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Type 'q()' to quit R. > x <- array(list(2.0 + ,6.3 + ,4.5 + ,1000 + ,6600 + ,42.0 + ,3 + ,1 + ,3 + ,1.8 + ,2.1 + ,69.0 + ,2547000 + ,4603000 + ,624.0 + ,3 + ,5 + ,4 + ,.7 + ,9.1 + ,27.0 + ,10550 + ,179500 + ,180.0 + ,4 + ,4 + ,4 + ,3.9 + ,15.8 + ,19.0 + ,0.023 + ,0.3 + ,35.0 + ,1 + ,1 + ,1 + ,1.0 + ,5.2 + ,30.4 + ,160000 + ,169000 + ,392.0 + ,4 + ,5 + ,4 + ,3.6 + ,10.9 + ,28.0 + ,3300 + ,25600 + ,63.0 + ,1 + ,2 + ,1 + ,1.4 + ,8.3 + ,50.0 + ,52160 + ,440000 + ,230.0 + ,1 + ,1 + ,1 + ,1.5 + ,11.0 + ,7.0 + ,0.425 + ,6400 + ,112.0 + ,5 + ,4 + ,4 + ,.7 + ,3.2 + ,30.0 + ,465000 + ,423000 + ,281.0 + ,5 + ,5 + ,5 + ,2.1 + ,6.3 + ,3.5 + ,0.075 + ,1200 + ,42.0 + ,1 + ,1 + ,1 + ,4.1 + ,6.6 + ,6.0 + ,0.785 + ,3500 + ,42.0 + ,2 + ,2 + ,2 + ,1.2 + ,9.5 + ,10.4 + ,0.2 + ,5000 + ,120.0 + ,2 + ,2 + ,2 + ,.5 + ,3.3 + ,20.0 + ,27660 + ,115000 + ,148.0 + ,5 + ,5 + ,5 + ,3.4 + ,11.0 + ,3.9 + ,0.12 + ,1000 + ,16.0 + ,3 + ,1 + ,2 + ,1.5 + ,4.7 + ,41.0 + ,85000 + ,325000 + ,310.0 + ,1 + ,3 + ,1 + ,3.4 + ,10.4 + ,9.0 + ,0.101 + ,4000 + ,28.0 + ,5 + ,1 + ,3 + ,.8 + ,7.4 + ,7.6 + ,1040 + ,5500 + ,68.0 + ,5 + ,3 + ,4 + ,.8 + ,2.1 + ,46.0 + ,521000 + ,655000 + ,336.0 + ,5 + ,5 + ,5 + ,2.0 + ,17.9 + ,24.0 + ,0.01 + ,0.25 + ,50.0 + ,1 + ,1 + ,1 + ,1.9 + ,6.1 + ,100.0 + ,62000 + ,1320000 + ,267.0 + ,1 + ,1 + ,1 + ,1.3 + ,11.9 + ,3.2 + ,0.023 + ,0.4 + ,19.0 + ,4 + ,1 + ,3 + ,5.6 + ,13.8 + ,5.0 + ,1700 + ,6300 + ,12.0 + ,2 + ,1 + ,1 + ,3.1 + ,14.3 + ,6.5 + ,3500 + ,10800 + ,120.0 + ,2 + ,1 + ,1 + ,1.8 + ,15.2 + ,12.0 + ,0.48 + ,15500 + ,140.0 + ,2 + ,2 + ,2 + ,.9 + ,10.0 + ,20.2 + ,10000 + ,115000 + ,170.0 + ,4 + ,4 + ,4 + ,1.8 + ,11.9 + ,13.0 + ,1620 + ,11400 + ,17.0 + ,2 + ,1 + ,2 + ,1.9 + ,6.5 + ,27.0 + ,192000 + ,180000 + ,115.0 + ,4 + ,4 + ,4 + ,.9 + ,7.5 + ,18.0 + ,2500 + ,12100 + ,31.0 + ,5 + ,5 + ,5 + ,2.6 + ,10.6 + ,4.7 + ,0.28 + ,1900 + ,21.0 + ,3 + ,1 + ,3 + ,2.4 + ,7.4 + ,9.8 + ,4235 + ,50400 + ,52.0 + ,1 + ,1 + ,1 + ,1.2 + ,8.4 + ,29.0 + ,6800 + ,179000 + ,164.0 + ,2 + ,3 + ,2 + ,.9 + ,5.7 + ,7.0 + ,0.75 + ,12300 + ,225.0 + ,2 + ,2 + ,2 + ,.5 + ,4.9 + ,6.0 + ,3600 + ,21000 + ,225.0 + ,3 + ,2 + ,3 + ,.6 + ,3.2 + ,20.0 + ,55500 + ,175000 + ,151.0 + ,5 + ,5 + ,5 + ,2.3 + ,11.0 + ,4.5 + ,0.9 + ,2600 + ,60.0 + ,2 + ,1 + ,2 + ,.5 + ,4.9 + ,7.5 + ,2000 + ,12300 + ,200.0 + ,3 + ,1 + ,3 + ,2.6 + ,13.2 + ,2.3 + ,0.104 + ,2500 + ,46.0 + ,3 + ,2 + ,2 + ,.6 + ,9.7 + ,24.0 + ,4190 + ,58000 + ,210.0 + ,4 + ,3 + ,4 + ,6.6 + ,12.8 + ,3.0 + ,3500 + ,3900 + ,14.0 + ,2 + ,1 + ,1) + ,dim=c(9 + ,39) + ,dimnames=list(c('PS' + ,'SWS' + ,'L' + ,'Wb' + ,'Wbr' + ,'Tg' + ,'P' + ,'S' + ,'D ') + ,1:39)) > y <- array(NA,dim=c(9,39),dimnames=list(c('PS','SWS','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 > 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\r 1 2.0 6.3 4.5 1.000e+03 6.600e+03 42 3 1 3 2 1.8 2.1 69.0 2.547e+06 4.603e+06 624 3 5 4 3 0.7 9.1 27.0 1.055e+04 1.795e+05 180 4 4 4 4 3.9 15.8 19.0 2.300e-02 3.000e-01 35 1 1 1 5 1.0 5.2 30.4 1.600e+05 1.690e+05 392 4 5 4 6 3.6 10.9 28.0 3.300e+03 2.560e+04 63 1 2 1 7 1.4 8.3 50.0 5.216e+04 4.400e+05 230 1 1 1 8 1.5 11.0 7.0 4.250e-01 6.400e+03 112 5 4 4 9 0.7 3.2 30.0 4.650e+05 4.230e+05 281 5 5 5 10 2.1 6.3 3.5 7.500e-02 1.200e+03 42 1 1 1 11 4.1 6.6 6.0 7.850e-01 3.500e+03 42 2 2 2 12 1.2 9.5 10.4 2.000e-01 5.000e+03 120 2 2 2 13 0.5 3.3 20.0 2.766e+04 1.150e+05 148 5 5 5 14 3.4 11.0 3.9 1.200e-01 1.000e+03 16 3 1 2 15 1.5 4.7 41.0 8.500e+04 3.250e+05 310 1 3 1 16 3.4 10.4 9.0 1.010e-01 4.000e+03 28 5 1 3 17 0.8 7.4 7.6 1.040e+03 5.500e+03 68 5 3 4 18 0.8 2.1 46.0 5.210e+05 6.550e+05 336 5 5 5 19 2.0 17.9 24.0 1.000e-02 2.500e-01 50 1 1 1 20 1.9 6.1 100.0 6.200e+04 1.320e+06 267 1 1 1 21 1.3 11.9 3.2 2.300e-02 4.000e-01 19 4 1 3 22 5.6 13.8 5.0 1.700e+03 6.300e+03 12 2 1 1 23 3.1 14.3 6.5 3.500e+03 1.080e+04 120 2 1 1 24 1.8 15.2 12.0 4.800e-01 1.550e+04 140 2 2 2 25 0.9 10.0 20.2 1.000e+04 1.150e+05 170 4 4 4 26 1.8 11.9 13.0 1.620e+03 1.140e+04 17 2 1 2 27 1.9 6.5 27.0 1.920e+05 1.800e+05 115 4 4 4 28 0.9 7.5 18.0 2.500e+03 1.210e+04 31 5 5 5 29 2.6 10.6 4.7 2.800e-01 1.900e+03 21 3 1 3 30 2.4 7.4 9.8 4.235e+03 5.040e+04 52 1 1 1 31 1.2 8.4 29.0 6.800e+03 1.790e+05 164 2 3 2 32 0.9 5.7 7.0 7.500e-01 1.230e+04 225 2 2 2 33 0.5 4.9 6.0 3.600e+03 2.100e+04 225 3 2 3 34 0.6 3.2 20.0 5.550e+04 1.750e+05 151 5 5 5 35 2.3 11.0 4.5 9.000e-01 2.600e+03 60 2 1 2 36 0.5 4.9 7.5 2.000e+03 1.230e+04 200 3 1 3 37 2.6 13.2 2.3 1.040e-01 2.500e+03 46 3 2 2 38 0.6 9.7 24.0 4.190e+03 5.800e+04 210 4 3 4 39 6.6 12.8 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) SWS L Wb Wbr Tg 3.987e+00 -1.396e-02 1.194e-02 3.637e-06 -1.022e-06 -7.506e-03 P S `D\r` 9.243e-01 2.631e-01 -1.714e+00 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -1.23547 -0.55815 0.03274 0.24759 2.45448 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 3.987e+00 8.122e-01 4.908 3.02e-05 *** SWS -1.396e-02 5.360e-02 -0.260 0.796268 L 1.194e-02 1.604e-02 0.745 0.462186 Wb 3.637e-06 1.903e-06 1.911 0.065621 . Wbr -1.022e-06 1.137e-06 -0.899 0.375825 Tg -7.506e-03 2.330e-03 -3.222 0.003062 ** P 9.243e-01 3.308e-01 2.794 0.008982 ** S 2.631e-01 2.049e-01 1.284 0.208885 `D\r` -1.714e+00 4.192e-01 -4.088 0.000300 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 0.8783 on 30 degrees of freedom Multiple R-squared: 0.6918, Adjusted R-squared: 0.6096 F-statistic: 8.416 on 8 and 30 DF, p-value: 6.33e-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,] 0.8557194 0.2885613 0.1442806 [2,] 0.7512213 0.4975575 0.2487787 [3,] 0.6484310 0.7031380 0.3515690 [4,] 0.5061490 0.9877020 0.4938510 [5,] 0.3959754 0.7919509 0.6040246 [6,] 0.4181708 0.8363417 0.5818292 [7,] 0.3060699 0.6121398 0.6939301 [8,] 0.3223019 0.6446038 0.6776981 [9,] 0.2412377 0.4824754 0.7587623 [10,] 0.4073070 0.8146139 0.5926930 [11,] 0.5092643 0.9814715 0.4907357 [12,] 0.4401368 0.8802735 0.5598632 [13,] 0.3163271 0.6326541 0.6836729 [14,] 0.2203668 0.4407335 0.7796332 [15,] 0.1769803 0.3539606 0.8230197 [16,] 0.1661278 0.3322556 0.8338722 > postscript(file="/var/www/rcomp/tmp/1reyv1292176632.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/2reyv1292176632.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$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/rcomp/tmp/32nfy1292176632.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/42nfy1292176632.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/52nfy1292176632.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 0.470821293 -0.090490674 0.119108383 0.695905946 1.098052048 0.181246231 7 8 9 10 11 12 -0.555461883 -0.388680680 -0.118541675 -0.997848953 1.505116787 -0.819927062 13 14 15 16 17 18 0.079690663 0.032738423 -0.560833047 -0.078309206 -1.218006784 0.221247533 19 20 21 22 23 24 -1.121897153 0.457765980 -1.235470681 1.438539921 -0.263676834 0.001403580 25 26 27 28 29 30 0.273924051 -0.726876161 0.135553311 -0.329643623 0.969677547 -0.647800850 31 32 33 34 35 36 -0.837179435 -0.336774990 0.049164945 0.160877579 0.181738355 0.103602647 37 38 39 -0.753793747 0.450560096 2.454478120 > postscript(file="/var/www/rcomp/tmp/6uxwj1292176632.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 0.470821293 NA 1 -0.090490674 0.470821293 2 0.119108383 -0.090490674 3 0.695905946 0.119108383 4 1.098052048 0.695905946 5 0.181246231 1.098052048 6 -0.555461883 0.181246231 7 -0.388680680 -0.555461883 8 -0.118541675 -0.388680680 9 -0.997848953 -0.118541675 10 1.505116787 -0.997848953 11 -0.819927062 1.505116787 12 0.079690663 -0.819927062 13 0.032738423 0.079690663 14 -0.560833047 0.032738423 15 -0.078309206 -0.560833047 16 -1.218006784 -0.078309206 17 0.221247533 -1.218006784 18 -1.121897153 0.221247533 19 0.457765980 -1.121897153 20 -1.235470681 0.457765980 21 1.438539921 -1.235470681 22 -0.263676834 1.438539921 23 0.001403580 -0.263676834 24 0.273924051 0.001403580 25 -0.726876161 0.273924051 26 0.135553311 -0.726876161 27 -0.329643623 0.135553311 28 0.969677547 -0.329643623 29 -0.647800850 0.969677547 30 -0.837179435 -0.647800850 31 -0.336774990 -0.837179435 32 0.049164945 -0.336774990 33 0.160877579 0.049164945 34 0.181738355 0.160877579 35 0.103602647 0.181738355 36 -0.753793747 0.103602647 37 0.450560096 -0.753793747 38 2.454478120 0.450560096 39 NA 2.454478120 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] -0.090490674 0.470821293 [2,] 0.119108383 -0.090490674 [3,] 0.695905946 0.119108383 [4,] 1.098052048 0.695905946 [5,] 0.181246231 1.098052048 [6,] -0.555461883 0.181246231 [7,] -0.388680680 -0.555461883 [8,] -0.118541675 -0.388680680 [9,] -0.997848953 -0.118541675 [10,] 1.505116787 -0.997848953 [11,] -0.819927062 1.505116787 [12,] 0.079690663 -0.819927062 [13,] 0.032738423 0.079690663 [14,] -0.560833047 0.032738423 [15,] -0.078309206 -0.560833047 [16,] -1.218006784 -0.078309206 [17,] 0.221247533 -1.218006784 [18,] -1.121897153 0.221247533 [19,] 0.457765980 -1.121897153 [20,] -1.235470681 0.457765980 [21,] 1.438539921 -1.235470681 [22,] -0.263676834 1.438539921 [23,] 0.001403580 -0.263676834 [24,] 0.273924051 0.001403580 [25,] -0.726876161 0.273924051 [26,] 0.135553311 -0.726876161 [27,] -0.329643623 0.135553311 [28,] 0.969677547 -0.329643623 [29,] -0.647800850 0.969677547 [30,] -0.837179435 -0.647800850 [31,] -0.336774990 -0.837179435 [32,] 0.049164945 -0.336774990 [33,] 0.160877579 0.049164945 [34,] 0.181738355 0.160877579 [35,] 0.103602647 0.181738355 [36,] -0.753793747 0.103602647 [37,] 0.450560096 -0.753793747 [38,] 2.454478120 0.450560096 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 -0.090490674 0.470821293 2 0.119108383 -0.090490674 3 0.695905946 0.119108383 4 1.098052048 0.695905946 5 0.181246231 1.098052048 6 -0.555461883 0.181246231 7 -0.388680680 -0.555461883 8 -0.118541675 -0.388680680 9 -0.997848953 -0.118541675 10 1.505116787 -0.997848953 11 -0.819927062 1.505116787 12 0.079690663 -0.819927062 13 0.032738423 0.079690663 14 -0.560833047 0.032738423 15 -0.078309206 -0.560833047 16 -1.218006784 -0.078309206 17 0.221247533 -1.218006784 18 -1.121897153 0.221247533 19 0.457765980 -1.121897153 20 -1.235470681 0.457765980 21 1.438539921 -1.235470681 22 -0.263676834 1.438539921 23 0.001403580 -0.263676834 24 0.273924051 0.001403580 25 -0.726876161 0.273924051 26 0.135553311 -0.726876161 27 -0.329643623 0.135553311 28 0.969677547 -0.329643623 29 -0.647800850 0.969677547 30 -0.837179435 -0.647800850 31 -0.336774990 -0.837179435 32 0.049164945 -0.336774990 33 0.160877579 0.049164945 34 0.181738355 0.160877579 35 0.103602647 0.181738355 36 -0.753793747 0.103602647 37 0.450560096 -0.753793747 38 2.454478120 0.450560096 > 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/rcomp/tmp/7noem1292176632.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/8noem1292176632.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/rcomp/tmp/9noem1292176632.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') Warning messages: 1: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced 2: In sqrt(crit * p * (1 - hh)/hh) : NaNs produced > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/rcomp/tmp/10gfvp1292176632.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/rcomp/tmp/111ycv1292176632.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/rcomp/tmp/12ngsi1292176632.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/rcomp/tmp/1318q91292176632.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/rcomp/tmp/144r6x1292176632.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/rcomp/tmp/15q9531292176632.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/rcomp/tmp/16l12u1292176632.tab") + } > > try(system("convert tmp/1reyv1292176632.ps tmp/1reyv1292176632.png",intern=TRUE)) character(0) > try(system("convert tmp/2reyv1292176632.ps tmp/2reyv1292176632.png",intern=TRUE)) character(0) > try(system("convert tmp/32nfy1292176632.ps tmp/32nfy1292176632.png",intern=TRUE)) character(0) > try(system("convert tmp/42nfy1292176632.ps tmp/42nfy1292176632.png",intern=TRUE)) character(0) > try(system("convert tmp/52nfy1292176632.ps tmp/52nfy1292176632.png",intern=TRUE)) character(0) > try(system("convert tmp/6uxwj1292176632.ps tmp/6uxwj1292176632.png",intern=TRUE)) character(0) > try(system("convert tmp/7noem1292176632.ps tmp/7noem1292176632.png",intern=TRUE)) character(0) > try(system("convert tmp/8noem1292176632.ps tmp/8noem1292176632.png",intern=TRUE)) character(0) > try(system("convert tmp/9noem1292176632.ps tmp/9noem1292176632.png",intern=TRUE)) character(0) > try(system("convert tmp/10gfvp1292176632.ps tmp/10gfvp1292176632.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 3.010 1.540 4.548