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Type 'q()' to quit R. > x <- array(list(3030.29 + ,0 + ,2803.47 + ,0 + ,2767.63 + ,0 + ,2882.6 + ,0 + ,2863.36 + ,0 + ,2897.06 + ,0 + ,3012.61 + ,0 + ,3142.95 + ,0 + ,3032.93 + ,0 + ,3045.78 + ,0 + ,3110.52 + ,0 + ,3013.24 + ,0 + ,2987.1 + ,0 + ,2995.55 + ,0 + ,2833.18 + ,0 + ,2848.96 + ,0 + ,2794.83 + ,0 + ,2845.26 + ,0 + ,2915.02 + ,0 + ,2892.63 + ,0 + ,2604.42 + ,0 + ,2641.65 + ,0 + ,2659.81 + ,0 + ,2638.53 + ,0 + ,2720.25 + ,0 + ,2745.88 + ,0 + ,2735.7 + ,0 + ,2811.7 + ,0 + ,2799.43 + ,0 + ,2555.28 + ,0 + ,2304.98 + ,0 + ,2214.95 + ,0 + ,2065.81 + ,0 + ,1940.49 + ,0 + ,2042 + ,0 + ,1995.37 + ,0 + ,1946.81 + ,0 + ,1765.9 + ,0 + ,1635.25 + ,0 + ,1833.42 + ,0 + ,1910.43 + ,0 + ,1959.67 + ,0 + ,1969.6 + ,0 + ,2061.41 + ,0 + ,2093.48 + ,0 + ,2120.88 + ,0 + ,2174.56 + ,0 + ,2196.72 + ,0 + ,2350.44 + ,0 + ,2440.25 + ,0 + ,2408.64 + ,0 + ,2472.81 + ,0 + ,2407.6 + ,0 + ,2454.62 + ,0 + ,2448.05 + ,0 + ,2497.84 + ,0 + ,2645.64 + ,0 + ,2756.76 + ,0 + ,2849.27 + ,0 + ,2921.44 + ,0 + ,2981.85 + ,0 + ,3080.58 + ,0 + ,3106.22 + ,0 + ,3119.31 + ,0 + ,3061.26 + ,0 + ,3097.31 + ,0 + ,3161.69 + ,0 + ,3257.16 + ,0 + ,3277.01 + ,0 + ,3295.32 + ,0 + ,3363.99 + ,0 + ,3494.17 + ,0 + ,3667.03 + ,0 + ,3813.06 + ,0 + ,3917.96 + ,0 + ,3895.51 + ,0 + ,3801.06 + ,0 + ,3570.12 + ,0 + ,3701.61 + ,0 + ,3862.27 + ,0 + ,3970.1 + ,0 + ,4138.52 + ,0 + ,4199.75 + ,0 + ,4290.89 + ,0 + ,4443.91 + ,0 + ,4502.64 + ,0 + ,4356.98 + ,0 + ,4591.27 + ,0 + ,4696.96 + ,0 + ,4621.4 + ,0 + ,4562.84 + ,0 + ,4202.52 + ,0 + ,4296.49 + ,0 + ,4435.23 + ,0 + ,4105.18 + ,0 + ,4116.68 + ,0 + ,3844.49 + ,1 + ,3720.98 + ,1 + ,3674.4 + ,1 + ,3857.62 + ,1 + ,3801.06 + ,1 + ,3504.37 + ,1 + ,3032.6 + ,1 + ,3047.03 + ,1 + ,2962.34 + ,1 + ,2197.82 + ,1 + ,2014.45 + ,1) + ,dim=c(2 + ,107) + ,dimnames=list(c('BEL-20' + ,'Wel(1)_geen(0)_financiële_crisis') + ,1:107)) > y <- array(NA,dim=c(2,107),dimnames=list(c('BEL-20','Wel(1)_geen(0)_financiële_crisis'),1:107)) > 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 BEL-20 Wel(1)_geen(0)_financi\353le_crisis M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 1 3030.29 0 1 0 0 0 0 0 0 0 0 0 2 2803.47 0 0 1 0 0 0 0 0 0 0 0 3 2767.63 0 0 0 1 0 0 0 0 0 0 0 4 2882.60 0 0 0 0 1 0 0 0 0 0 0 5 2863.36 0 0 0 0 0 1 0 0 0 0 0 6 2897.06 0 0 0 0 0 0 1 0 0 0 0 7 3012.61 0 0 0 0 0 0 0 1 0 0 0 8 3142.95 0 0 0 0 0 0 0 0 1 0 0 9 3032.93 0 0 0 0 0 0 0 0 0 1 0 10 3045.78 0 0 0 0 0 0 0 0 0 0 1 11 3110.52 0 0 0 0 0 0 0 0 0 0 0 12 3013.24 0 0 0 0 0 0 0 0 0 0 0 13 2987.10 0 1 0 0 0 0 0 0 0 0 0 14 2995.55 0 0 1 0 0 0 0 0 0 0 0 15 2833.18 0 0 0 1 0 0 0 0 0 0 0 16 2848.96 0 0 0 0 1 0 0 0 0 0 0 17 2794.83 0 0 0 0 0 1 0 0 0 0 0 18 2845.26 0 0 0 0 0 0 1 0 0 0 0 19 2915.02 0 0 0 0 0 0 0 1 0 0 0 20 2892.63 0 0 0 0 0 0 0 0 1 0 0 21 2604.42 0 0 0 0 0 0 0 0 0 1 0 22 2641.65 0 0 0 0 0 0 0 0 0 0 1 23 2659.81 0 0 0 0 0 0 0 0 0 0 0 24 2638.53 0 0 0 0 0 0 0 0 0 0 0 25 2720.25 0 1 0 0 0 0 0 0 0 0 0 26 2745.88 0 0 1 0 0 0 0 0 0 0 0 27 2735.70 0 0 0 1 0 0 0 0 0 0 0 28 2811.70 0 0 0 0 1 0 0 0 0 0 0 29 2799.43 0 0 0 0 0 1 0 0 0 0 0 30 2555.28 0 0 0 0 0 0 1 0 0 0 0 31 2304.98 0 0 0 0 0 0 0 1 0 0 0 32 2214.95 0 0 0 0 0 0 0 0 1 0 0 33 2065.81 0 0 0 0 0 0 0 0 0 1 0 34 1940.49 0 0 0 0 0 0 0 0 0 0 1 35 2042.00 0 0 0 0 0 0 0 0 0 0 0 36 1995.37 0 0 0 0 0 0 0 0 0 0 0 37 1946.81 0 1 0 0 0 0 0 0 0 0 0 38 1765.90 0 0 1 0 0 0 0 0 0 0 0 39 1635.25 0 0 0 1 0 0 0 0 0 0 0 40 1833.42 0 0 0 0 1 0 0 0 0 0 0 41 1910.43 0 0 0 0 0 1 0 0 0 0 0 42 1959.67 0 0 0 0 0 0 1 0 0 0 0 43 1969.60 0 0 0 0 0 0 0 1 0 0 0 44 2061.41 0 0 0 0 0 0 0 0 1 0 0 45 2093.48 0 0 0 0 0 0 0 0 0 1 0 46 2120.88 0 0 0 0 0 0 0 0 0 0 1 47 2174.56 0 0 0 0 0 0 0 0 0 0 0 48 2196.72 0 0 0 0 0 0 0 0 0 0 0 49 2350.44 0 1 0 0 0 0 0 0 0 0 0 50 2440.25 0 0 1 0 0 0 0 0 0 0 0 51 2408.64 0 0 0 1 0 0 0 0 0 0 0 52 2472.81 0 0 0 0 1 0 0 0 0 0 0 53 2407.60 0 0 0 0 0 1 0 0 0 0 0 54 2454.62 0 0 0 0 0 0 1 0 0 0 0 55 2448.05 0 0 0 0 0 0 0 1 0 0 0 56 2497.84 0 0 0 0 0 0 0 0 1 0 0 57 2645.64 0 0 0 0 0 0 0 0 0 1 0 58 2756.76 0 0 0 0 0 0 0 0 0 0 1 59 2849.27 0 0 0 0 0 0 0 0 0 0 0 60 2921.44 0 0 0 0 0 0 0 0 0 0 0 61 2981.85 0 1 0 0 0 0 0 0 0 0 0 62 3080.58 0 0 1 0 0 0 0 0 0 0 0 63 3106.22 0 0 0 1 0 0 0 0 0 0 0 64 3119.31 0 0 0 0 1 0 0 0 0 0 0 65 3061.26 0 0 0 0 0 1 0 0 0 0 0 66 3097.31 0 0 0 0 0 0 1 0 0 0 0 67 3161.69 0 0 0 0 0 0 0 1 0 0 0 68 3257.16 0 0 0 0 0 0 0 0 1 0 0 69 3277.01 0 0 0 0 0 0 0 0 0 1 0 70 3295.32 0 0 0 0 0 0 0 0 0 0 1 71 3363.99 0 0 0 0 0 0 0 0 0 0 0 72 3494.17 0 0 0 0 0 0 0 0 0 0 0 73 3667.03 0 1 0 0 0 0 0 0 0 0 0 74 3813.06 0 0 1 0 0 0 0 0 0 0 0 75 3917.96 0 0 0 1 0 0 0 0 0 0 0 76 3895.51 0 0 0 0 1 0 0 0 0 0 0 77 3801.06 0 0 0 0 0 1 0 0 0 0 0 78 3570.12 0 0 0 0 0 0 1 0 0 0 0 79 3701.61 0 0 0 0 0 0 0 1 0 0 0 80 3862.27 0 0 0 0 0 0 0 0 1 0 0 81 3970.10 0 0 0 0 0 0 0 0 0 1 0 82 4138.52 0 0 0 0 0 0 0 0 0 0 1 83 4199.75 0 0 0 0 0 0 0 0 0 0 0 84 4290.89 0 0 0 0 0 0 0 0 0 0 0 85 4443.91 0 1 0 0 0 0 0 0 0 0 0 86 4502.64 0 0 1 0 0 0 0 0 0 0 0 87 4356.98 0 0 0 1 0 0 0 0 0 0 0 88 4591.27 0 0 0 0 1 0 0 0 0 0 0 89 4696.96 0 0 0 0 0 1 0 0 0 0 0 90 4621.40 0 0 0 0 0 0 1 0 0 0 0 91 4562.84 0 0 0 0 0 0 0 1 0 0 0 92 4202.52 0 0 0 0 0 0 0 0 1 0 0 93 4296.49 0 0 0 0 0 0 0 0 0 1 0 94 4435.23 0 0 0 0 0 0 0 0 0 0 1 95 4105.18 0 0 0 0 0 0 0 0 0 0 0 96 4116.68 0 0 0 0 0 0 0 0 0 0 0 97 3844.49 1 1 0 0 0 0 0 0 0 0 0 98 3720.98 1 0 1 0 0 0 0 0 0 0 0 99 3674.40 1 0 0 1 0 0 0 0 0 0 0 100 3857.62 1 0 0 0 1 0 0 0 0 0 0 101 3801.06 1 0 0 0 0 1 0 0 0 0 0 102 3504.37 1 0 0 0 0 0 1 0 0 0 0 103 3032.60 1 0 0 0 0 0 0 1 0 0 0 104 3047.03 1 0 0 0 0 0 0 0 1 0 0 105 2962.34 1 0 0 0 0 0 0 0 0 1 0 106 2197.82 1 0 0 0 0 0 0 0 0 0 1 107 2014.45 1 0 0 0 0 0 0 0 0 0 0 M11 t 1 0 1 2 0 2 3 0 3 4 0 4 5 0 5 6 0 6 7 0 7 8 0 8 9 0 9 10 0 10 11 1 11 12 0 12 13 0 13 14 0 14 15 0 15 16 0 16 17 0 17 18 0 18 19 0 19 20 0 20 21 0 21 22 0 22 23 1 23 24 0 24 25 0 25 26 0 26 27 0 27 28 0 28 29 0 29 30 0 30 31 0 31 32 0 32 33 0 33 34 0 34 35 1 35 36 0 36 37 0 37 38 0 38 39 0 39 40 0 40 41 0 41 42 0 42 43 0 43 44 0 44 45 0 45 46 0 46 47 1 47 48 0 48 49 0 49 50 0 50 51 0 51 52 0 52 53 0 53 54 0 54 55 0 55 56 0 56 57 0 57 58 0 58 59 1 59 60 0 60 61 0 61 62 0 62 63 0 63 64 0 64 65 0 65 66 0 66 67 0 67 68 0 68 69 0 69 70 0 70 71 1 71 72 0 72 73 0 73 74 0 74 75 0 75 76 0 76 77 0 77 78 0 78 79 0 79 80 0 80 81 0 81 82 0 82 83 1 83 84 0 84 85 0 85 86 0 86 87 0 87 88 0 88 89 0 89 90 0 90 91 0 91 92 0 92 93 0 93 94 0 94 95 1 95 96 0 96 97 0 97 98 0 98 99 0 99 100 0 100 101 0 101 102 0 102 103 0 103 104 0 104 105 0 105 106 0 106 107 1 107 > 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` 2091.239 -772.189 M1 M2 202.303 172.390 M3 M4 105.978 185.076 M5 M6 147.013 58.540 M7 M8 -3.843 -14.465 M9 M10 -58.453 -118.579 M11 t -142.832 18.373 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -1278.51 -442.08 80.08 478.93 960.01 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2091.239 255.318 8.191 1.35e-12 *** `Wel(1)_geen(0)_financi\353le_crisis` -772.189 237.103 -3.257 0.00157 ** M1 202.303 307.143 0.659 0.51174 M2 172.390 306.957 0.562 0.57573 M3 105.978 306.789 0.345 0.73054 M4 185.076 306.638 0.604 0.54760 M5 147.013 306.505 0.480 0.63261 M6 58.540 306.390 0.191 0.84889 M7 -3.843 306.292 -0.013 0.99002 M8 -14.465 306.212 -0.047 0.96242 M9 -58.453 306.150 -0.191 0.84900 M10 -118.579 306.105 -0.387 0.69936 M11 -142.832 306.079 -0.467 0.64184 t 18.373 2.332 7.879 6.06e-12 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 628.2 on 93 degrees of freedom Multiple R-squared: 0.409, Adjusted R-squared: 0.3264 F-statistic: 4.95 on 13 and 93 DF, p-value: 1.557e-06 > postscript(file="/var/www/html/rcomp/tmp/1pusy1229005467.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/2zo8g1229005467.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/31wrc1229005467.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4sbf31229005467.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/57d6i1229005467.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 107 Frequency = 1 1 2 3 4 5 6 718.375619 503.095619 515.294508 532.793396 533.243396 637.043396 7 8 9 10 11 12 796.603396 919.192285 834.787841 889.390063 960.010063 701.525417 13 14 15 16 17 18 454.709785 474.699785 360.368674 278.677563 244.237563 364.767563 19 20 21 22 23 24 478.537563 448.396452 185.802008 264.784230 288.824230 106.339583 25 26 27 28 29 30 -32.616048 4.553952 42.412841 20.941730 28.361730 -145.688270 31 32 33 34 35 36 -351.978270 -449.759381 -573.283826 -656.851604 -549.461604 -757.296250 37 38 39 40 41 42 -1026.531881 -1195.901881 -1278.512992 -1177.814104 -1081.114104 -961.774104 43 44 45 46 47 48 -907.834104 -823.775215 -766.089659 -696.937437 -637.377437 -776.422083 49 50 51 52 53 54 -843.377715 -742.027715 -725.598826 -758.899937 -804.419937 -687.299937 55 56 57 58 59 60 -649.859937 -607.821048 -434.405492 -281.533270 -183.143270 -272.177917 61 62 63 64 65 66 -432.443548 -322.173548 -248.494659 -332.875770 -371.235770 -265.085770 67 68 69 70 71 72 -156.695770 -68.976881 -23.511326 36.550896 111.100896 80.076250 73 74 75 76 77 78 32.260619 189.830619 342.769508 222.848396 148.088396 -12.751604 79 80 81 82 83 84 162.748396 315.657285 449.102841 659.275063 726.385063 656.320417 85 86 87 88 89 90 588.664785 658.934785 561.313674 698.132563 823.512563 818.052563 91 92 93 94 95 96 803.502563 435.431452 555.017008 735.509230 411.339230 261.634583 97 98 99 100 101 102 540.958384 428.988384 430.447273 516.196162 479.326162 252.736162 103 104 105 106 107 -175.023838 -168.344949 -227.419394 -950.187172 -1127.677172 > postscript(file="/var/www/html/rcomp/tmp/6wqu21229005467.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 = 107 Frequency = 1 lag(myerror, k = 1) myerror 0 718.375619 NA 1 503.095619 718.375619 2 515.294508 503.095619 3 532.793396 515.294508 4 533.243396 532.793396 5 637.043396 533.243396 6 796.603396 637.043396 7 919.192285 796.603396 8 834.787841 919.192285 9 889.390063 834.787841 10 960.010063 889.390063 11 701.525417 960.010063 12 454.709785 701.525417 13 474.699785 454.709785 14 360.368674 474.699785 15 278.677563 360.368674 16 244.237563 278.677563 17 364.767563 244.237563 18 478.537563 364.767563 19 448.396452 478.537563 20 185.802008 448.396452 21 264.784230 185.802008 22 288.824230 264.784230 23 106.339583 288.824230 24 -32.616048 106.339583 25 4.553952 -32.616048 26 42.412841 4.553952 27 20.941730 42.412841 28 28.361730 20.941730 29 -145.688270 28.361730 30 -351.978270 -145.688270 31 -449.759381 -351.978270 32 -573.283826 -449.759381 33 -656.851604 -573.283826 34 -549.461604 -656.851604 35 -757.296250 -549.461604 36 -1026.531881 -757.296250 37 -1195.901881 -1026.531881 38 -1278.512992 -1195.901881 39 -1177.814104 -1278.512992 40 -1081.114104 -1177.814104 41 -961.774104 -1081.114104 42 -907.834104 -961.774104 43 -823.775215 -907.834104 44 -766.089659 -823.775215 45 -696.937437 -766.089659 46 -637.377437 -696.937437 47 -776.422083 -637.377437 48 -843.377715 -776.422083 49 -742.027715 -843.377715 50 -725.598826 -742.027715 51 -758.899937 -725.598826 52 -804.419937 -758.899937 53 -687.299937 -804.419937 54 -649.859937 -687.299937 55 -607.821048 -649.859937 56 -434.405492 -607.821048 57 -281.533270 -434.405492 58 -183.143270 -281.533270 59 -272.177917 -183.143270 60 -432.443548 -272.177917 61 -322.173548 -432.443548 62 -248.494659 -322.173548 63 -332.875770 -248.494659 64 -371.235770 -332.875770 65 -265.085770 -371.235770 66 -156.695770 -265.085770 67 -68.976881 -156.695770 68 -23.511326 -68.976881 69 36.550896 -23.511326 70 111.100896 36.550896 71 80.076250 111.100896 72 32.260619 80.076250 73 189.830619 32.260619 74 342.769508 189.830619 75 222.848396 342.769508 76 148.088396 222.848396 77 -12.751604 148.088396 78 162.748396 -12.751604 79 315.657285 162.748396 80 449.102841 315.657285 81 659.275063 449.102841 82 726.385063 659.275063 83 656.320417 726.385063 84 588.664785 656.320417 85 658.934785 588.664785 86 561.313674 658.934785 87 698.132563 561.313674 88 823.512563 698.132563 89 818.052563 823.512563 90 803.502563 818.052563 91 435.431452 803.502563 92 555.017008 435.431452 93 735.509230 555.017008 94 411.339230 735.509230 95 261.634583 411.339230 96 540.958384 261.634583 97 428.988384 540.958384 98 430.447273 428.988384 99 516.196162 430.447273 100 479.326162 516.196162 101 252.736162 479.326162 102 -175.023838 252.736162 103 -168.344949 -175.023838 104 -227.419394 -168.344949 105 -950.187172 -227.419394 106 -1127.677172 -950.187172 107 NA -1127.677172 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 503.095619 718.375619 [2,] 515.294508 503.095619 [3,] 532.793396 515.294508 [4,] 533.243396 532.793396 [5,] 637.043396 533.243396 [6,] 796.603396 637.043396 [7,] 919.192285 796.603396 [8,] 834.787841 919.192285 [9,] 889.390063 834.787841 [10,] 960.010063 889.390063 [11,] 701.525417 960.010063 [12,] 454.709785 701.525417 [13,] 474.699785 454.709785 [14,] 360.368674 474.699785 [15,] 278.677563 360.368674 [16,] 244.237563 278.677563 [17,] 364.767563 244.237563 [18,] 478.537563 364.767563 [19,] 448.396452 478.537563 [20,] 185.802008 448.396452 [21,] 264.784230 185.802008 [22,] 288.824230 264.784230 [23,] 106.339583 288.824230 [24,] -32.616048 106.339583 [25,] 4.553952 -32.616048 [26,] 42.412841 4.553952 [27,] 20.941730 42.412841 [28,] 28.361730 20.941730 [29,] -145.688270 28.361730 [30,] -351.978270 -145.688270 [31,] -449.759381 -351.978270 [32,] -573.283826 -449.759381 [33,] -656.851604 -573.283826 [34,] -549.461604 -656.851604 [35,] -757.296250 -549.461604 [36,] -1026.531881 -757.296250 [37,] -1195.901881 -1026.531881 [38,] -1278.512992 -1195.901881 [39,] -1177.814104 -1278.512992 [40,] -1081.114104 -1177.814104 [41,] -961.774104 -1081.114104 [42,] -907.834104 -961.774104 [43,] -823.775215 -907.834104 [44,] -766.089659 -823.775215 [45,] -696.937437 -766.089659 [46,] -637.377437 -696.937437 [47,] -776.422083 -637.377437 [48,] -843.377715 -776.422083 [49,] -742.027715 -843.377715 [50,] -725.598826 -742.027715 [51,] -758.899937 -725.598826 [52,] -804.419937 -758.899937 [53,] -687.299937 -804.419937 [54,] -649.859937 -687.299937 [55,] -607.821048 -649.859937 [56,] -434.405492 -607.821048 [57,] -281.533270 -434.405492 [58,] -183.143270 -281.533270 [59,] -272.177917 -183.143270 [60,] -432.443548 -272.177917 [61,] -322.173548 -432.443548 [62,] -248.494659 -322.173548 [63,] -332.875770 -248.494659 [64,] -371.235770 -332.875770 [65,] -265.085770 -371.235770 [66,] -156.695770 -265.085770 [67,] -68.976881 -156.695770 [68,] -23.511326 -68.976881 [69,] 36.550896 -23.511326 [70,] 111.100896 36.550896 [71,] 80.076250 111.100896 [72,] 32.260619 80.076250 [73,] 189.830619 32.260619 [74,] 342.769508 189.830619 [75,] 222.848396 342.769508 [76,] 148.088396 222.848396 [77,] -12.751604 148.088396 [78,] 162.748396 -12.751604 [79,] 315.657285 162.748396 [80,] 449.102841 315.657285 [81,] 659.275063 449.102841 [82,] 726.385063 659.275063 [83,] 656.320417 726.385063 [84,] 588.664785 656.320417 [85,] 658.934785 588.664785 [86,] 561.313674 658.934785 [87,] 698.132563 561.313674 [88,] 823.512563 698.132563 [89,] 818.052563 823.512563 [90,] 803.502563 818.052563 [91,] 435.431452 803.502563 [92,] 555.017008 435.431452 [93,] 735.509230 555.017008 [94,] 411.339230 735.509230 [95,] 261.634583 411.339230 [96,] 540.958384 261.634583 [97,] 428.988384 540.958384 [98,] 430.447273 428.988384 [99,] 516.196162 430.447273 [100,] 479.326162 516.196162 [101,] 252.736162 479.326162 [102,] -175.023838 252.736162 [103,] -168.344949 -175.023838 [104,] -227.419394 -168.344949 [105,] -950.187172 -227.419394 [106,] -1127.677172 -950.187172 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 503.095619 718.375619 2 515.294508 503.095619 3 532.793396 515.294508 4 533.243396 532.793396 5 637.043396 533.243396 6 796.603396 637.043396 7 919.192285 796.603396 8 834.787841 919.192285 9 889.390063 834.787841 10 960.010063 889.390063 11 701.525417 960.010063 12 454.709785 701.525417 13 474.699785 454.709785 14 360.368674 474.699785 15 278.677563 360.368674 16 244.237563 278.677563 17 364.767563 244.237563 18 478.537563 364.767563 19 448.396452 478.537563 20 185.802008 448.396452 21 264.784230 185.802008 22 288.824230 264.784230 23 106.339583 288.824230 24 -32.616048 106.339583 25 4.553952 -32.616048 26 42.412841 4.553952 27 20.941730 42.412841 28 28.361730 20.941730 29 -145.688270 28.361730 30 -351.978270 -145.688270 31 -449.759381 -351.978270 32 -573.283826 -449.759381 33 -656.851604 -573.283826 34 -549.461604 -656.851604 35 -757.296250 -549.461604 36 -1026.531881 -757.296250 37 -1195.901881 -1026.531881 38 -1278.512992 -1195.901881 39 -1177.814104 -1278.512992 40 -1081.114104 -1177.814104 41 -961.774104 -1081.114104 42 -907.834104 -961.774104 43 -823.775215 -907.834104 44 -766.089659 -823.775215 45 -696.937437 -766.089659 46 -637.377437 -696.937437 47 -776.422083 -637.377437 48 -843.377715 -776.422083 49 -742.027715 -843.377715 50 -725.598826 -742.027715 51 -758.899937 -725.598826 52 -804.419937 -758.899937 53 -687.299937 -804.419937 54 -649.859937 -687.299937 55 -607.821048 -649.859937 56 -434.405492 -607.821048 57 -281.533270 -434.405492 58 -183.143270 -281.533270 59 -272.177917 -183.143270 60 -432.443548 -272.177917 61 -322.173548 -432.443548 62 -248.494659 -322.173548 63 -332.875770 -248.494659 64 -371.235770 -332.875770 65 -265.085770 -371.235770 66 -156.695770 -265.085770 67 -68.976881 -156.695770 68 -23.511326 -68.976881 69 36.550896 -23.511326 70 111.100896 36.550896 71 80.076250 111.100896 72 32.260619 80.076250 73 189.830619 32.260619 74 342.769508 189.830619 75 222.848396 342.769508 76 148.088396 222.848396 77 -12.751604 148.088396 78 162.748396 -12.751604 79 315.657285 162.748396 80 449.102841 315.657285 81 659.275063 449.102841 82 726.385063 659.275063 83 656.320417 726.385063 84 588.664785 656.320417 85 658.934785 588.664785 86 561.313674 658.934785 87 698.132563 561.313674 88 823.512563 698.132563 89 818.052563 823.512563 90 803.502563 818.052563 91 435.431452 803.502563 92 555.017008 435.431452 93 735.509230 555.017008 94 411.339230 735.509230 95 261.634583 411.339230 96 540.958384 261.634583 97 428.988384 540.958384 98 430.447273 428.988384 99 516.196162 430.447273 100 479.326162 516.196162 101 252.736162 479.326162 102 -175.023838 252.736162 103 -168.344949 -175.023838 104 -227.419394 -168.344949 105 -950.187172 -227.419394 106 -1127.677172 -950.187172 > 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/7maxi1229005467.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/83e0j1229005467.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9oe5s1229005467.ps",horizontal=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/10ewes1229005467.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/116b121229005467.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/12c6l11229005467.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/132v191229005467.tab") > > system("convert tmp/1pusy1229005467.ps tmp/1pusy1229005467.png") > system("convert tmp/2zo8g1229005467.ps tmp/2zo8g1229005467.png") > system("convert tmp/31wrc1229005467.ps tmp/31wrc1229005467.png") > system("convert tmp/4sbf31229005467.ps tmp/4sbf31229005467.png") > system("convert tmp/57d6i1229005467.ps tmp/57d6i1229005467.png") > system("convert tmp/6wqu21229005467.ps tmp/6wqu21229005467.png") > system("convert tmp/7maxi1229005467.ps tmp/7maxi1229005467.png") > system("convert tmp/83e0j1229005467.ps tmp/83e0j1229005467.png") > system("convert tmp/9oe5s1229005467.ps tmp/9oe5s1229005467.png") > > > proc.time() user system elapsed 4.232 2.542 4.590