R version 2.8.0 (2008-10-20) Copyright (C) 2008 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. Natural language support but running in an English locale 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(6.3 + ,2.0 + ,4.5 + ,1.000 + ,6.600 + ,42.0 + ,3 + ,1 + ,3 + ,2.1 + ,1.8 + ,69.0 + ,2547.000 + ,44.500 + ,624.0 + ,3 + ,5 + ,4 + ,9.1 + ,0.7 + ,27.0 + ,10.55 + ,179.500 + ,180.0 + ,4 + ,4 + ,4 + ,15.8 + ,3.9 + ,19.0 + ,0.023 + ,0.300 + ,35.0 + ,1 + ,1 + ,1 + ,5.2 + ,1.0 + ,30.4 + ,160.000 + ,169.000 + ,392.0 + ,4 + ,5 + ,4 + ,10.9 + ,3.6 + ,28.0 + ,3.300 + ,25.600 + ,63.0 + ,1 + ,2 + ,1 + ,8.3 + ,1.4 + ,50.0 + ,52.16 + ,440.000 + ,230.0 + ,1 + ,1 + ,1 + ,11.0 + ,1.5 + ,7.0 + ,0.425 + ,6.400 + ,112.0 + ,5 + ,4 + ,4 + ,3.2 + ,0.7 + ,30.0 + ,465.000 + ,423.000 + ,281.0 + ,5 + ,5 + ,5 + ,6.3 + ,2.1 + ,3.5 + ,0.075 + ,1.200 + ,42.0 + ,1 + ,1 + ,1 + ,6.6 + ,4.1 + ,6.0 + ,0.785 + ,3.500 + ,42.0 + ,2 + ,2 + ,2 + ,9.5 + ,1.2 + ,10.4 + ,0.200 + ,5.000 + ,120.0 + ,2 + ,2 + ,2 + ,3.3 + ,0.5 + ,20.0 + ,27.66 + ,115.000 + ,148.0 + ,5 + ,5 + ,5 + ,11.0 + ,3.4 + ,3.9 + ,0.120 + ,1.000 + ,16.0 + ,3 + ,1 + ,2 + ,4.7 + ,1.5 + ,41.0 + ,85.000 + ,325.000 + ,310.0 + ,1 + ,3 + ,1 + ,10.4 + ,3.4 + ,9.0 + ,0.101 + ,4.000 + ,28.0 + ,5 + ,1 + ,3 + ,7.4 + ,0.8 + ,7.6 + ,1.040 + ,5.500 + ,68.0 + ,5 + ,3 + ,4 + ,2.1 + ,0.8 + ,46.0 + ,521.000 + ,655.000 + ,336.0 + ,5 + ,5 + ,5 + ,17.9 + ,2.0 + ,24.0 + ,0.010 + ,0.250 + ,50.0 + ,1 + ,1 + ,1 + ,6.1 + ,1.9 + ,100.0 + ,62.000 + ,1320.000 + ,267.0 + ,1 + ,1 + ,1 + ,11.9 + ,1.3 + ,3.2 + ,0.023 + ,0.400 + ,19.0 + ,4 + ,1 + ,3 + ,13.8 + ,5.6 + ,5.0 + ,1.700 + ,6.300 + ,12.0 + ,2 + ,1 + ,1 + ,14.3 + ,3.1 + ,6.5 + ,3.500 + ,10.800 + ,120.0 + ,2 + ,1 + ,1 + ,15.2 + ,1.8 + ,12.0 + ,0.480 + ,15.500 + ,140.0 + ,2 + ,2 + ,2 + ,10.0 + ,0.9 + ,20.2 + ,10.000 + ,115.000 + ,170.0 + ,4 + ,4 + ,4 + ,11.9 + ,1.8 + ,13.0 + ,1.620 + ,11.400 + ,17.0 + ,2 + ,1 + ,2 + ,6.5 + ,1.9 + ,27.0 + ,192.000 + ,180.000 + ,115.0 + ,4 + ,4 + ,4 + ,7.5 + ,0.9 + ,18.0 + ,2.500 + ,12.300 + ,31.0 + ,5 + ,5 + ,5 + ,10.6 + ,2.6 + ,4.7 + ,0.280 + ,1.900 + ,21.0 + ,3 + ,1 + ,3 + ,7.4 + ,2.4 + ,9.8 + ,4.235 + ,50.400 + ,52.0 + ,1 + ,1 + ,1 + ,8.4 + ,1.2 + ,29.0 + ,6.800 + ,179.000 + ,164.0 + ,2 + ,3 + ,2 + ,5.7 + ,0.9 + ,7.0 + ,0.750 + ,12.300 + ,225.0 + ,2 + ,2 + ,2 + ,4.9 + ,0.5 + ,6.0 + ,3.600 + ,21.000 + ,225.0 + ,3 + ,2 + ,3 + ,3.2 + ,0.6 + ,20.0 + ,55.500 + ,175.000 + ,151.0 + ,5 + ,5 + ,5 + ,11.0 + ,2.3 + ,4.5 + ,0.900 + ,2.600 + ,60.0 + ,2 + ,1 + ,2 + ,4.9 + ,0.5 + ,7.5 + ,2.000 + ,12.300 + ,200.0 + ,3 + ,1 + ,3 + ,13.2 + ,2.6 + ,2.3 + ,0.104 + ,2.500 + ,46.0 + ,3 + ,2 + ,2 + ,9.7 + ,0.6 + ,24.0 + ,4.190 + ,58.000 + ,210.0 + ,4 + ,3 + ,4 + ,12.8 + ,6.6 + ,3.0 + ,3.500 + ,3.900 + ,14.0 + ,2 + ,1 + ,1) + ,dim=c(9 + ,39) + ,dimnames=list(c('SWS' + ,'PS' + ,'L' + ,'Wb' + ,'Wbr' + ,'Tg' + ,'P' + ,'S' + ,'D') + ,1:39)) > y <- array(NA,dim=c(9,39),dimnames=list(c('SWS','PS','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 = '2' > #'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 PS SWS L Wb Wbr Tg P S D 1 2.0 6.3 4.5 1.000 6.60 42 3 1 3 2 1.8 2.1 69.0 2547.000 44.50 624 3 5 4 3 0.7 9.1 27.0 10.550 179.50 180 4 4 4 4 3.9 15.8 19.0 0.023 0.30 35 1 1 1 5 1.0 5.2 30.4 160.000 169.00 392 4 5 4 6 3.6 10.9 28.0 3.300 25.60 63 1 2 1 7 1.4 8.3 50.0 52.160 440.00 230 1 1 1 8 1.5 11.0 7.0 0.425 6.40 112 5 4 4 9 0.7 3.2 30.0 465.000 423.00 281 5 5 5 10 2.1 6.3 3.5 0.075 1.20 42 1 1 1 11 4.1 6.6 6.0 0.785 3.50 42 2 2 2 12 1.2 9.5 10.4 0.200 5.00 120 2 2 2 13 0.5 3.3 20.0 27.660 115.00 148 5 5 5 14 3.4 11.0 3.9 0.120 1.00 16 3 1 2 15 1.5 4.7 41.0 85.000 325.00 310 1 3 1 16 3.4 10.4 9.0 0.101 4.00 28 5 1 3 17 0.8 7.4 7.6 1.040 5.50 68 5 3 4 18 0.8 2.1 46.0 521.000 655.00 336 5 5 5 19 2.0 17.9 24.0 0.010 0.25 50 1 1 1 20 1.9 6.1 100.0 62.000 1320.00 267 1 1 1 21 1.3 11.9 3.2 0.023 0.40 19 4 1 3 22 5.6 13.8 5.0 1.700 6.30 12 2 1 1 23 3.1 14.3 6.5 3.500 10.80 120 2 1 1 24 1.8 15.2 12.0 0.480 15.50 140 2 2 2 25 0.9 10.0 20.2 10.000 115.00 170 4 4 4 26 1.8 11.9 13.0 1.620 11.40 17 2 1 2 27 1.9 6.5 27.0 192.000 180.00 115 4 4 4 28 0.9 7.5 18.0 2.500 12.30 31 5 5 5 29 2.6 10.6 4.7 0.280 1.90 21 3 1 3 30 2.4 7.4 9.8 4.235 50.40 52 1 1 1 31 1.2 8.4 29.0 6.800 179.00 164 2 3 2 32 0.9 5.7 7.0 0.750 12.30 225 2 2 2 33 0.5 4.9 6.0 3.600 21.00 225 3 2 3 34 0.6 3.2 20.0 55.500 175.00 151 5 5 5 35 2.3 11.0 4.5 0.900 2.60 60 2 1 2 36 0.5 4.9 7.5 2.000 12.30 200 3 1 3 37 2.6 13.2 2.3 0.104 2.50 46 3 2 2 38 0.6 9.7 24.0 4.190 58.00 210 4 3 4 39 6.6 12.8 3.0 3.500 3.90 14 2 1 1 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) SWS L Wb Wbr Tg 3.879814 0.020766 -0.023114 0.002442 0.001835 -0.007289 P S D 0.753428 0.379291 -1.584598 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -1.254479 -0.502961 0.009168 0.335994 2.308514 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 3.8798141 0.8054389 4.817 3.90e-05 *** SWS 0.0207658 0.0592489 0.350 0.728425 L -0.0231143 0.0242532 -0.953 0.348187 Wb 0.0024421 0.0006486 3.765 0.000725 *** Wbr 0.0018346 0.0016760 1.095 0.282384 Tg -0.0072885 0.0023016 -3.167 0.003528 ** P 0.7534277 0.3532113 2.133 0.041215 * S 0.3792914 0.1984211 1.912 0.065529 . D -1.5845975 0.4268905 -3.712 0.000837 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.8727 on 30 degrees of freedom Multiple R-squared: 0.6957, Adjusted R-squared: 0.6145 F-statistic: 8.572 on 8 and 30 DF, p-value: 5.313e-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,] 0.8491300 0.3017400 0.1508700 [2,] 0.7845484 0.4309033 0.2154516 [3,] 0.6939939 0.6120121 0.3060061 [4,] 0.5601247 0.8797506 0.4398753 [5,] 0.4455383 0.8910766 0.5544617 [6,] 0.4936165 0.9872330 0.5063835 [7,] 0.4018405 0.8036810 0.5981595 [8,] 0.3718248 0.7436496 0.6281752 [9,] 0.2634628 0.5269255 0.7365372 [10,] 0.4381427 0.8762854 0.5618573 [11,] 0.5050118 0.9899763 0.4949882 [12,] 0.4396966 0.8793932 0.5603034 [13,] 0.3140357 0.6280715 0.6859643 [14,] 0.2170890 0.4341781 0.7829110 [15,] 0.1720083 0.3440166 0.8279917 [16,] 0.1631114 0.3262228 0.8368886 > postscript(file="/var/www/html/freestat/rcomp/tmp/17asd1292249266.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/2iksg1292249266.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/freestat/rcomp/tmp/3iksg1292249266.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/4iksg1292249266.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/5ab9j1292249266.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 0.499160814 -0.100417161 0.019673723 0.837627151 1.299419782 0.617776746 7 8 9 10 11 12 -0.302822854 -0.588817781 -0.156965311 -1.074127347 1.423353558 -0.867983845 13 14 15 16 17 18 0.073509656 0.026017001 -0.380814249 0.316106043 -1.141446289 0.174190874 19 20 21 22 23 24 -0.880958573 0.029771699 -1.254479182 1.319392773 -0.381810815 -0.223542849 25 26 27 28 29 30 0.090597299 -0.644359224 0.355882831 -0.262835509 0.871812929 -0.678886070 31 32 33 34 35 36 -0.809151176 -0.417104239 -0.015356921 0.019388895 0.009167622 0.236261339 37 38 39 -1.019999368 0.674253615 2.308514414 > postscript(file="/var/www/html/freestat/rcomp/tmp/6ab9j1292249266.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 0.499160814 NA 1 -0.100417161 0.499160814 2 0.019673723 -0.100417161 3 0.837627151 0.019673723 4 1.299419782 0.837627151 5 0.617776746 1.299419782 6 -0.302822854 0.617776746 7 -0.588817781 -0.302822854 8 -0.156965311 -0.588817781 9 -1.074127347 -0.156965311 10 1.423353558 -1.074127347 11 -0.867983845 1.423353558 12 0.073509656 -0.867983845 13 0.026017001 0.073509656 14 -0.380814249 0.026017001 15 0.316106043 -0.380814249 16 -1.141446289 0.316106043 17 0.174190874 -1.141446289 18 -0.880958573 0.174190874 19 0.029771699 -0.880958573 20 -1.254479182 0.029771699 21 1.319392773 -1.254479182 22 -0.381810815 1.319392773 23 -0.223542849 -0.381810815 24 0.090597299 -0.223542849 25 -0.644359224 0.090597299 26 0.355882831 -0.644359224 27 -0.262835509 0.355882831 28 0.871812929 -0.262835509 29 -0.678886070 0.871812929 30 -0.809151176 -0.678886070 31 -0.417104239 -0.809151176 32 -0.015356921 -0.417104239 33 0.019388895 -0.015356921 34 0.009167622 0.019388895 35 0.236261339 0.009167622 36 -1.019999368 0.236261339 37 0.674253615 -1.019999368 38 2.308514414 0.674253615 39 NA 2.308514414 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -0.100417161 0.499160814 [2,] 0.019673723 -0.100417161 [3,] 0.837627151 0.019673723 [4,] 1.299419782 0.837627151 [5,] 0.617776746 1.299419782 [6,] -0.302822854 0.617776746 [7,] -0.588817781 -0.302822854 [8,] -0.156965311 -0.588817781 [9,] -1.074127347 -0.156965311 [10,] 1.423353558 -1.074127347 [11,] -0.867983845 1.423353558 [12,] 0.073509656 -0.867983845 [13,] 0.026017001 0.073509656 [14,] -0.380814249 0.026017001 [15,] 0.316106043 -0.380814249 [16,] -1.141446289 0.316106043 [17,] 0.174190874 -1.141446289 [18,] -0.880958573 0.174190874 [19,] 0.029771699 -0.880958573 [20,] -1.254479182 0.029771699 [21,] 1.319392773 -1.254479182 [22,] -0.381810815 1.319392773 [23,] -0.223542849 -0.381810815 [24,] 0.090597299 -0.223542849 [25,] -0.644359224 0.090597299 [26,] 0.355882831 -0.644359224 [27,] -0.262835509 0.355882831 [28,] 0.871812929 -0.262835509 [29,] -0.678886070 0.871812929 [30,] -0.809151176 -0.678886070 [31,] -0.417104239 -0.809151176 [32,] -0.015356921 -0.417104239 [33,] 0.019388895 -0.015356921 [34,] 0.009167622 0.019388895 [35,] 0.236261339 0.009167622 [36,] -1.019999368 0.236261339 [37,] 0.674253615 -1.019999368 [38,] 2.308514414 0.674253615 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -0.100417161 0.499160814 2 0.019673723 -0.100417161 3 0.837627151 0.019673723 4 1.299419782 0.837627151 5 0.617776746 1.299419782 6 -0.302822854 0.617776746 7 -0.588817781 -0.302822854 8 -0.156965311 -0.588817781 9 -1.074127347 -0.156965311 10 1.423353558 -1.074127347 11 -0.867983845 1.423353558 12 0.073509656 -0.867983845 13 0.026017001 0.073509656 14 -0.380814249 0.026017001 15 0.316106043 -0.380814249 16 -1.141446289 0.316106043 17 0.174190874 -1.141446289 18 -0.880958573 0.174190874 19 0.029771699 -0.880958573 20 -1.254479182 0.029771699 21 1.319392773 -1.254479182 22 -0.381810815 1.319392773 23 -0.223542849 -0.381810815 24 0.090597299 -0.223542849 25 -0.644359224 0.090597299 26 0.355882831 -0.644359224 27 -0.262835509 0.355882831 28 0.871812929 -0.262835509 29 -0.678886070 0.871812929 30 -0.809151176 -0.678886070 31 -0.417104239 -0.809151176 32 -0.015356921 -0.417104239 33 0.019388895 -0.015356921 34 0.009167622 0.019388895 35 0.236261339 0.009167622 36 -1.019999368 0.236261339 37 0.674253615 -1.019999368 38 2.308514414 0.674253615 > 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/7l2841292249266.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/8l2841292249266.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/9eb871292249266.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') Warning messages: 1: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced 2: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/freestat/rcomp/tmp/10eb871292249266.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/11hc6d1292249266.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/122c4j1292249266.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/139dju1292249266.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/14cwi01292249266.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/freestat/rcomp/tmp/15n5hl1292249266.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/freestat/rcomp/tmp/161ffu1292249266.tab") + } > > try(system("convert tmp/17asd1292249266.ps tmp/17asd1292249266.png",intern=TRUE)) character(0) > try(system("convert tmp/2iksg1292249266.ps tmp/2iksg1292249266.png",intern=TRUE)) character(0) > try(system("convert tmp/3iksg1292249266.ps tmp/3iksg1292249266.png",intern=TRUE)) character(0) > try(system("convert tmp/4iksg1292249266.ps tmp/4iksg1292249266.png",intern=TRUE)) character(0) > try(system("convert tmp/5ab9j1292249266.ps tmp/5ab9j1292249266.png",intern=TRUE)) character(0) > try(system("convert tmp/6ab9j1292249266.ps tmp/6ab9j1292249266.png",intern=TRUE)) character(0) > try(system("convert tmp/7l2841292249266.ps tmp/7l2841292249266.png",intern=TRUE)) character(0) > try(system("convert tmp/8l2841292249266.ps tmp/8l2841292249266.png",intern=TRUE)) character(0) > try(system("convert tmp/9eb871292249266.ps tmp/9eb871292249266.png",intern=TRUE)) character(0) > try(system("convert tmp/10eb871292249266.ps tmp/10eb871292249266.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.654 2.478 3.993