R version 2.15.2 (2012-10-26) -- "Trick or Treat" Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i686-pc-linux-gnu (32-bit) 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(2.45 + ,2.44 + ,2.46 + ,2.45 + ,2.45 + ,2.43 + ,2.42 + ,2.43 + ,2.46 + ,2.47 + ,2.48 + ,2.49 + ,0.55 + ,0.55 + ,0.55 + ,0.55 + ,0.56 + ,0.55 + ,0.55 + ,0.56 + ,0.55 + ,0.56 + ,0.56 + ,0.56 + ,1.41 + ,1.37 + ,1.4 + ,1.38 + ,1.44 + ,1.43 + ,1.45 + ,1.47 + ,1.47 + ,1.44 + ,1.45 + ,1.45 + ,1.1 + ,1.1 + ,1.1 + ,1.09 + ,1.09 + ,1.08 + ,1.08 + ,1.08 + ,1.08 + ,1.08 + ,1.08 + ,1.06 + ,1.65 + ,1.65 + ,1.64 + ,1.64 + ,1.64 + ,1.63 + ,1.63 + ,1.63 + ,1.63 + ,1.63 + ,1.62 + ,1.61 + ,1.65 + ,1.65 + ,1.65 + ,1.65 + ,1.64 + ,1.64 + ,1.64 + ,1.64 + ,1.64 + ,1.63 + ,1.63 + ,1.62 + ,4.15 + ,4.14 + ,4.13 + ,4.13 + ,4.12 + ,4.11 + ,4.11 + ,4.1 + ,4.1 + ,4.1 + ,4.08 + ,4.06 + ,5.64 + ,5.64 + ,5.63 + ,5.61 + ,5.59 + ,5.58 + ,5.58 + ,5.57 + ,5.56 + ,5.55 + ,5.51 + ,5.44 + ,6.64 + ,6.61 + ,6.63 + ,6.62 + ,6.59 + ,6.57 + ,6.52 + ,6.51 + ,6.51 + ,6.48 + ,6.49 + ,6.47 + ,1.6 + ,1.6 + ,1.6 + ,1.59 + ,1.58 + ,1.58 + ,1.58 + ,1.57 + ,1.58 + ,1.57 + ,1.57 + ,1.56 + ,0.98 + ,0.98 + ,0.98 + ,0.98 + ,0.97 + ,0.97 + ,0.97 + ,0.97 + ,0.97 + ,0.97 + ,0.97 + ,0.96 + ,1.03 + ,1.03 + ,1.02 + ,1.02 + ,1.02 + ,1.02 + ,1.02 + ,1.03 + ,1.03 + ,1.02 + ,1.02 + ,1.02 + ,4.72 + ,4.6 + ,4.62 + ,4.63 + ,4.65 + ,4.61 + ,4.65 + ,4.59 + ,4.65 + ,4.65 + ,4.63 + ,4.48 + ,3.17 + ,3.16 + ,3.16 + ,3.15 + ,3.19 + ,3.2 + ,3.2 + ,3.2 + ,3.22 + ,3.21 + ,3.2 + ,3.15 + ,7.3 + ,7.29 + ,7.27 + ,7.26 + ,7.2 + ,7.19 + ,7.18 + ,7.15 + ,7.14 + ,7.12 + ,7.11 + ,7.08 + ,3.25 + ,3.23 + ,3.23 + ,3.25 + ,3.25 + ,3.27 + ,3.27 + ,3.29 + ,3.27 + ,3.28 + ,3.29 + ,3.24 + ,0.65 + ,0.65 + ,0.65 + ,0.65 + ,0.65 + ,0.65 + ,0.66 + ,0.65 + ,0.66 + ,0.65 + ,0.65 + ,0.65 + ,4.1 + ,4.1 + ,4.11 + ,4.12 + ,4.15 + ,4.13 + ,4.12 + ,4.12 + ,4.18 + ,4.19 + ,4.2 + ,4.19 + ,6.58 + ,6.57 + ,6.56 + ,6.43 + ,6.45 + ,6.41 + ,6.33 + ,6.39 + ,6.39 + ,6.39 + ,6.39 + ,6.4 + ,15.21 + ,15.19 + ,15.17 + ,15.19 + ,15.18 + ,15.15 + ,15.2 + ,15.06 + ,14.97 + ,15.13 + ,15.05 + ,15.16 + ,10.99 + ,11 + ,10.9 + ,10.99 + ,11.04 + ,11.03 + ,10.99 + ,11 + ,10.87 + ,10.88 + ,10.91 + ,10.92 + ,8.19 + ,8.3 + ,8.18 + ,8.24 + ,8.3 + ,8.34 + ,8.3 + ,8.27 + ,8.22 + ,8.22 + ,8.22 + ,8.12 + ,5.89 + ,5.88 + ,5.89 + ,5.91 + ,5.89 + ,5.87 + ,5.87 + ,5.84 + ,5.83 + ,5.83 + ,5.83 + ,5.8 + ,15 + ,15.18 + ,15.18 + ,15.18 + ,15.05 + ,15 + ,15.13 + ,15.08 + ,14.98 + ,15.1 + ,14.95 + ,15.12) + ,dim=c(12 + ,24) + ,dimnames=list(c('2005/12' + ,'2005/11' + ,'2005/10' + ,'2005/09' + ,'2005/08' + ,'2005/07' + ,'2005/06' + ,'2005/05' + ,'2005/04' + ,'2005/03' + ,'2005/02' + ,'2005/01') + ,1:24)) > y <- array(NA,dim=c(12,24),dimnames=list(c('2005/12','2005/11','2005/10','2005/09','2005/08','2005/07','2005/06','2005/05','2005/04','2005/03','2005/02','2005/01'),1:24)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '1' > par3 <- 'Linear Trend' > par2 <- 'Do not include Seasonal Dummies' > par1 <- '1' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from 'package:base': as.Date, 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 2005/12 2005/11 2005/10 2005/09 2005/08 2005/07 2005/06 2005/05 2005/04 1 2.45 2.44 2.46 2.45 2.45 2.43 2.42 2.43 2.46 2 0.55 0.55 0.55 0.55 0.56 0.55 0.55 0.56 0.55 3 1.41 1.37 1.40 1.38 1.44 1.43 1.45 1.47 1.47 4 1.10 1.10 1.10 1.09 1.09 1.08 1.08 1.08 1.08 5 1.65 1.65 1.64 1.64 1.64 1.63 1.63 1.63 1.63 6 1.65 1.65 1.65 1.65 1.64 1.64 1.64 1.64 1.64 7 4.15 4.14 4.13 4.13 4.12 4.11 4.11 4.10 4.10 8 5.64 5.64 5.63 5.61 5.59 5.58 5.58 5.57 5.56 9 6.64 6.61 6.63 6.62 6.59 6.57 6.52 6.51 6.51 10 1.60 1.60 1.60 1.59 1.58 1.58 1.58 1.57 1.58 11 0.98 0.98 0.98 0.98 0.97 0.97 0.97 0.97 0.97 12 1.03 1.03 1.02 1.02 1.02 1.02 1.02 1.03 1.03 13 4.72 4.60 4.62 4.63 4.65 4.61 4.65 4.59 4.65 14 3.17 3.16 3.16 3.15 3.19 3.20 3.20 3.20 3.22 15 7.30 7.29 7.27 7.26 7.20 7.19 7.18 7.15 7.14 16 3.25 3.23 3.23 3.25 3.25 3.27 3.27 3.29 3.27 17 0.65 0.65 0.65 0.65 0.65 0.65 0.66 0.65 0.66 18 4.10 4.10 4.11 4.12 4.15 4.13 4.12 4.12 4.18 19 6.58 6.57 6.56 6.43 6.45 6.41 6.33 6.39 6.39 20 15.21 15.19 15.17 15.19 15.18 15.15 15.20 15.06 14.97 21 10.99 11.00 10.90 10.99 11.04 11.03 10.99 11.00 10.87 22 8.19 8.30 8.18 8.24 8.30 8.34 8.30 8.27 8.22 23 5.89 5.88 5.89 5.91 5.89 5.87 5.87 5.84 5.83 24 15.00 15.18 15.18 15.18 15.05 15.00 15.13 15.08 14.98 2005/03 2005/02 2005/01 t 1 2.47 2.48 2.49 1 2 0.56 0.56 0.56 2 3 1.44 1.45 1.45 3 4 1.08 1.08 1.06 4 5 1.63 1.62 1.61 5 6 1.63 1.63 1.62 6 7 4.10 4.08 4.06 7 8 5.55 5.51 5.44 8 9 6.48 6.49 6.47 9 10 1.57 1.57 1.56 10 11 0.97 0.97 0.96 11 12 1.02 1.02 1.02 12 13 4.65 4.63 4.48 13 14 3.21 3.20 3.15 14 15 7.12 7.11 7.08 15 16 3.28 3.29 3.24 16 17 0.65 0.65 0.65 17 18 4.19 4.20 4.19 18 19 6.39 6.39 6.40 19 20 15.13 15.05 15.16 20 21 10.88 10.91 10.92 21 22 8.22 8.22 8.12 22 23 5.83 5.83 5.80 23 24 15.10 14.95 15.12 24 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) `2005/11` `2005/10` `2005/09` `2005/08` `2005/07` 0.0047289 0.1299333 1.3813444 -0.6893953 1.0657528 -1.1150220 `2005/06` `2005/05` `2005/04` `2005/03` `2005/02` `2005/01` 0.9806615 -0.1074636 -0.9610608 -1.1981282 2.0985233 -0.5864878 t -0.0006417 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -0.034116 -0.012283 0.001512 0.011578 0.027850 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.0047289 0.0122928 0.385 0.7078 `2005/11` 0.1299333 0.4300361 0.302 0.7682 `2005/10` 1.3813444 0.3827263 3.609 0.0041 ** `2005/09` -0.6893953 0.3633953 -1.897 0.0844 . `2005/08` 1.0657528 0.5808556 1.835 0.0937 . `2005/07` -1.1150220 0.6344992 -1.757 0.1066 `2005/06` 0.9806615 0.6264250 1.565 0.1458 `2005/05` -0.1074636 0.3751970 -0.286 0.7799 `2005/04` -0.9610608 0.4706693 -2.042 0.0659 . `2005/03` -1.1981282 0.7373641 -1.625 0.1325 `2005/02` 2.0985233 0.8199424 2.559 0.0265 * `2005/01` -0.5864878 0.1940418 -3.022 0.0116 * t -0.0006417 0.0011731 -0.547 0.5953 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.02427 on 11 degrees of freedom Multiple R-squared: 1, Adjusted R-squared: 1 F-statistic: 5.77e+04 on 12 and 11 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 + } > postscript(file="/var/fisher/rcomp/tmp/1xg4o1353445036.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/2q8gt1353445036.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/3ffat1353445036.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/43vn31353445036.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/501o71353445036.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 = 24 Frequency = 1 1 2 3 4 5 -0.0142652686 -0.0154291931 -0.0119068535 -0.0264312728 0.0097474194 6 7 8 9 10 0.0003780975 0.0278504926 0.0096050282 -0.0087341721 -0.0033231623 11 12 13 14 15 -0.0004520327 0.0237263778 0.0052231176 0.0170673079 0.0156018435 16 17 18 19 20 0.0124713629 0.0068561324 0.0026467202 -0.0015398180 0.0112803940 21 22 23 24 0.0186154942 -0.0341163205 -0.0314604424 -0.0134112523 > postscript(file="/var/fisher/rcomp/tmp/6739c1353445036.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 = 24 Frequency = 1 lag(myerror, k = 1) myerror 0 -0.0142652686 NA 1 -0.0154291931 -0.0142652686 2 -0.0119068535 -0.0154291931 3 -0.0264312728 -0.0119068535 4 0.0097474194 -0.0264312728 5 0.0003780975 0.0097474194 6 0.0278504926 0.0003780975 7 0.0096050282 0.0278504926 8 -0.0087341721 0.0096050282 9 -0.0033231623 -0.0087341721 10 -0.0004520327 -0.0033231623 11 0.0237263778 -0.0004520327 12 0.0052231176 0.0237263778 13 0.0170673079 0.0052231176 14 0.0156018435 0.0170673079 15 0.0124713629 0.0156018435 16 0.0068561324 0.0124713629 17 0.0026467202 0.0068561324 18 -0.0015398180 0.0026467202 19 0.0112803940 -0.0015398180 20 0.0186154942 0.0112803940 21 -0.0341163205 0.0186154942 22 -0.0314604424 -0.0341163205 23 -0.0134112523 -0.0314604424 24 NA -0.0134112523 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -0.0154291931 -0.0142652686 [2,] -0.0119068535 -0.0154291931 [3,] -0.0264312728 -0.0119068535 [4,] 0.0097474194 -0.0264312728 [5,] 0.0003780975 0.0097474194 [6,] 0.0278504926 0.0003780975 [7,] 0.0096050282 0.0278504926 [8,] -0.0087341721 0.0096050282 [9,] -0.0033231623 -0.0087341721 [10,] -0.0004520327 -0.0033231623 [11,] 0.0237263778 -0.0004520327 [12,] 0.0052231176 0.0237263778 [13,] 0.0170673079 0.0052231176 [14,] 0.0156018435 0.0170673079 [15,] 0.0124713629 0.0156018435 [16,] 0.0068561324 0.0124713629 [17,] 0.0026467202 0.0068561324 [18,] -0.0015398180 0.0026467202 [19,] 0.0112803940 -0.0015398180 [20,] 0.0186154942 0.0112803940 [21,] -0.0341163205 0.0186154942 [22,] -0.0314604424 -0.0341163205 [23,] -0.0134112523 -0.0314604424 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -0.0154291931 -0.0142652686 2 -0.0119068535 -0.0154291931 3 -0.0264312728 -0.0119068535 4 0.0097474194 -0.0264312728 5 0.0003780975 0.0097474194 6 0.0278504926 0.0003780975 7 0.0096050282 0.0278504926 8 -0.0087341721 0.0096050282 9 -0.0033231623 -0.0087341721 10 -0.0004520327 -0.0033231623 11 0.0237263778 -0.0004520327 12 0.0052231176 0.0237263778 13 0.0170673079 0.0052231176 14 0.0156018435 0.0170673079 15 0.0124713629 0.0156018435 16 0.0068561324 0.0124713629 17 0.0026467202 0.0068561324 18 -0.0015398180 0.0026467202 19 0.0112803940 -0.0015398180 20 0.0186154942 0.0112803940 21 -0.0341163205 0.0186154942 22 -0.0314604424 -0.0341163205 23 -0.0134112523 -0.0314604424 > 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/fisher/rcomp/tmp/7ve7k1353445036.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/8rtv31353445036.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/92wtu1353445036.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') Warning messages: 1: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced 2: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/fisher/rcomp/tmp/108k861353445036.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } > > #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/fisher/rcomp/tmp/11nvl71353445036.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/fisher/rcomp/tmp/12n49v1353445036.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/fisher/rcomp/tmp/13m99v1353445036.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/fisher/rcomp/tmp/14m2d51353445036.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/fisher/rcomp/tmp/15br2h1353445036.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/fisher/rcomp/tmp/16qm6z1353445036.tab") + } > > try(system("convert tmp/1xg4o1353445036.ps tmp/1xg4o1353445036.png",intern=TRUE)) character(0) > try(system("convert tmp/2q8gt1353445036.ps tmp/2q8gt1353445036.png",intern=TRUE)) character(0) > try(system("convert tmp/3ffat1353445036.ps tmp/3ffat1353445036.png",intern=TRUE)) character(0) > try(system("convert tmp/43vn31353445036.ps tmp/43vn31353445036.png",intern=TRUE)) character(0) > try(system("convert tmp/501o71353445036.ps tmp/501o71353445036.png",intern=TRUE)) character(0) > try(system("convert tmp/6739c1353445036.ps tmp/6739c1353445036.png",intern=TRUE)) character(0) > try(system("convert tmp/7ve7k1353445036.ps tmp/7ve7k1353445036.png",intern=TRUE)) character(0) > try(system("convert tmp/8rtv31353445036.ps tmp/8rtv31353445036.png",intern=TRUE)) character(0) > try(system("convert tmp/92wtu1353445036.ps tmp/92wtu1353445036.png",intern=TRUE)) character(0) > try(system("convert tmp/108k861353445036.ps tmp/108k861353445036.png",intern=TRUE)) convert: unable to open image `tmp/108k861353445036.ps': @ error/blob.c/OpenBlob/2587. convert: missing an image filename `tmp/108k861353445036.png' @ error/convert.c/ConvertImageCommand/3011. character(0) attr(,"status") [1] 1 Warning message: running command 'convert tmp/108k861353445036.ps tmp/108k861353445036.png' had status 1 > > > proc.time() user system elapsed 5.277 1.215 6.489