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Data X:
9/06/2002 169498 1.21 0.97 0.80 5.06 16/06/2002 125451 1.22 0.95 0.80 5.07 23/06/2002 140449 1.22 0.96 0.80 5.04 30/06/2002 141653 1.22 0.97 0.81 5.08 7/07/2002 136394 1.21 0.96 0.81 5.15 14/07/2002 167588 1.23 0.96 0.83 5.16 21/07/2002 191807 1.22 0.94 0.79 5.09 28/07/2002 149736 1.22 0.95 0.80 5.14 4/08/2002 196066 1.22 0.95 0.81 5.17 11/08/2002 239155 1.22 0.95 0.80 5.13 18/08/2002 178421 1.23 0.95 0.81 5.19 25/08/2002 139871 1.22 0.97 0.81 5.17 1/09/2002 118159 1.21 0.97 0.82 5.17 8/09/2002 109763 1.22 0.95 0.81 5.21 15/09/2002 97415 1.21 0.96 0.82 5.21 22/09/2002 119190 1.22 0.96 0.82 5.23 29/09/2002 97903 1.21 0.94 0.80 5.17 6/10/2002 96953 1.20 0.96 0.79 5.16 13/10/2002 87888 1.18 0.98 0.79 5.15 20/10/2002 84637 1.19 0.97 0.80 5.12 27/10/2002 90549 1.20 0.96 0.80 5.12 3/11/2002 95680 1.19 0.95 0.80 5.10 10/11/2002 99371 1.19 0.96 0.80 5.13 17/11/2002 79984 1.20 0.96 0.80 5.14 24/11/2002 86752 1.21 0.97 0.80 5.16 1/12/2002 85733 1.20 0.96 0.80 5.17 8/12/2002 84906 1.20 0.95 0.78 5.15 15/12/2002 78356 1.20 0.95 0.78 5.12 22/12/2002 108895 1.21 0.94 0.76 5.08 29/12/2002 101768 1.21 0.94 0.77 5.07 5/01/2003 73285 1.21 0.98 0.82 5.16 12/01/2003 65724 1.20 0.93 0.81 5.14 19/01/2003 67457 1.21 0.93 0.81 5.13 26/01/2003 67203 1.21 0.96 0.80 5.11 2/02/2003 69273 1.21 0.97 0.79 5.12 9/02/2003 80807 1.20 0.97 0.81 5.09 16/02/2003 75129 1.19 0.95 0.81 5.10 23/02/2003 74991 1.20 0.95 0.81 4.95 2/03/2003 68157 1.20 0.96 0.81 5.11 9/03/2003 73858 1.20 0.98 0.82 5.11 16/03/2003 71349 1.22 0.98 0.81 5.10 23/03/2003 85634 1.22 0.97 0.80 5.11 30/03/2003 91624 1.21 0.98 0.83 5.12 6/04/2003 116014 1.25 0.98 0.81 5.09 13/04/2003 120033 1.25 0.99 0.83 5.10 20/04/2003 108651 1.27 0.99 0.84 5.06 27/04/2003 105378 1.28 0.97 0.84 5.03 4/05/2003 138939 1.27 0.98 0.85 5.05 11/05/2003 132974 1.28 0.97 0.85 5.04 18/05/2003 135277 1.29 0.97 0.86 5.02 25/05/2003 152741 1.26 0.97 0.85 4.97 1/06/2003 158417 1.27 0.98 0.87 4.91 8/06/2003 157460 1.25 0.97 0.86 4.91 15/06/2003 193997 1.27 0.97 0.87 4.98 22/06/2003 154089 1.27 0.98 0.87 4.98 29/06/2003 147570 1.27 0.98 0.86 4.97 6/07/2003 162924 1.29 0.95 0.87 4.97 13/07/2003 153629 1.26 0.97 0.88 4.90 20/07/2003 155907 1.27 0.97 0.87 4.91 27/07/2003 197675 1.27 0.97 0.87 4.88 3/08/2003 250708 1.28 0.97 0.86 4.86 10/08/2003 266652 1.28 0.98 0.86 4.87 17/08/2003 209842 1.28 0.98 0.88 4.86 24/08/2003 165826 1.27 0.98 0.88 4.89 31/08/2003 137152 1.24 0.96 0.87 4.90 7/09/2003 150581 1.25 0.98 0.88 4.88 14/09/2003 145973 1.25 1.00 0.89 4.85 21/09/2003 126532 1.24 1.01 0.89 4.85 28/09/2003 115437 1.24 1.02 0.88 4.84 5/10/2003 119526 1.23 1.01 0.88 4.91 12/10/2003 110856 1.24 1.01 0.88 4.94 19/10/2003 97243 1.23 1.02 0.88 4.92 26/10/2003 103876 1.24 1.01 0.87 4.93 2/11/2003 116370 1.24 1.01 0.87 4.97 9/11/2003 109616 1.24 1.01 0.86 4.89 16/11/2003 98365 1.25 1.02 0.88 4.88 23/11/2003 90440 1.26 1.02 0.87 4.93 30/11/2003 88899 1.26 1.02 0.86 4.94 7/12/2003 92358 1.27 1.01 0.85 4.99 14/12/2003 88394 1.26 1.01 0.86 5.00 21/12/2003 98219 1.28 0.99 0.84 5.02 28/12/2003 113546 1.29 1.00 0.85 5.06 4/01/2004 107168 1.28 1.01 0.88 5.01 11/01/2004 77540 1.27 0.99 0.88 5.02 18/01/2004 74944 1.30 1.00 0.89 4.97 25/01/2004 75641 1.30 1.02 0.88 4.96 1/02/2004 75910 1.28 1.01 0.88 4.95 8/02/2004 87384 1.29 1.01 0.88 4.92 15/02/2004 84615 1.27 1.01 0.89 4.88 22/02/2004 80420 1.26 1.03 0.89 4.86 29/02/2004 80784 1.27 1.02 0.89 4.94 7/03/2004 79933 1.27 1.02 0.88 4.83 14/03/2004 82118 1.27 1.03 0.89 4.95 21/03/2004 91420 1.28 1.03 0.89 4.95 28/03/2004 112426 1.29 1.02 0.89 4.94 4/04/2004 114528 1.28 1.02 0.89 4.93 11/04/2004 131025 1.30 1.02 0.90 4.97 18/04/2004 116460 1.30 1.02 0.88 4.95 25/04/2004 111258 1.30 1.03 0.90 4.92 2/05/2004 155318 1.29 1.02 0.88 4.82 9/05/2004 155078 1.30 1.02 0.90 4.82 16/05/2004 134794 1.29 1.02 0.89 4.84 23/05/2004 139985 1.28 1.03 0.89 4.83 30/05/2004 198778 1.30 1.02 0.88 4.79 6/06/2004 172436 1.30 1.02 0.89 4.81 13/06/2004 169585 1.31 1.02 0.91 4.85 20/06/2004 203702 1.32 1.02 0.91 4.84 27/06/2004 282392 1.33 1.02 0.90 4.82 4/07/2004 220658 1.32 1.00 0.93 4.92 11/07/2004 194472 1.30 1.04 0.94 4.92 18/07/2004 269246 1.31 1.04 0.95 4.90 25/07/2004 215340 1.30 1.03 0.95 4.91 1/08/2004 218319 1.30 1.02 0.93 4.85 8/08/2004 195724 1.30 1.04 0.95 4.86 15/08/2004 174614 1.29 1.05 0.95 4.88 22/08/2004 172085 1.29 1.03 0.94 4.85 29/08/2004 152347 1.30 0.99 0.92 4.91 5/09/2004 189615 1.30 1.03 0.94 4.89 12/09/2004 173804 1.29 1.08 0.95 4.92 19/09/2004 145683 1.27 1.09 0.97 4.82 26/09/2004 133550 1.26 1.08 0.96 4.82 3/10/2004 121156 1.25 1.05 0.92 4.87 10/10/2004 112040 1.26 1.06 0.94 4.88 17/10/2004 120767 1.27 1.04 0.94 4.90 24/10/2004 127019 1.26 1.06 0.92 4.88 31/10/2004 136295 1.25 1.06 0.91 4.89 7/11/2004 113425 1.25 1.07 0.93 4.88 14/11/2004 107815 1.25 1.08 0.93 4.87 21/11/2004 100298 1.26 1.08 0.94 4.85 28/11/2004 97048 1.26 1.05 0.92 4.87 5/12/2004 98750 1.26 1.04 0.91 4.88 12/12/2004 98235 1.27 1.04 0.91 4.87 19/12/2004 101254 1.28 1.04 0.90 4.93 26/12/2004 139589 1.29 1.04 0.89 4.93 2/01/2005 134921 1.30 1.06 0.91 4.74 9/01/2005 80355 1.26 1.08 0.93 4.77 16/01/2005 80396 1.25 1.08 0.94 4.81 23/01/2005 82183 1.26 1.08 0.93 4.82 30/01/2005 79709 1.25 1.07 0.91 4.79 6/02/2005 90781 1.24 1.06 0.92 4.75
Names of X columns:
PERIODE QBEFRU PPIL PCOLA PORA PSTIM

Sample Range: (leave blank to include all observations)
From:
To:

Column Number of Endogenous Series (?)


Fixed Seasonal Effects


Type of Equation


Degree of Predetermination (lagged endogenous variables)


Degree of Seasonal Predetermination


Seasonality


Chart options



R Code
library(lattice) library(lmtest) 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 k <- length(x[1,]) df <- as.data.frame(x) (mylm <- lm(df)) (mysum <- summary(mylm)) 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)$p.value } if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 } gqarr } bitmap(file='test0.png') plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') points(x[,1]-mysum$resid) grid() dev.off() bitmap(file='test1.png') plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') grid() dev.off() bitmap(file='test2.png') hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') grid() dev.off() bitmap(file='test3.png') densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') dev.off() bitmap(file='test4.png') qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') qqline(mysum$resid) grid() dev.off() (myerror <- as.ts(mysum$resid)) bitmap(file='test5.png') dum <- cbind(lag(myerror,k=1),myerror) dum dum1 <- dum[2:length(myerror),] dum1 z <- as.data.frame(dum1) z 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() bitmap(file='test6.png') acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') grid() dev.off() bitmap(file='test7.png') pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') grid() dev.off() bitmap(file='test8.png') opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) plot(mylm, las = 1, sub='Residual Diagnostics') par(opar) dev.off() if (n > n25) { bitmap(file='test9.png') plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') grid() dev.off() } load(file='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$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') } } myeq <- paste(myeq, ' + e[t]') a<-table.row.start(a) a<-table.element(a, myeq) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variable',header=TRUE) a<-table.element(a,'Parameter',header=TRUE) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,'T-STAT<br />H0: parameter = 0',header=TRUE) a<-table.element(a,'2-tail p-value',header=TRUE) a<-table.element(a,'1-tail p-value',header=TRUE) a<-table.row.end(a) for (i in 1:k){ a<-table.row.start(a) a<-table.element(a,rownames(mysum$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$coefficients[i,4]/2,6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable2.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Multiple R',1,TRUE) a<-table.element(a, sqrt(mysum$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$sigma) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Sum Squared Residuals',1,TRUE) a<-table.element(a, sum(myerror*myerror)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable3.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Time or Index', 1, TRUE) a<-table.element(a, 'Actuals', 1, TRUE) a<-table.element(a, 'Interpolation<br />Forecast', 1, TRUE) a<-table.element(a, 'Residuals<br />Prediction Error', 1, TRUE) a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,i, 1, TRUE) a<-table.element(a,x[i]) a<-table.element(a,x[i]-mysum$resid[i]) a<-table.element(a,mysum$resid[i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable4.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='mytable5.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='mytable6.tab') }

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Raw Output	view raw output of R engine
Computing time	0 seconds
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