,0 + ,9131.7 + ,0 + ,8814.6 + ,0 + ,8598.8 + ,0 + ,8439.6 + ,0 + ,7451.8 + ,0 + ,8016.2 + ,0 + ,9544.1 + ,0 + ,8270.7 + ,0 + ,8102.2 + ,0 + ,9369 + ,0 + ,7657.7 + ,0 + ,7816.6 + ,0 + ,9391.3 + ,0 + ,9445.4 + ,0 + ,9533.1 + ,0 + ,10068.7 + ,0 + ,8955.5 + ,0 + ,10423.9 + ,0 + ,11617.2 + ,0 + ,9391.1 + ,0 + ,10872 + ,0 + ,10230.4 + ,0 + ,9221 + ,0 + ,9428.6 + ,0 + ,10934.5 + ,0 + ,10986 + ,0 + ,11724.6 + ,0 + ,11180.9 + ,0 + ,11163.2 + ,0 + ,11240.9 + ,0 + ,12107.1 + ,0 + ,10762.3 + ,0 + ,11340.4 + ,0 + ,11266.8 + ,0 + ,9542.7 + ,0 + ,9227.7 + ,0 + ,10571.9 + ,0 + ,10774.4 + ,0 + ,10392.8 + ,0 + ,9920.2 + ,0 + ,9884.9 + ,1 + ,10174.5 + ,1 + ,11395.4 + ,1 + ,10760.2 + ,1 + ,10570.1 + ,1 + ,10536 + ,1 + ,9902.6 + ,1 + ,8889 + ,1 + ,10837.3 + ,1 + ,11624.1 + ,1 + ,10509 + ,1 + ,10984.9 + ,1 + ,10649.1 + ,1 + ,10855.7 + ,1 + ,11677.4 + ,1 + ,10760.2 + ,1 + ,10046.2 + ,1 + ,10772.8 + ,1 + ,9987.7 + ,1 + ,8638.7 + ,1 + ,11063.7 + ,1 + ,11855.7 + ,1 + ,10684.5 + ,1 + ,11337.4 + ,1 + ,10478 + ,1 + ,11123.9 + ,1 + ,12909.3 + ,1 + ,11339.9 + ,1 + ,10462.2 + ,1 + ,12733.5 + ,1 + ,10519.2 + ,1 + ,10414.9 + ,1 + ,12476.8 + ,1 + ,12384.6 + ,1 + ,12266.7 + ,1 + ,12919.9 + ,1 + ,11497.3 + ,1 + ,12142 + ,1 + ,13919.4 + ,1 + ,12656.8 + ,1 + ,12034.1 + ,1 + ,13199.7 + ,1 + ,10881.3 + ,1 + ,11301.2 + ,1 + ,13643.9 + ,1 + ,12517 + ,1 + ,13981.1 + ,1 + ,14275.7 + ,1 + ,13435 + ,1 + ,13565.7 + ,1 + ,16216.3 + ,1 + ,12970 + ,1 + ,14079.9 + ,1 + ,14235 + ,1 + ,12213.4 + ,1 + ,12581 + ,1) + ,dim=c(2 + ,121) + ,dimnames=list(c('y' + ,'x') + ,1:121)) > y <- array(NA,dim=c(2,121),dimnames=list(c('y','x'),1:121)) > 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 y x 1 6340.5 0 2 7901.5 0 3 8191.1 0 4 7181.7 0 5 7594.4 0 6 7384.7 0 7 7876.7 0 8 8463.4 0 9 8317.2 0 10 7778.7 0 11 8532.8 0 12 7272.2 0 13 6680.1 0 14 8427.6 0 15 8752.8 0 16 7952.7 0 17 8694.3 0 18 7787.0 0 19 8474.2 0 20 9154.7 0 21 8557.2 0 22 7951.1 0 23 9156.7 0 24 7865.7 0 25 7337.4 0 26 9131.7 0 27 8814.6 0 28 8598.8 0 29 8439.6 0 30 7451.8 0 31 8016.2 0 32 9544.1 0 33 8270.7 0 34 8102.2 0 35 9369.0 0 36 7657.7 0 37 7816.6 0 38 9391.3 0 39 9445.4 0 40 9533.1 0 41 10068.7 0 42 8955.5 0 43 10423.9 0 44 11617.2 0 45 9391.1 0 46 10872.0 0 47 10230.4 0 48 9221.0 0 49 9428.6 0 50 10934.5 0 51 10986.0 0 52 11724.6 0 53 11180.9 0 54 11163.2 0 55 11240.9 0 56 12107.1 0 57 10762.3 0 58 11340.4 0 59 11266.8 0 60 9542.7 0 61 9227.7 0 62 10571.9 0 63 10774.4 0 64 10392.8 0 65 9920.2 0 66 9884.9 1 67 10174.5 1 68 11395.4 1 69 10760.2 1 70 10570.1 1 71 10536.0 1 72 9902.6 1 73 8889.0 1 74 10837.3 1 75 11624.1 1 76 10509.0 1 77 10984.9 1 78 10649.1 1 79 10855.7 1 80 11677.4 1 81 10760.2 1 82 10046.2 1 83 10772.8 1 84 9987.7 1 85 8638.7 1 86 11063.7 1 87 11855.7 1 88 10684.5 1 89 11337.4 1 90 10478.0 1 91 11123.9 1 92 12909.3 1 93 11339.9 1 94 10462.2 1 95 12733.5 1 96 10519.2 1 97 10414.9 1 98 12476.8 1 99 12384.6 1 100 12266.7 1 101 12919.9 1 102 11497.3 1 103 12142.0 1 104 13919.4 1 105 12656.8 1 106 12034.1 1 107 13199.7 1 108 10881.3 1 109 11301.2 1 110 13643.9 1 111 12517.0 1 112 13981.1 1 113 14275.7 1 114 13435.0 1 115 13565.7 1 116 16216.3 1 117 12970.0 1 118 14079.9 1 119 14235.0 1 120 12213.4 1 121 12581.0 1 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) x 9116 2594 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -3071.5 -1140.1 -301.6 1023.3 4506.1 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 9116.2 178.2 51.146 <2e-16 *** x 2594.0 262.0 9.901 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 1437 on 119 degrees of freedom Multiple R-squared: 0.4517, Adjusted R-squared: 0.4471 F-statistic: 98.02 on 1 and 119 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,] 2.074475e-01 0.4148949659 0.7925525 [2,] 9.772643e-02 0.1954528578 0.9022736 [3,] 4.942326e-02 0.0988465187 0.9505767 [4,] 4.386486e-02 0.0877297134 0.9561351 [5,] 2.845907e-02 0.0569181334 0.9715409 [6,] 1.305744e-02 0.0261148702 0.9869426 [7,] 1.014340e-02 0.0202867948 0.9898566 [8,] 5.964757e-03 0.0119295137 0.9940352 [9,] 7.587662e-03 0.0151753231 0.9924123 [10,] 5.656854e-03 0.0113137081 0.9943431 [11,] 5.833734e-03 0.0116674688 0.9941663 [12,] 3.068063e-03 0.0061361255 0.9969319 [13,] 2.666371e-03 0.0053327423 0.9973336 [14,] 1.407875e-03 0.0028157506 0.9985921 [15,] 9.342977e-04 0.0018685954 0.9990657 [16,] 1.425341e-03 0.0028506815 0.9985747 [17,] 9.436937e-04 0.0018873874 0.9990563 [18,] 5.145905e-04 0.0010291810 0.9994854 [19,] 6.575249e-04 0.0013150497 0.9993425 [20,] 3.820609e-04 0.0007641218 0.9996179 [21,] 3.333166e-04 0.0006666333 0.9996667 [22,] 3.980953e-04 0.0007961907 0.9996019 [23,] 3.115050e-04 0.0006230100 0.9996885 [24,] 2.053627e-04 0.0004107254 0.9997946 [25,] 1.256071e-04 0.0002512143 0.9998744 [26,] 1.168914e-04 0.0002337828 0.9998831 [27,] 7.473411e-05 0.0001494682 0.9999253 [28,] 1.529600e-04 0.0003059200 0.9998470 [29,] 9.957697e-05 0.0001991539 0.9999004 [30,] 6.813038e-05 0.0001362608 0.9999319 [31,] 9.571257e-05 0.0001914251 0.9999043 [32,] 9.511670e-05 0.0001902334 0.9999049 [33,] 8.809622e-05 0.0001761924 0.9999119 [34,] 1.274872e-04 0.0002549744 0.9998725 [35,] 1.808611e-04 0.0003617221 0.9998191 [36,] 2.613424e-04 0.0005226849 0.9997387 [37,] 6.588389e-04 0.0013176778 0.9993412 [38,] 5.791055e-04 0.0011582110 0.9994209 [39,] 1.786703e-03 0.0035734068 0.9982133 [40,] 1.856695e-02 0.0371339096 0.9814330 [41,] 1.725769e-02 0.0345153784 0.9827423 [42,] 3.465431e-02 0.0693086253 0.9653457 [43,] 4.054070e-02 0.0810814072 0.9594593 [44,] 3.646870e-02 0.0729373982 0.9635313 [45,] 3.365110e-02 0.0673021940 0.9663489 [46,] 5.362774e-02 0.1072554897 0.9463723 [47,] 7.822082e-02 0.1564416443 0.9217792 [48,] 1.512805e-01 0.3025610031 0.8487195 [49,] 1.927489e-01 0.3854978832 0.8072511 [50,] 2.308022e-01 0.4616044491 0.7691978 [51,] 2.713467e-01 0.5426934299 0.7286533 [52,] 3.993092e-01 0.7986183724 0.6006908 [53,] 3.979188e-01 0.7958375494 0.6020812 [54,] 4.370044e-01 0.8740088632 0.5629956 [55,] 4.681687e-01 0.9363373849 0.5318313 [56,] 4.237086e-01 0.8474171812 0.5762914 [57,] 3.866699e-01 0.7733398535 0.6133301 [58,] 3.659370e-01 0.7318740894 0.6340630 [59,] 3.542403e-01 0.7084805095 0.6457597 [60,] 3.265513e-01 0.6531025652 0.6734487 [61,] 2.874006e-01 0.5748011612 0.7125994 [62,] 2.789486e-01 0.5578971822 0.7210514 [63,] 2.624574e-01 0.5249147873 0.7375426 [64,] 2.341532e-01 0.4683064218 0.7658468 [65,] 2.057593e-01 0.4115185115 0.7942407 [66,] 1.833067e-01 0.3666133555 0.8166933 [67,] 1.637971e-01 0.3275941419 0.8362029 [68,] 1.664558e-01 0.3329115333 0.8335442 [69,] 2.411404e-01 0.4822807124 0.7588596 [70,] 2.177372e-01 0.4354744779 0.7822628 [71,] 1.933899e-01 0.3867798499 0.8066101 [72,] 1.802538e-01 0.3605075443 0.8197462 [73,] 1.586562e-01 0.3173123734 0.8413438 [74,] 1.453299e-01 0.2906598765 0.8546701 [75,] 1.294607e-01 0.2589214890 0.8705393 [76,] 1.104005e-01 0.2208010132 0.8895995 [77,] 9.943344e-02 0.1988668825 0.9005666 [78,] 1.107256e-01 0.2214511195 0.8892744 [79,] 1.020798e-01 0.2041595082 0.8979202 [80,] 1.223330e-01 0.2446660953 0.8776670 [81,] 3.056157e-01 0.6112313615 0.6943843 [82,] 2.941914e-01 0.5883827391 0.7058086 [83,] 2.668768e-01 0.5337536926 0.7331232 [84,] 2.804882e-01 0.5609764851 0.7195118 [85,] 2.639793e-01 0.5279585873 0.7360207 [86,] 3.065312e-01 0.6130624393 0.6934688 [87,] 3.080335e-01 0.6160670387 0.6919665 [88,] 2.974535e-01 0.5949070953 0.7025465 [89,] 2.880253e-01 0.5760506388 0.7119747 [90,] 3.639369e-01 0.7278737571 0.6360631 [91,] 3.360859e-01 0.6721717243 0.6639141 [92,] 4.310943e-01 0.8621885649 0.5689057 [93,] 5.830779e-01 0.8338441568 0.4169221 [94,] 5.465235e-01 0.9069529555 0.4534765 [95,] 5.092740e-01 0.9814520689 0.4907260 [96,] 4.746423e-01 0.9492845163 0.5253577 [97,] 4.313424e-01 0.8626848684 0.5686576 [98,] 4.578511e-01 0.9157021112 0.5421489 [99,] 4.334886e-01 0.8669771557 0.5665114 [100,] 4.292910e-01 0.8585819934 0.5707090 [101,] 3.762464e-01 0.7524928116 0.6237536 [102,] 3.577925e-01 0.7155850118 0.6422075 [103,] 3.020925e-01 0.6041849571 0.6979075 [104,] 4.802231e-01 0.9604461713 0.5197769 [105,] 6.601277e-01 0.6797445082 0.3398723 [106,] 5.881090e-01 0.8237820793 0.4118910 [107,] 5.754182e-01 0.8491635269 0.4245818 [108,] 4.941352e-01 0.9882704261 0.5058648 [109,] 4.255268e-01 0.8510536221 0.5744732 [110,] 3.204492e-01 0.6408983727 0.6795508 [111,] 2.187206e-01 0.4374412642 0.7812794 [112,] 6.575537e-01 0.6848925795 0.3424463 > postscript(file="/var/www/html/rcomp/tmp/1fmf71229180489.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2ty1t1229180489.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/3ydb71229180489.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4l1iw1229180489.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5hk4r1229180489.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 = 121 Frequency = 1 1 2 3 4 5 6 -2775.71538 -1214.71538 -925.11538 -1934.51538 -1521.81538 -1731.51538 7 8 9 10 11 12 -1239.51538 -652.81538 -799.01538 -1337.51538 -583.41538 -1844.01538 13 14 15 16 17 18 -2436.11538 -688.61538 -363.41538 -1163.51538 -421.91538 -1329.21538 19 20 21 22 23 24 -642.01538 38.48462 -559.01538 -1165.11538 40.48462 -1250.51538 25 26 27 28 29 30 -1778.81538 15.48462 -301.61538 -517.41538 -676.61538 -1664.41538 31 32 33 34 35 36 -1100.01538 427.88462 -845.51538 -1014.01538 252.78462 -1458.51538 37 38 39 40 41 42 -1299.61538 275.08462 329.18462 416.88462 952.48462 -160.71538 43 44 45 46 47 48 1307.68462 2500.98462 274.88462 1755.78462 1114.18462 104.78462 49 50 51 52 53 54 312.38462 1818.28462 1869.78462 2608.38462 2064.68462 2046.98462 55 56 57 58 59 60 2124.68462 2990.88462 1646.08462 2224.18462 2150.58462 426.48462 61 62 63 64 65 66 111.48462 1455.68462 1658.18462 1276.58462 803.98462 -1825.31071 67 68 69 70 71 72 -1535.71071 -314.81071 -950.01071 -1140.11071 -1174.21071 -1807.61071 73 74 75 76 77 78 -2821.21071 -872.91071 -86.11071 -1201.21071 -725.31071 -1061.11071 79 80 81 82 83 84 -854.51071 -32.81071 -950.01071 -1664.01071 -937.41071 -1722.51071 85 86 87 88 89 90 -3071.51071 -646.51071 145.48929 -1025.71071 -372.81071 -1232.21071 91 92 93 94 95 96 -586.31071 1199.08929 -370.31071 -1248.01071 1023.28929 -1191.01071 97 98 99 100 101 102 -1295.31071 766.58929 674.38929 556.48929 1209.68929 -212.91071 103 104 105 106 107 108 431.78929 2209.18929 946.58929 323.88929 1489.48929 -828.91071 109 110 111 112 113 114 -409.01071 1933.68929 806.78929 2270.88929 2565.48929 1724.78929 115 116 117 118 119 120 1855.48929 4506.08929 1259.78929 2369.68929 2524.78929 503.18929 121 870.78929 > postscript(file="/var/www/html/rcomp/tmp/6q0fy1229180489.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 = 121 Frequency = 1 lag(myerror, k = 1) myerror 0 -2775.71538 NA 1 -1214.71538 -2775.71538 2 -925.11538 -1214.71538 3 -1934.51538 -925.11538 4 -1521.81538 -1934.51538 5 -1731.51538 -1521.81538 6 -1239.51538 -1731.51538 7 -652.81538 -1239.51538 8 -799.01538 -652.81538 9 -1337.51538 -799.01538 10 -583.41538 -1337.51538 11 -1844.01538 -583.41538 12 -2436.11538 -1844.01538 13 -688.61538 -2436.11538 14 -363.41538 -688.61538 15 -1163.51538 -363.41538 16 -421.91538 -1163.51538 17 -1329.21538 -421.91538 18 -642.01538 -1329.21538 19 38.48462 -642.01538 20 -559.01538 38.48462 21 -1165.11538 -559.01538 22 40.48462 -1165.11538 23 -1250.51538 40.48462 24 -1778.81538 -1250.51538 25 15.48462 -1778.81538 26 -301.61538 15.48462 27 -517.41538 -301.61538 28 -676.61538 -517.41538 29 -1664.41538 -676.61538 30 -1100.01538 -1664.41538 31 427.88462 -1100.01538 32 -845.51538 427.88462 33 -1014.01538 -845.51538 34 252.78462 -1014.01538 35 -1458.51538 252.78462 36 -1299.61538 -1458.51538 37 275.08462 -1299.61538 38 329.18462 275.08462 39 416.88462 329.18462 40 952.48462 416.88462 41 -160.71538 952.48462 42 1307.68462 -160.71538 43 2500.98462 1307.68462 44 274.88462 2500.98462 45 1755.78462 274.88462 46 1114.18462 1755.78462 47 104.78462 1114.18462 48 312.38462 104.78462 49 1818.28462 312.38462 50 1869.78462 1818.28462 51 2608.38462 1869.78462 52 2064.68462 2608.38462 53 2046.98462 2064.68462 54 2124.68462 2046.98462 55 2990.88462 2124.68462 56 1646.08462 2990.88462 57 2224.18462 1646.08462 58 2150.58462 2224.18462 59 426.48462 2150.58462 60 111.48462 426.48462 61 1455.68462 111.48462 62 1658.18462 1455.68462 63 1276.58462 1658.18462 64 803.98462 1276.58462 65 -1825.31071 803.98462 66 -1535.71071 -1825.31071 67 -314.81071 -1535.71071 68 -950.01071 -314.81071 69 -1140.11071 -950.01071 70 -1174.21071 -1140.11071 71 -1807.61071 -1174.21071 72 -2821.21071 -1807.61071 73 -872.91071 -2821.21071 74 -86.11071 -872.91071 75 -1201.21071 -86.11071 76 -725.31071 -1201.21071 77 -1061.11071 -725.31071 78 -854.51071 -1061.11071 79 -32.81071 -854.51071 80 -950.01071 -32.81071 81 -1664.01071 -950.01071 82 -937.41071 -1664.01071 83 -1722.51071 -937.41071 84 -3071.51071 -1722.51071 85 -646.51071 -3071.51071 86 145.48929 -646.51071 87 -1025.71071 145.48929 88 -372.81071 -1025.71071 89 -1232.21071 -372.81071 90 -586.31071 -1232.21071 91 1199.08929 -586.31071 92 -370.31071 1199.08929 93 -1248.01071 -370.31071 94 1023.28929 -1248.01071 95 -1191.01071 1023.28929 96 -1295.31071 -1191.01071 97 766.58929 -1295.31071 98 674.38929 766.58929 99 556.48929 674.38929 100 1209.68929 556.48929 101 -212.91071 1209.68929 102 431.78929 -212.91071 103 2209.18929 431.78929 104 946.58929 2209.18929 105 323.88929 946.58929 106 1489.48929 323.88929 107 -828.91071 1489.48929 108 -409.01071 -828.91071 109 1933.68929 -409.01071 110 806.78929 1933.68929 111 2270.88929 806.78929 112 2565.48929 2270.88929 113 1724.78929 2565.48929 114 1855.48929 1724.78929 115 4506.08929 1855.48929 116 1259.78929 4506.08929 117 2369.68929 1259.78929 118 2524.78929 2369.68929 119 503.18929 2524.78929 120 870.78929 503.18929 121 NA 870.78929 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -1214.71538 -2775.71538 [2,] -925.11538 -1214.71538 [3,] -1934.51538 -925.11538 [4,] -1521.81538 -1934.51538 [5,] -1731.51538 -1521.81538 [6,] -1239.51538 -1731.51538 [7,] -652.81538 -1239.51538 [8,] -799.01538 -652.81538 [9,] -1337.51538 -799.01538 [10,] -583.41538 -1337.51538 [11,] -1844.01538 -583.41538 [12,] -2436.11538 -1844.01538 [13,] -688.61538 -2436.11538 [14,] -363.41538 -688.61538 [15,] -1163.51538 -363.41538 [16,] -421.91538 -1163.51538 [17,] -1329.21538 -421.91538 [18,] -642.01538 -1329.21538 [19,] 38.48462 -642.01538 [20,] -559.01538 38.48462 [21,] -1165.11538 -559.01538 [22,] 40.48462 -1165.11538 [23,] -1250.51538 40.48462 [24,] -1778.81538 -1250.51538 [25,] 15.48462 -1778.81538 [26,] -301.61538 15.48462 [27,] -517.41538 -301.61538 [28,] -676.61538 -517.41538 [29,] -1664.41538 -676.61538 [30,] -1100.01538 -1664.41538 [31,] 427.88462 -1100.01538 [32,] -845.51538 427.88462 [33,] -1014.01538 -845.51538 [34,] 252.78462 -1014.01538 [35,] -1458.51538 252.78462 [36,] -1299.61538 -1458.51538 [37,] 275.08462 -1299.61538 [38,] 329.18462 275.08462 [39,] 416.88462 329.18462 [40,] 952.48462 416.88462 [41,] -160.71538 952.48462 [42,] 1307.68462 -160.71538 [43,] 2500.98462 1307.68462 [44,] 274.88462 2500.98462 [45,] 1755.78462 274.88462 [46,] 1114.18462 1755.78462 [47,] 104.78462 1114.18462 [48,] 312.38462 104.78462 [49,] 1818.28462 312.38462 [50,] 1869.78462 1818.28462 [51,] 2608.38462 1869.78462 [52,] 2064.68462 2608.38462 [53,] 2046.98462 2064.68462 [54,] 2124.68462 2046.98462 [55,] 2990.88462 2124.68462 [56,] 1646.08462 2990.88462 [57,] 2224.18462 1646.08462 [58,] 2150.58462 2224.18462 [59,] 426.48462 2150.58462 [60,] 111.48462 426.48462 [61,] 1455.68462 111.48462 [62,] 1658.18462 1455.68462 [63,] 1276.58462 1658.18462 [64,] 803.98462 1276.58462 [65,] -1825.31071 803.98462 [66,] -1535.71071 -1825.31071 [67,] -314.81071 -1535.71071 [68,] -950.01071 -314.81071 [69,] -1140.11071 -950.01071 [70,] -1174.21071 -1140.11071 [71,] -1807.61071 -1174.21071 [72,] -2821.21071 -1807.61071 [73,] -872.91071 -2821.21071 [74,] -86.11071 -872.91071 [75,] -1201.21071 -86.11071 [76,] -725.31071 -1201.21071 [77,] -1061.11071 -725.31071 [78,] -854.51071 -1061.11071 [79,] -32.81071 -854.51071 [80,] -950.01071 -32.81071 [81,] -1664.01071 -950.01071 [82,] -937.41071 -1664.01071 [83,] -1722.51071 -937.41071 [84,] -3071.51071 -1722.51071 [85,] -646.51071 -3071.51071 [86,] 145.48929 -646.51071 [87,] -1025.71071 145.48929 [88,] -372.81071 -1025.71071 [89,] -1232.21071 -372.81071 [90,] -586.31071 -1232.21071 [91,] 1199.08929 -586.31071 [92,] -370.31071 1199.08929 [93,] -1248.01071 -370.31071 [94,] 1023.28929 -1248.01071 [95,] -1191.01071 1023.28929 [96,] -1295.31071 -1191.01071 [97,] 766.58929 -1295.31071 [98,] 674.38929 766.58929 [99,] 556.48929 674.38929 [100,] 1209.68929 556.48929 [101,] -212.91071 1209.68929 [102,] 431.78929 -212.91071 [103,] 2209.18929 431.78929 [104,] 946.58929 2209.18929 [105,] 323.88929 946.58929 [106,] 1489.48929 323.88929 [107,] -828.91071 1489.48929 [108,] -409.01071 -828.91071 [109,] 1933.68929 -409.01071 [110,] 806.78929 1933.68929 [111,] 2270.88929 806.78929 [112,] 2565.48929 2270.88929 [113,] 1724.78929 2565.48929 [114,] 1855.48929 1724.78929 [115,] 4506.08929 1855.48929 [116,] 1259.78929 4506.08929 [117,] 2369.68929 1259.78929 [118,] 2524.78929 2369.68929 [119,] 503.18929 2524.78929 [120,] 870.78929 503.18929 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -1214.71538 -2775.71538 2 -925.11538 -1214.71538 3 -1934.51538 -925.11538 4 -1521.81538 -1934.51538 5 -1731.51538 -1521.81538 6 -1239.51538 -1731.51538 7 -652.81538 -1239.51538 8 -799.01538 -652.81538 9 -1337.51538 -799.01538 10 -583.41538 -1337.51538 11 -1844.01538 -583.41538 12 -2436.11538 -1844.01538 13 -688.61538 -2436.11538 14 -363.41538 -688.61538 15 -1163.51538 -363.41538 16 -421.91538 -1163.51538 17 -1329.21538 -421.91538 18 -642.01538 -1329.21538 19 38.48462 -642.01538 20 -559.01538 38.48462 21 -1165.11538 -559.01538 22 40.48462 -1165.11538 23 -1250.51538 40.48462 24 -1778.81538 -1250.51538 25 15.48462 -1778.81538 26 -301.61538 15.48462 27 -517.41538 -301.61538 28 -676.61538 -517.41538 29 -1664.41538 -676.61538 30 -1100.01538 -1664.41538 31 427.88462 -1100.01538 32 -845.51538 427.88462 33 -1014.01538 -845.51538 34 252.78462 -1014.01538 35 -1458.51538 252.78462 36 -1299.61538 -1458.51538 37 275.08462 -1299.61538 38 329.18462 275.08462 39 416.88462 329.18462 40 952.48462 416.88462 41 -160.71538 952.48462 42 1307.68462 -160.71538 43 2500.98462 1307.68462 44 274.88462 2500.98462 45 1755.78462 274.88462 46 1114.18462 1755.78462 47 104.78462 1114.18462 48 312.38462 104.78462 49 1818.28462 312.38462 50 1869.78462 1818.28462 51 2608.38462 1869.78462 52 2064.68462 2608.38462 53 2046.98462 2064.68462 54 2124.68462 2046.98462 55 2990.88462 2124.68462 56 1646.08462 2990.88462 57 2224.18462 1646.08462 58 2150.58462 2224.18462 59 426.48462 2150.58462 60 111.48462 426.48462 61 1455.68462 111.48462 62 1658.18462 1455.68462 63 1276.58462 1658.18462 64 803.98462 1276.58462 65 -1825.31071 803.98462 66 -1535.71071 -1825.31071 67 -314.81071 -1535.71071 68 -950.01071 -314.81071 69 -1140.11071 -950.01071 70 -1174.21071 -1140.11071 71 -1807.61071 -1174.21071 72 -2821.21071 -1807.61071 73 -872.91071 -2821.21071 74 -86.11071 -872.91071 75 -1201.21071 -86.11071 76 -725.31071 -1201.21071 77 -1061.11071 -725.31071 78 -854.51071 -1061.11071 79 -32.81071 -854.51071 80 -950.01071 -32.81071 81 -1664.01071 -950.01071 82 -937.41071 -1664.01071 83 -1722.51071 -937.41071 84 -3071.51071 -1722.51071 85 -646.51071 -3071.51071 86 145.48929 -646.51071 87 -1025.71071 145.48929 88 -372.81071 -1025.71071 89 -1232.21071 -372.81071 90 -586.31071 -1232.21071 91 1199.08929 -586.31071 92 -370.31071 1199.08929 93 -1248.01071 -370.31071 94 1023.28929 -1248.01071 95 -1191.01071 1023.28929 96 -1295.31071 -1191.01071 97 766.58929 -1295.31071 98 674.38929 766.58929 99 556.48929 674.38929 100 1209.68929 556.48929 101 -212.91071 1209.68929 102 431.78929 -212.91071 103 2209.18929 431.78929 104 946.58929 2209.18929 105 323.88929 946.58929 106 1489.48929 323.88929 107 -828.91071 1489.48929 108 -409.01071 -828.91071 109 1933.68929 -409.01071 110 806.78929 1933.68929 111 2270.88929 806.78929 112 2565.48929 2270.88929 113 1724.78929 2565.48929 114 1855.48929 1724.78929 115 4506.08929 1855.48929 116 1259.78929 4506.08929 117 2369.68929 1259.78929 118 2524.78929 2369.68929 119 503.18929 2524.78929 120 870.78929 503.18929 > 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/7u3xq1229180489.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8jnzh1229180489.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9i4f61229180489.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10h6p61229180489.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/118mul1229180490.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/12i6l51229180490.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/13x5xm1229180490.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/14czgy1229180490.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/15y2an1229180490.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/16vjzq1229180490.tab") + } > > system("convert tmp/1fmf71229180489.ps tmp/1fmf71229180489.png") > system("convert tmp/2ty1t1229180489.ps tmp/2ty1t1229180489.png") > system("convert tmp/3ydb71229180489.ps tmp/3ydb71229180489.png") > system("convert tmp/4l1iw1229180489.ps tmp/4l1iw1229180489.png") > system("convert tmp/5hk4r1229180489.ps tmp/5hk4r1229180489.png") > system("convert tmp/6q0fy1229180489.ps tmp/6q0fy1229180489.png") > system("convert tmp/7u3xq1229180489.ps tmp/7u3xq1229180489.png") > system("convert tmp/8jnzh1229180489.ps tmp/8jnzh1229180489.png") > system("convert tmp/9i4f61229180489.ps tmp/9i4f61229180489.png") > system("convert tmp/10h6p61229180489.ps tmp/10h6p61229180489.png") > > > proc.time() user system elapsed 3.200 1.683 3.690