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(2.0 + ,4.5 + ,1000.00 + ,6600.00 + ,42.0 + ,3.00 + ,1.00 + ,3.00 + ,1.8 + ,69.0 + ,2547000.00 + ,4603000.00 + ,624.0 + ,3.00 + ,5.00 + ,4.00 + ,0.7 + ,27.0 + ,10550.00 + ,179500.00 + ,180.0 + ,4.00 + ,4.00 + ,4.00 + ,3.9 + ,19.0 + ,0.023 + ,0.300 + ,35.0 + ,1.00 + ,1.00 + ,1.00 + ,1.0 + ,30.4 + ,160000.00 + ,169000.00 + ,392.0 + ,4.00 + ,5.00 + ,4.00 + ,3.6 + ,28.0 + ,3300.00 + ,25600.00 + ,63.0 + ,1.00 + ,2.00 + ,1.00 + ,1.4 + ,50.0 + ,52160.00 + ,440000.00 + ,230.0 + ,1.00 + ,1.00 + ,1.00 + ,1.5 + ,7.0 + ,0.425 + ,6400.00 + ,112.0 + ,5.00 + ,4.00 + ,4.00 + ,0.7 + ,30.0 + ,465000.00 + ,423000.00 + ,281.0 + ,5.00 + ,5.00 + ,5.00 + ,2.1 + ,3.5 + ,0.075 + ,1200.00 + ,42.0 + ,1.00 + ,1.00 + ,1.00 + ,4.1 + ,6.0 + ,0.785 + ,3500.00 + ,42.0 + ,2.00 + ,2.00 + ,2.00 + ,1.2 + ,10.4 + ,0.200 + ,5000.00 + ,120.0 + ,2.00 + ,2.00 + ,2.00 + ,0.5 + ,20.0 + ,27660.00 + ,115000.00 + ,148.0 + ,5.00 + ,5.00 + ,5.00 + ,3.4 + ,3.9 + ,0.120 + ,1000.00 + ,16.0 + ,3.00 + ,1.00 + ,2.00 + ,1.5 + ,41.0 + ,85000.00 + ,325000.00 + ,310.0 + ,1.00 + ,3.00 + ,1.00 + ,3.4 + ,9.0 + ,0.101 + ,4000.00 + ,28.0 + ,5.00 + ,1.00 + ,3.00 + ,0.8 + ,7.6 + ,1040.00 + ,5500.00 + ,68.0 + ,5.00 + ,3.00 + ,4.00 + ,0.8 + ,46.0 + ,521000.00 + ,655000.00 + ,336.0 + ,5.00 + ,5.00 + ,5.00 + ,2.0 + ,24.0 + ,0.010 + ,0.250 + ,50.0 + ,1.00 + ,1.00 + ,1.00 + ,1.9 + ,100.0 + ,62000.00 + ,1320000.00 + ,267.0 + ,1.00 + ,1.00 + ,1.00 + ,1.3 + ,3.2 + ,.023 + ,0.400 + ,19.0 + ,4.00 + ,1.00 + ,3.00 + ,5.6 + ,5.0 + ,1700.00 + ,6300.00 + ,12.0 + ,2.00 + ,1.00 + ,1.00 + ,3.1 + ,6.5 + ,3500.00 + ,10800.00 + ,120.0 + ,2.00 + ,1.00 + ,1.00 + ,1.8 + ,12.0 + ,0.480 + ,15500.00 + ,140.0 + ,2.00 + ,2.00 + ,2.00 + ,0.9 + ,20.2 + ,10000.00 + ,115000.00 + ,170.0 + ,4.00 + ,4.00 + ,4.00 + ,1.8 + ,13.0 + ,1620.00 + ,11400.00 + ,17.0 + ,2.00 + ,1.00 + ,2.00 + ,1.9 + ,27.0 + ,192000.00 + ,180000.00 + ,115.0 + ,4.00 + ,4.00 + ,4.00 + ,0.9 + ,18.0 + ,2500.00 + ,12100.00 + ,31.0 + ,5.00 + ,5.00 + ,5.00 + ,2.6 + ,4.7 + ,0.280 + ,1900.00 + ,21.0 + ,3.00 + ,1.00 + ,3.00 + ,2.4 + ,9.8 + ,4235.00 + ,50400.00 + ,52.0 + ,1.00 + ,1.00 + ,1.00 + ,1.2 + ,29.0 + ,6800.00 + ,179000.00 + ,164.0 + ,2.00 + ,3.00 + ,2.00 + ,0.9 + ,7.0 + ,0.750 + ,12300.00 + ,225.0 + ,2.00 + ,2.00 + ,2.00 + ,0.5 + ,6.0 + ,3600.00 + ,21000.00 + ,225.0 + ,3.00 + ,2.00 + ,3.00 + ,0.6 + ,20.0 + ,55500.00 + ,175000.00 + ,151.0 + ,5.00 + ,5.00 + ,5.00 + ,2.3 + ,4.5 + ,0.900 + ,2600.00 + ,60.0 + ,2.00 + ,1.00 + ,2.00 + ,0.5 + ,7.5 + ,2000.00 + ,12300.00 + ,200.0 + ,3.00 + ,1.00 + ,3.00 + ,2.6 + ,2.3 + ,0.104 + ,2500.00 + ,46.0 + ,3.00 + ,2.00 + ,2.00 + ,0.6 + ,24.0 + ,4190.00 + ,58000.00 + ,210.0 + ,4.00 + ,3.00 + ,4.00 + ,6.6 + ,3.0 + ,3500.00 + ,3900.00 + ,14.0 + ,2.00 + ,1.00 + ,1.00) + ,dim=c(8 + ,39) + ,dimnames=list(c('SP' + ,'L' + ,'Wb' + ,'Wbr' + ,'Tg' + ,'P' + ,'S' + ,'D') + ,1:39)) > y <- array(NA,dim=c(8,39),dimnames=list(c('SP','L','Wb','Wbr','Tg','P','S','D'),1:39)) > 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 SP L Wb Wbr Tg P S D 1 2.0 4.5 1.000e+03 6.600e+03 42 3 1 3 2 1.8 69.0 2.547e+06 4.603e+06 624 3 5 4 3 0.7 27.0 1.055e+04 1.795e+05 180 4 4 4 4 3.9 19.0 2.300e-02 3.000e-01 35 1 1 1 5 1.0 30.4 1.600e+05 1.690e+05 392 4 5 4 6 3.6 28.0 3.300e+03 2.560e+04 63 1 2 1 7 1.4 50.0 5.216e+04 4.400e+05 230 1 1 1 8 1.5 7.0 4.250e-01 6.400e+03 112 5 4 4 9 0.7 30.0 4.650e+05 4.230e+05 281 5 5 5 10 2.1 3.5 7.500e-02 1.200e+03 42 1 1 1 11 4.1 6.0 7.850e-01 3.500e+03 42 2 2 2 12 1.2 10.4 2.000e-01 5.000e+03 120 2 2 2 13 0.5 20.0 2.766e+04 1.150e+05 148 5 5 5 14 3.4 3.9 1.200e-01 1.000e+03 16 3 1 2 15 1.5 41.0 8.500e+04 3.250e+05 310 1 3 1 16 3.4 9.0 1.010e-01 4.000e+03 28 5 1 3 17 0.8 7.6 1.040e+03 5.500e+03 68 5 3 4 18 0.8 46.0 5.210e+05 6.550e+05 336 5 5 5 19 2.0 24.0 1.000e-02 2.500e-01 50 1 1 1 20 1.9 100.0 6.200e+04 1.320e+06 267 1 1 1 21 1.3 3.2 2.300e-02 4.000e-01 19 4 1 3 22 5.6 5.0 1.700e+03 6.300e+03 12 2 1 1 23 3.1 6.5 3.500e+03 1.080e+04 120 2 1 1 24 1.8 12.0 4.800e-01 1.550e+04 140 2 2 2 25 0.9 20.2 1.000e+04 1.150e+05 170 4 4 4 26 1.8 13.0 1.620e+03 1.140e+04 17 2 1 2 27 1.9 27.0 1.920e+05 1.800e+05 115 4 4 4 28 0.9 18.0 2.500e+03 1.210e+04 31 5 5 5 29 2.6 4.7 2.800e-01 1.900e+03 21 3 1 3 30 2.4 9.8 4.235e+03 5.040e+04 52 1 1 1 31 1.2 29.0 6.800e+03 1.790e+05 164 2 3 2 32 0.9 7.0 7.500e-01 1.230e+04 225 2 2 2 33 0.5 6.0 3.600e+03 2.100e+04 225 3 2 3 34 0.6 20.0 5.550e+04 1.750e+05 151 5 5 5 35 2.3 4.5 9.000e-01 2.600e+03 60 2 1 2 36 0.5 7.5 2.000e+03 1.230e+04 200 3 1 3 37 2.6 2.3 1.040e-01 2.500e+03 46 3 2 2 38 0.6 24.0 4.190e+03 5.800e+04 210 4 3 4 39 6.6 3.0 3.500e+03 3.900e+03 14 2 1 1 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) L Wb Wbr Tg P 3.801e+00 1.163e-02 3.562e-06 -9.877e-07 -7.280e-03 9.041e-01 S D 2.613e-01 -1.675e+00 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -1.25115 -0.53213 0.04849 0.23571 2.46343 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 3.801e+00 3.819e-01 9.952 3.59e-11 *** L 1.163e-02 1.575e-02 0.738 0.465813 Wb 3.562e-06 1.853e-06 1.922 0.063797 . Wbr -9.877e-07 1.112e-06 -0.888 0.381240 Tg -7.280e-03 2.130e-03 -3.418 0.001782 ** P 9.041e-01 3.168e-01 2.854 0.007624 ** S 2.613e-01 2.016e-01 1.296 0.204516 D -1.675e+00 3.869e-01 -4.331 0.000144 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.865 on 31 degrees of freedom Multiple R-squared: 0.6911, Adjusted R-squared: 0.6213 F-statistic: 9.907 on 7 and 31 DF, p-value: 1.953e-06 > 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,] 0.7898815 0.4202371 0.2101185 [2,] 0.7942504 0.4114991 0.2057496 [3,] 0.6974966 0.6050068 0.3025034 [4,] 0.5914139 0.8171722 0.4085861 [5,] 0.4664453 0.9328905 0.5335547 [6,] 0.3539977 0.7079954 0.6460023 [7,] 0.4075017 0.8150033 0.5924983 [8,] 0.3015905 0.6031810 0.6984095 [9,] 0.3086953 0.6173907 0.6913047 [10,] 0.2413223 0.4826446 0.7586777 [11,] 0.4395566 0.8791131 0.5604434 [12,] 0.5493263 0.9013474 0.4506737 [13,] 0.4868740 0.9737480 0.5131260 [14,] 0.3727540 0.7455080 0.6272460 [15,] 0.2675478 0.5350956 0.7324522 [16,] 0.2324642 0.4649284 0.7675358 [17,] 0.2473124 0.4946248 0.7526876 [18,] 0.1530491 0.3060982 0.8469509 > postscript(file="/var/www/html/rcomp/tmp/1kuf81292079711.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/2kuf81292079711.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/3dlxt1292079711.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/4dlxt1292079711.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/5dlxt1292079711.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 39 Frequency = 1 1 2 3 4 5 6 0.50827301 -0.10420851 0.07540419 0.64301162 1.07518606 0.19439062 7 8 9 10 11 12 -0.54903880 -0.42460941 -0.09253081 -0.92459801 1.55862309 -0.82319830 13 14 15 16 17 18 0.10920083 0.04849468 -0.51521407 -0.05325607 -1.19517005 0.25148687 19 20 21 22 23 24 -1.20592749 0.47303597 -1.25114744 1.43439751 -0.29874390 -0.08582873 25 26 27 28 29 30 0.21992781 -0.74140863 0.15630087 -0.33134164 0.95198070 -0.59154618 31 32 33 34 35 36 -0.83286004 -0.31202445 0.06673969 0.19113004 0.16756206 0.12573717 37 38 39 -0.77435040 0.39268753 2.46343264 > postscript(file="/var/www/html/rcomp/tmp/65cev1292079711.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 39 Frequency = 1 lag(myerror, k = 1) myerror 0 0.50827301 NA 1 -0.10420851 0.50827301 2 0.07540419 -0.10420851 3 0.64301162 0.07540419 4 1.07518606 0.64301162 5 0.19439062 1.07518606 6 -0.54903880 0.19439062 7 -0.42460941 -0.54903880 8 -0.09253081 -0.42460941 9 -0.92459801 -0.09253081 10 1.55862309 -0.92459801 11 -0.82319830 1.55862309 12 0.10920083 -0.82319830 13 0.04849468 0.10920083 14 -0.51521407 0.04849468 15 -0.05325607 -0.51521407 16 -1.19517005 -0.05325607 17 0.25148687 -1.19517005 18 -1.20592749 0.25148687 19 0.47303597 -1.20592749 20 -1.25114744 0.47303597 21 1.43439751 -1.25114744 22 -0.29874390 1.43439751 23 -0.08582873 -0.29874390 24 0.21992781 -0.08582873 25 -0.74140863 0.21992781 26 0.15630087 -0.74140863 27 -0.33134164 0.15630087 28 0.95198070 -0.33134164 29 -0.59154618 0.95198070 30 -0.83286004 -0.59154618 31 -0.31202445 -0.83286004 32 0.06673969 -0.31202445 33 0.19113004 0.06673969 34 0.16756206 0.19113004 35 0.12573717 0.16756206 36 -0.77435040 0.12573717 37 0.39268753 -0.77435040 38 2.46343264 0.39268753 39 NA 2.46343264 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -0.10420851 0.50827301 [2,] 0.07540419 -0.10420851 [3,] 0.64301162 0.07540419 [4,] 1.07518606 0.64301162 [5,] 0.19439062 1.07518606 [6,] -0.54903880 0.19439062 [7,] -0.42460941 -0.54903880 [8,] -0.09253081 -0.42460941 [9,] -0.92459801 -0.09253081 [10,] 1.55862309 -0.92459801 [11,] -0.82319830 1.55862309 [12,] 0.10920083 -0.82319830 [13,] 0.04849468 0.10920083 [14,] -0.51521407 0.04849468 [15,] -0.05325607 -0.51521407 [16,] -1.19517005 -0.05325607 [17,] 0.25148687 -1.19517005 [18,] -1.20592749 0.25148687 [19,] 0.47303597 -1.20592749 [20,] -1.25114744 0.47303597 [21,] 1.43439751 -1.25114744 [22,] -0.29874390 1.43439751 [23,] -0.08582873 -0.29874390 [24,] 0.21992781 -0.08582873 [25,] -0.74140863 0.21992781 [26,] 0.15630087 -0.74140863 [27,] -0.33134164 0.15630087 [28,] 0.95198070 -0.33134164 [29,] -0.59154618 0.95198070 [30,] -0.83286004 -0.59154618 [31,] -0.31202445 -0.83286004 [32,] 0.06673969 -0.31202445 [33,] 0.19113004 0.06673969 [34,] 0.16756206 0.19113004 [35,] 0.12573717 0.16756206 [36,] -0.77435040 0.12573717 [37,] 0.39268753 -0.77435040 [38,] 2.46343264 0.39268753 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -0.10420851 0.50827301 2 0.07540419 -0.10420851 3 0.64301162 0.07540419 4 1.07518606 0.64301162 5 0.19439062 1.07518606 6 -0.54903880 0.19439062 7 -0.42460941 -0.54903880 8 -0.09253081 -0.42460941 9 -0.92459801 -0.09253081 10 1.55862309 -0.92459801 11 -0.82319830 1.55862309 12 0.10920083 -0.82319830 13 0.04849468 0.10920083 14 -0.51521407 0.04849468 15 -0.05325607 -0.51521407 16 -1.19517005 -0.05325607 17 0.25148687 -1.19517005 18 -1.20592749 0.25148687 19 0.47303597 -1.20592749 20 -1.25114744 0.47303597 21 1.43439751 -1.25114744 22 -0.29874390 1.43439751 23 -0.08582873 -0.29874390 24 0.21992781 -0.08582873 25 -0.74140863 0.21992781 26 0.15630087 -0.74140863 27 -0.33134164 0.15630087 28 0.95198070 -0.33134164 29 -0.59154618 0.95198070 30 -0.83286004 -0.59154618 31 -0.31202445 -0.83286004 32 0.06673969 -0.31202445 33 0.19113004 0.06673969 34 0.16756206 0.19113004 35 0.12573717 0.16756206 36 -0.77435040 0.12573717 37 0.39268753 -0.77435040 38 2.46343264 0.39268753 > 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/7ylvh1292079711.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/8ylvh1292079711.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/rcomp/tmp/9ylvh1292079711.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') Warning messages: 1: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced 2: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/rcomp/tmp/10rdu21292079711.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11vdbq1292079711.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/12gesd1292079711.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/13u5741292079711.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/14fooa1292079711.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/151o4g1292079711.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/16mpl41292079711.tab") + } > > try(system("convert tmp/1kuf81292079711.ps tmp/1kuf81292079711.png",intern=TRUE)) character(0) > try(system("convert tmp/2kuf81292079711.ps tmp/2kuf81292079711.png",intern=TRUE)) character(0) > try(system("convert tmp/3dlxt1292079711.ps tmp/3dlxt1292079711.png",intern=TRUE)) character(0) > try(system("convert tmp/4dlxt1292079711.ps tmp/4dlxt1292079711.png",intern=TRUE)) character(0) > try(system("convert tmp/5dlxt1292079711.ps tmp/5dlxt1292079711.png",intern=TRUE)) character(0) > try(system("convert tmp/65cev1292079711.ps tmp/65cev1292079711.png",intern=TRUE)) character(0) > try(system("convert tmp/7ylvh1292079711.ps tmp/7ylvh1292079711.png",intern=TRUE)) character(0) > try(system("convert tmp/8ylvh1292079711.ps tmp/8ylvh1292079711.png",intern=TRUE)) character(0) > try(system("convert tmp/9ylvh1292079711.ps tmp/9ylvh1292079711.png",intern=TRUE)) character(0) > try(system("convert tmp/10rdu21292079711.ps tmp/10rdu21292079711.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.278 1.645 7.254