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Type 'q()' to quit R. > x <- array(list(160646.8 + ,0 + ,160637.2 + ,0 + ,164997.4 + ,0 + ,167984.4 + ,0 + ,172568.7 + ,0 + ,178880 + ,0 + ,181932.9 + ,0 + ,187714.3 + ,0 + ,188076.3 + ,0 + ,189892.2 + ,0 + ,182166.5 + ,0 + ,196657.6 + ,0 + ,176794.5 + ,0 + ,178830.4 + ,0 + ,168934.5 + ,0 + ,167902.6 + ,0 + ,166530.3 + ,0 + ,169323.4 + ,0 + ,175184.6 + ,0 + ,172493.7 + ,0 + ,158829.4 + ,0 + ,156139.6 + ,0 + ,162112.3 + ,0 + ,186258.3 + ,0 + ,167201.2 + ,0 + ,165990.2 + ,0 + ,165731.8 + ,0 + ,168118.1 + ,0 + ,162460.8 + ,0 + ,151526.9 + ,0 + ,136480.9 + ,0 + ,135780.2 + ,0 + ,114973.3 + ,0 + ,121127.6 + ,0 + ,124920.1 + ,0 + ,122454.3 + ,0 + ,114088.9 + ,0 + ,106266.2 + ,0 + ,104412 + ,0 + ,117742.8 + ,0 + ,121798.2 + ,0 + ,122644.1 + ,0 + ,127011.6 + ,0 + ,129469.6 + ,0 + ,129579.3 + ,0 + ,135693.2 + ,0 + ,136320.4 + ,0 + ,137592.5 + ,0 + ,148244.4 + ,0 + ,154458 + ,0 + ,159692.2 + ,0 + ,163144.1 + ,0 + ,162107.5 + ,0 + ,165131.3 + ,0 + ,164231.2 + ,0 + ,170001.9 + ,0 + ,182144.8 + ,0 + ,188313.5 + ,0 + ,193955.3 + ,0 + ,200918.4 + ,0 + ,206409 + ,0 + ,214390.6 + ,0 + ,203845.4 + ,0 + ,206986.7 + ,0 + ,209341 + ,0 + ,214284 + ,0 + ,222753 + ,0 + ,224041 + ,0 + ,232062 + ,0 + ,229253 + ,0 + ,237632 + ,0 + ,244574 + ,0 + ,257227 + ,0 + ,264083 + ,0 + ,265331 + ,0 + ,269216 + ,0 + ,253965 + ,0 + ,254036 + ,0 + ,259733 + ,0 + ,266302 + ,0 + ,277784 + ,0 + ,282973 + ,0 + ,283398 + ,0 + ,300454 + ,0 + ,304528 + ,0 + ,298325 + ,0 + ,311393 + ,0 + ,316867 + ,0 + ,322725 + ,0 + ,317988 + ,0 + ,274957 + ,1 + ,267993 + ,1 + ,260728 + ,1 + ,286828 + ,1 + ,265985 + ,1 + ,263718 + ,1 + ,239891 + ,1 + ,241398 + ,1 + ,238924 + ,1 + ,246829 + ,1 + ,234725 + ,1 + ,199177 + ,1 + ,189131 + ,1 + ,198293 + ,1 + ,165763 + ,1 + ,124900 + ,1) + ,dim=c(2 + ,106) + ,dimnames=list(c('beurskapitalisatie' + ,'Wel(1)_geen(0)_financiële_crisis') + ,1:106)) > y <- array(NA,dim=c(2,106),dimnames=list(c('beurskapitalisatie','Wel(1)_geen(0)_financiële_crisis'),1:106)) > 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 = 'Include Monthly 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) > 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 beurskapitalisatie Wel(1)_geen(0)_financi\353le_crisis M1 M2 M3 M4 M5 M6 M7 1 160646.8 0 1 0 0 0 0 0 0 2 160637.2 0 0 1 0 0 0 0 0 3 164997.4 0 0 0 1 0 0 0 0 4 167984.4 0 0 0 0 1 0 0 0 5 172568.7 0 0 0 0 0 1 0 0 6 178880.0 0 0 0 0 0 0 1 0 7 181932.9 0 0 0 0 0 0 0 1 8 187714.3 0 0 0 0 0 0 0 0 9 188076.3 0 0 0 0 0 0 0 0 10 189892.2 0 0 0 0 0 0 0 0 11 182166.5 0 0 0 0 0 0 0 0 12 196657.6 0 0 0 0 0 0 0 0 13 176794.5 0 1 0 0 0 0 0 0 14 178830.4 0 0 1 0 0 0 0 0 15 168934.5 0 0 0 1 0 0 0 0 16 167902.6 0 0 0 0 1 0 0 0 17 166530.3 0 0 0 0 0 1 0 0 18 169323.4 0 0 0 0 0 0 1 0 19 175184.6 0 0 0 0 0 0 0 1 20 172493.7 0 0 0 0 0 0 0 0 21 158829.4 0 0 0 0 0 0 0 0 22 156139.6 0 0 0 0 0 0 0 0 23 162112.3 0 0 0 0 0 0 0 0 24 186258.3 0 0 0 0 0 0 0 0 25 167201.2 0 1 0 0 0 0 0 0 26 165990.2 0 0 1 0 0 0 0 0 27 165731.8 0 0 0 1 0 0 0 0 28 168118.1 0 0 0 0 1 0 0 0 29 162460.8 0 0 0 0 0 1 0 0 30 151526.9 0 0 0 0 0 0 1 0 31 136480.9 0 0 0 0 0 0 0 1 32 135780.2 0 0 0 0 0 0 0 0 33 114973.3 0 0 0 0 0 0 0 0 34 121127.6 0 0 0 0 0 0 0 0 35 124920.1 0 0 0 0 0 0 0 0 36 122454.3 0 0 0 0 0 0 0 0 37 114088.9 0 1 0 0 0 0 0 0 38 106266.2 0 0 1 0 0 0 0 0 39 104412.0 0 0 0 1 0 0 0 0 40 117742.8 0 0 0 0 1 0 0 0 41 121798.2 0 0 0 0 0 1 0 0 42 122644.1 0 0 0 0 0 0 1 0 43 127011.6 0 0 0 0 0 0 0 1 44 129469.6 0 0 0 0 0 0 0 0 45 129579.3 0 0 0 0 0 0 0 0 46 135693.2 0 0 0 0 0 0 0 0 47 136320.4 0 0 0 0 0 0 0 0 48 137592.5 0 0 0 0 0 0 0 0 49 148244.4 0 1 0 0 0 0 0 0 50 154458.0 0 0 1 0 0 0 0 0 51 159692.2 0 0 0 1 0 0 0 0 52 163144.1 0 0 0 0 1 0 0 0 53 162107.5 0 0 0 0 0 1 0 0 54 165131.3 0 0 0 0 0 0 1 0 55 164231.2 0 0 0 0 0 0 0 1 56 170001.9 0 0 0 0 0 0 0 0 57 182144.8 0 0 0 0 0 0 0 0 58 188313.5 0 0 0 0 0 0 0 0 59 193955.3 0 0 0 0 0 0 0 0 60 200918.4 0 0 0 0 0 0 0 0 61 206409.0 0 1 0 0 0 0 0 0 62 214390.6 0 0 1 0 0 0 0 0 63 203845.4 0 0 0 1 0 0 0 0 64 206986.7 0 0 0 0 1 0 0 0 65 209341.0 0 0 0 0 0 1 0 0 66 214284.0 0 0 0 0 0 0 1 0 67 222753.0 0 0 0 0 0 0 0 1 68 224041.0 0 0 0 0 0 0 0 0 69 232062.0 0 0 0 0 0 0 0 0 70 229253.0 0 0 0 0 0 0 0 0 71 237632.0 0 0 0 0 0 0 0 0 72 244574.0 0 0 0 0 0 0 0 0 73 257227.0 0 1 0 0 0 0 0 0 74 264083.0 0 0 1 0 0 0 0 0 75 265331.0 0 0 0 1 0 0 0 0 76 269216.0 0 0 0 0 1 0 0 0 77 253965.0 0 0 0 0 0 1 0 0 78 254036.0 0 0 0 0 0 0 1 0 79 259733.0 0 0 0 0 0 0 0 1 80 266302.0 0 0 0 0 0 0 0 0 81 277784.0 0 0 0 0 0 0 0 0 82 282973.0 0 0 0 0 0 0 0 0 83 283398.0 0 0 0 0 0 0 0 0 84 300454.0 0 0 0 0 0 0 0 0 85 304528.0 0 1 0 0 0 0 0 0 86 298325.0 0 0 1 0 0 0 0 0 87 311393.0 0 0 0 1 0 0 0 0 88 316867.0 0 0 0 0 1 0 0 0 89 322725.0 0 0 0 0 0 1 0 0 90 317988.0 0 0 0 0 0 0 1 0 91 274957.0 1 0 0 0 0 0 0 1 92 267993.0 1 0 0 0 0 0 0 0 93 260728.0 1 0 0 0 0 0 0 0 94 286828.0 1 0 0 0 0 0 0 0 95 265985.0 1 0 0 0 0 0 0 0 96 263718.0 1 0 0 0 0 0 0 0 97 239891.0 1 1 0 0 0 0 0 0 98 241398.0 1 0 1 0 0 0 0 0 99 238924.0 1 0 0 1 0 0 0 0 100 246829.0 1 0 0 0 1 0 0 0 101 234725.0 1 0 0 0 0 1 0 0 102 199177.0 1 0 0 0 0 0 1 0 103 189131.0 1 0 0 0 0 0 0 1 104 198293.0 1 0 0 0 0 0 0 0 105 165763.0 1 0 0 0 0 0 0 0 106 124900.0 1 0 0 0 0 0 0 0 M8 M9 M10 M11 t 1 0 0 0 0 1 2 0 0 0 0 2 3 0 0 0 0 3 4 0 0 0 0 4 5 0 0 0 0 5 6 0 0 0 0 6 7 0 0 0 0 7 8 1 0 0 0 8 9 0 1 0 0 9 10 0 0 1 0 10 11 0 0 0 1 11 12 0 0 0 0 12 13 0 0 0 0 13 14 0 0 0 0 14 15 0 0 0 0 15 16 0 0 0 0 16 17 0 0 0 0 17 18 0 0 0 0 18 19 0 0 0 0 19 20 1 0 0 0 20 21 0 1 0 0 21 22 0 0 1 0 22 23 0 0 0 1 23 24 0 0 0 0 24 25 0 0 0 0 25 26 0 0 0 0 26 27 0 0 0 0 27 28 0 0 0 0 28 29 0 0 0 0 29 30 0 0 0 0 30 31 0 0 0 0 31 32 1 0 0 0 32 33 0 1 0 0 33 34 0 0 1 0 34 35 0 0 0 1 35 36 0 0 0 0 36 37 0 0 0 0 37 38 0 0 0 0 38 39 0 0 0 0 39 40 0 0 0 0 40 41 0 0 0 0 41 42 0 0 0 0 42 43 0 0 0 0 43 44 1 0 0 0 44 45 0 1 0 0 45 46 0 0 1 0 46 47 0 0 0 1 47 48 0 0 0 0 48 49 0 0 0 0 49 50 0 0 0 0 50 51 0 0 0 0 51 52 0 0 0 0 52 53 0 0 0 0 53 54 0 0 0 0 54 55 0 0 0 0 55 56 1 0 0 0 56 57 0 1 0 0 57 58 0 0 1 0 58 59 0 0 0 1 59 60 0 0 0 0 60 61 0 0 0 0 61 62 0 0 0 0 62 63 0 0 0 0 63 64 0 0 0 0 64 65 0 0 0 0 65 66 0 0 0 0 66 67 0 0 0 0 67 68 1 0 0 0 68 69 0 1 0 0 69 70 0 0 1 0 70 71 0 0 0 1 71 72 0 0 0 0 72 73 0 0 0 0 73 74 0 0 0 0 74 75 0 0 0 0 75 76 0 0 0 0 76 77 0 0 0 0 77 78 0 0 0 0 78 79 0 0 0 0 79 80 1 0 0 0 80 81 0 1 0 0 81 82 0 0 1 0 82 83 0 0 0 1 83 84 0 0 0 0 84 85 0 0 0 0 85 86 0 0 0 0 86 87 0 0 0 0 87 88 0 0 0 0 88 89 0 0 0 0 89 90 0 0 0 0 90 91 0 0 0 0 91 92 1 0 0 0 92 93 0 1 0 0 93 94 0 0 1 0 94 95 0 0 0 1 95 96 0 0 0 0 96 97 0 0 0 0 97 98 0 0 0 0 98 99 0 0 0 0 99 100 0 0 0 0 100 101 0 0 0 0 101 102 0 0 0 0 102 103 0 0 0 0 103 104 1 0 0 0 104 105 0 1 0 0 105 106 0 0 1 0 106 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) `Wel(1)_geen(0)_financi\353le_crisis` 131973 -35410 M1 M2 -2527 -2952 M3 M4 -4539 -1389 M5 M6 -4915 -10071 M7 M8 -12220 -11386 M9 M10 -17533 -18421 M11 t -6804 1464 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -108378 -35963 4651 29162 71113 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 131973.1 17647.8 7.478 4.32e-11 *** `Wel(1)_geen(0)_financi\353le_crisis` -35410.2 15248.0 -2.322 0.0224 * M1 -2526.8 21251.9 -0.119 0.9056 M2 -2951.7 21246.4 -0.139 0.8898 M3 -4539.4 21242.3 -0.214 0.8313 M4 -1388.6 21239.7 -0.065 0.9480 M5 -4915.4 21238.6 -0.231 0.8175 M6 -10071.2 21238.9 -0.474 0.6365 M7 -12219.8 21282.7 -0.574 0.5673 M8 -11386.3 21277.2 -0.535 0.5938 M9 -17533.0 21273.3 -0.824 0.4120 M10 -18421.0 21270.8 -0.866 0.3887 M11 -6803.6 21854.3 -0.311 0.7563 t 1463.5 177.2 8.258 1.04e-12 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 43710 on 92 degrees of freedom Multiple R-squared: 0.4711, Adjusted R-squared: 0.3963 F-statistic: 6.303 on 13 and 92 DF, p-value: 2.429e-08 > postscript(file="/var/www/html/freestat/rcomp/tmp/1tzcu1228652355.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/freestat/rcomp/tmp/2rtn31228652355.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/3ooxd1228652355.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/42mmy1228652355.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/5xg3u1228652355.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 106 Frequency = 1 1 2 3 4 5 6 29736.968 28688.723 33173.068 31545.690 38193.234 48196.846 7 8 9 10 11 12 51934.778 55419.122 60464.300 61704.644 40898.019 47121.931 13 14 15 16 17 18 28322.098 29319.353 19547.598 13901.320 14592.264 21077.676 19 20 21 22 23 24 27623.908 22635.952 13654.830 10389.474 3281.249 19160.061 25 26 27 28 29 30 1166.228 -1083.417 -1217.672 -3445.750 -7039.806 -14281.394 31 32 33 34 35 36 -28642.362 -31640.118 -47763.840 -42185.096 -51473.521 -62206.509 37 38 39 40 41 42 -69508.642 -78369.987 -80100.042 -71383.620 -65264.976 -60726.765 43 44 45 46 47 48 -55674.232 -55513.288 -50720.410 -45182.066 -57635.791 -64630.879 49 50 51 52 53 54 -52915.712 -47740.757 -42382.412 -43544.890 -42518.246 -35802.135 55 56 57 58 59 60 -36017.202 -32543.558 -15717.480 -10124.336 -17563.461 -18867.549 61 62 63 64 65 66 -12313.682 -5370.727 -15791.782 -17264.860 -12847.316 -4212.005 67 68 69 70 71 72 4942.028 3932.972 16637.150 13252.594 8550.669 7225.481 73 74 75 76 77 78 20941.748 26759.103 28131.248 27401.870 14214.114 17977.425 79 80 81 82 83 84 24359.457 28631.402 44796.580 49410.024 36754.099 45542.911 85 86 87 88 89 90 50680.178 43438.533 56630.678 57490.300 65411.544 64366.855 91 92 93 94 95 96 57431.099 48170.043 45588.221 71112.665 37188.740 26654.552 97 98 99 100 101 102 3890.819 4359.174 2009.319 5299.941 -4740.815 -36596.504 103 104 105 106 -45957.472 -39092.527 -66939.349 -108377.905 > postscript(file="/var/www/html/freestat/rcomp/tmp/6y6001228652355.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 = 106 Frequency = 1 lag(myerror, k = 1) myerror 0 29736.968 NA 1 28688.723 29736.968 2 33173.068 28688.723 3 31545.690 33173.068 4 38193.234 31545.690 5 48196.846 38193.234 6 51934.778 48196.846 7 55419.122 51934.778 8 60464.300 55419.122 9 61704.644 60464.300 10 40898.019 61704.644 11 47121.931 40898.019 12 28322.098 47121.931 13 29319.353 28322.098 14 19547.598 29319.353 15 13901.320 19547.598 16 14592.264 13901.320 17 21077.676 14592.264 18 27623.908 21077.676 19 22635.952 27623.908 20 13654.830 22635.952 21 10389.474 13654.830 22 3281.249 10389.474 23 19160.061 3281.249 24 1166.228 19160.061 25 -1083.417 1166.228 26 -1217.672 -1083.417 27 -3445.750 -1217.672 28 -7039.806 -3445.750 29 -14281.394 -7039.806 30 -28642.362 -14281.394 31 -31640.118 -28642.362 32 -47763.840 -31640.118 33 -42185.096 -47763.840 34 -51473.521 -42185.096 35 -62206.509 -51473.521 36 -69508.642 -62206.509 37 -78369.987 -69508.642 38 -80100.042 -78369.987 39 -71383.620 -80100.042 40 -65264.976 -71383.620 41 -60726.765 -65264.976 42 -55674.232 -60726.765 43 -55513.288 -55674.232 44 -50720.410 -55513.288 45 -45182.066 -50720.410 46 -57635.791 -45182.066 47 -64630.879 -57635.791 48 -52915.712 -64630.879 49 -47740.757 -52915.712 50 -42382.412 -47740.757 51 -43544.890 -42382.412 52 -42518.246 -43544.890 53 -35802.135 -42518.246 54 -36017.202 -35802.135 55 -32543.558 -36017.202 56 -15717.480 -32543.558 57 -10124.336 -15717.480 58 -17563.461 -10124.336 59 -18867.549 -17563.461 60 -12313.682 -18867.549 61 -5370.727 -12313.682 62 -15791.782 -5370.727 63 -17264.860 -15791.782 64 -12847.316 -17264.860 65 -4212.005 -12847.316 66 4942.028 -4212.005 67 3932.972 4942.028 68 16637.150 3932.972 69 13252.594 16637.150 70 8550.669 13252.594 71 7225.481 8550.669 72 20941.748 7225.481 73 26759.103 20941.748 74 28131.248 26759.103 75 27401.870 28131.248 76 14214.114 27401.870 77 17977.425 14214.114 78 24359.457 17977.425 79 28631.402 24359.457 80 44796.580 28631.402 81 49410.024 44796.580 82 36754.099 49410.024 83 45542.911 36754.099 84 50680.178 45542.911 85 43438.533 50680.178 86 56630.678 43438.533 87 57490.300 56630.678 88 65411.544 57490.300 89 64366.855 65411.544 90 57431.099 64366.855 91 48170.043 57431.099 92 45588.221 48170.043 93 71112.665 45588.221 94 37188.740 71112.665 95 26654.552 37188.740 96 3890.819 26654.552 97 4359.174 3890.819 98 2009.319 4359.174 99 5299.941 2009.319 100 -4740.815 5299.941 101 -36596.504 -4740.815 102 -45957.472 -36596.504 103 -39092.527 -45957.472 104 -66939.349 -39092.527 105 -108377.905 -66939.349 106 NA -108377.905 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 28688.723 29736.968 [2,] 33173.068 28688.723 [3,] 31545.690 33173.068 [4,] 38193.234 31545.690 [5,] 48196.846 38193.234 [6,] 51934.778 48196.846 [7,] 55419.122 51934.778 [8,] 60464.300 55419.122 [9,] 61704.644 60464.300 [10,] 40898.019 61704.644 [11,] 47121.931 40898.019 [12,] 28322.098 47121.931 [13,] 29319.353 28322.098 [14,] 19547.598 29319.353 [15,] 13901.320 19547.598 [16,] 14592.264 13901.320 [17,] 21077.676 14592.264 [18,] 27623.908 21077.676 [19,] 22635.952 27623.908 [20,] 13654.830 22635.952 [21,] 10389.474 13654.830 [22,] 3281.249 10389.474 [23,] 19160.061 3281.249 [24,] 1166.228 19160.061 [25,] -1083.417 1166.228 [26,] -1217.672 -1083.417 [27,] -3445.750 -1217.672 [28,] -7039.806 -3445.750 [29,] -14281.394 -7039.806 [30,] -28642.362 -14281.394 [31,] -31640.118 -28642.362 [32,] -47763.840 -31640.118 [33,] -42185.096 -47763.840 [34,] -51473.521 -42185.096 [35,] -62206.509 -51473.521 [36,] -69508.642 -62206.509 [37,] -78369.987 -69508.642 [38,] -80100.042 -78369.987 [39,] -71383.620 -80100.042 [40,] -65264.976 -71383.620 [41,] -60726.765 -65264.976 [42,] -55674.232 -60726.765 [43,] -55513.288 -55674.232 [44,] -50720.410 -55513.288 [45,] -45182.066 -50720.410 [46,] -57635.791 -45182.066 [47,] -64630.879 -57635.791 [48,] -52915.712 -64630.879 [49,] -47740.757 -52915.712 [50,] -42382.412 -47740.757 [51,] -43544.890 -42382.412 [52,] -42518.246 -43544.890 [53,] -35802.135 -42518.246 [54,] -36017.202 -35802.135 [55,] -32543.558 -36017.202 [56,] -15717.480 -32543.558 [57,] -10124.336 -15717.480 [58,] -17563.461 -10124.336 [59,] -18867.549 -17563.461 [60,] -12313.682 -18867.549 [61,] -5370.727 -12313.682 [62,] -15791.782 -5370.727 [63,] -17264.860 -15791.782 [64,] -12847.316 -17264.860 [65,] -4212.005 -12847.316 [66,] 4942.028 -4212.005 [67,] 3932.972 4942.028 [68,] 16637.150 3932.972 [69,] 13252.594 16637.150 [70,] 8550.669 13252.594 [71,] 7225.481 8550.669 [72,] 20941.748 7225.481 [73,] 26759.103 20941.748 [74,] 28131.248 26759.103 [75,] 27401.870 28131.248 [76,] 14214.114 27401.870 [77,] 17977.425 14214.114 [78,] 24359.457 17977.425 [79,] 28631.402 24359.457 [80,] 44796.580 28631.402 [81,] 49410.024 44796.580 [82,] 36754.099 49410.024 [83,] 45542.911 36754.099 [84,] 50680.178 45542.911 [85,] 43438.533 50680.178 [86,] 56630.678 43438.533 [87,] 57490.300 56630.678 [88,] 65411.544 57490.300 [89,] 64366.855 65411.544 [90,] 57431.099 64366.855 [91,] 48170.043 57431.099 [92,] 45588.221 48170.043 [93,] 71112.665 45588.221 [94,] 37188.740 71112.665 [95,] 26654.552 37188.740 [96,] 3890.819 26654.552 [97,] 4359.174 3890.819 [98,] 2009.319 4359.174 [99,] 5299.941 2009.319 [100,] -4740.815 5299.941 [101,] -36596.504 -4740.815 [102,] -45957.472 -36596.504 [103,] -39092.527 -45957.472 [104,] -66939.349 -39092.527 [105,] -108377.905 -66939.349 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 28688.723 29736.968 2 33173.068 28688.723 3 31545.690 33173.068 4 38193.234 31545.690 5 48196.846 38193.234 6 51934.778 48196.846 7 55419.122 51934.778 8 60464.300 55419.122 9 61704.644 60464.300 10 40898.019 61704.644 11 47121.931 40898.019 12 28322.098 47121.931 13 29319.353 28322.098 14 19547.598 29319.353 15 13901.320 19547.598 16 14592.264 13901.320 17 21077.676 14592.264 18 27623.908 21077.676 19 22635.952 27623.908 20 13654.830 22635.952 21 10389.474 13654.830 22 3281.249 10389.474 23 19160.061 3281.249 24 1166.228 19160.061 25 -1083.417 1166.228 26 -1217.672 -1083.417 27 -3445.750 -1217.672 28 -7039.806 -3445.750 29 -14281.394 -7039.806 30 -28642.362 -14281.394 31 -31640.118 -28642.362 32 -47763.840 -31640.118 33 -42185.096 -47763.840 34 -51473.521 -42185.096 35 -62206.509 -51473.521 36 -69508.642 -62206.509 37 -78369.987 -69508.642 38 -80100.042 -78369.987 39 -71383.620 -80100.042 40 -65264.976 -71383.620 41 -60726.765 -65264.976 42 -55674.232 -60726.765 43 -55513.288 -55674.232 44 -50720.410 -55513.288 45 -45182.066 -50720.410 46 -57635.791 -45182.066 47 -64630.879 -57635.791 48 -52915.712 -64630.879 49 -47740.757 -52915.712 50 -42382.412 -47740.757 51 -43544.890 -42382.412 52 -42518.246 -43544.890 53 -35802.135 -42518.246 54 -36017.202 -35802.135 55 -32543.558 -36017.202 56 -15717.480 -32543.558 57 -10124.336 -15717.480 58 -17563.461 -10124.336 59 -18867.549 -17563.461 60 -12313.682 -18867.549 61 -5370.727 -12313.682 62 -15791.782 -5370.727 63 -17264.860 -15791.782 64 -12847.316 -17264.860 65 -4212.005 -12847.316 66 4942.028 -4212.005 67 3932.972 4942.028 68 16637.150 3932.972 69 13252.594 16637.150 70 8550.669 13252.594 71 7225.481 8550.669 72 20941.748 7225.481 73 26759.103 20941.748 74 28131.248 26759.103 75 27401.870 28131.248 76 14214.114 27401.870 77 17977.425 14214.114 78 24359.457 17977.425 79 28631.402 24359.457 80 44796.580 28631.402 81 49410.024 44796.580 82 36754.099 49410.024 83 45542.911 36754.099 84 50680.178 45542.911 85 43438.533 50680.178 86 56630.678 43438.533 87 57490.300 56630.678 88 65411.544 57490.300 89 64366.855 65411.544 90 57431.099 64366.855 91 48170.043 57431.099 92 45588.221 48170.043 93 71112.665 45588.221 94 37188.740 71112.665 95 26654.552 37188.740 96 3890.819 26654.552 97 4359.174 3890.819 98 2009.319 4359.174 99 5299.941 2009.319 100 -4740.815 5299.941 101 -36596.504 -4740.815 102 -45957.472 -36596.504 103 -39092.527 -45957.472 104 -66939.349 -39092.527 105 -108377.905 -66939.349 > 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/freestat/rcomp/tmp/7dy9n1228652355.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/8zsg11228652355.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/92ih71228652355.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/freestat/rcomp/tmp/10cl581228652355.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/freestat/rcomp/tmp/11lej11228652355.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/freestat/rcomp/tmp/12aay01228652356.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/freestat/rcomp/tmp/1309yc1228652356.tab") > > system("convert tmp/1tzcu1228652355.ps tmp/1tzcu1228652355.png") > system("convert tmp/2rtn31228652355.ps tmp/2rtn31228652355.png") > system("convert tmp/3ooxd1228652355.ps tmp/3ooxd1228652355.png") > system("convert tmp/42mmy1228652355.ps tmp/42mmy1228652355.png") > system("convert tmp/5xg3u1228652355.ps tmp/5xg3u1228652355.png") > system("convert tmp/6y6001228652355.ps tmp/6y6001228652355.png") > system("convert tmp/7dy9n1228652355.ps tmp/7dy9n1228652355.png") > system("convert tmp/8zsg11228652355.ps tmp/8zsg11228652355.png") > system("convert tmp/92ih71228652355.ps tmp/92ih71228652355.png") > > > proc.time() user system elapsed 3.104 2.252 3.382