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Type 'q()' to quit R. > x <- array(list(1192,5,-4.3574,0,1196,6,-1.4534,1,1183,8,-3.9786,0,1210,9,-1.0745,0,1210,10,1.8295,0,1218,11,2.5114,0,1219,12,7.0821,0,1202,15,-3.0946,0,1195,16,-2.4128,0,1203,17,2.1579,0,1170,19,-0.9229,1,1189,20,4.2034,1,1199,21,2.6630,0,1196,22,4.4560,0,1189,23,-2.6400,0,1185,25,4.2792,0,1192,26,1.0722,0,1188,27,-1.0238,0,1176,28,-2.5641,0,1166,31,-7.7409,0,1176,32,-0.9479,0,1181,33,1.9561,0),dim=c(4,22),dimnames=list(c('TIMEin','DATE','TEMP','RAIN'),1:22)) > y <- array(NA,dim=c(4,22),dimnames=list(c('TIMEin','DATE','TEMP','RAIN'),1:22)) > 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' > 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 TIMEin DATE TEMP RAIN 1 1192 5 -4.3574 0 2 1196 6 -1.4534 1 3 1183 8 -3.9786 0 4 1210 9 -1.0745 0 5 1210 10 1.8295 0 6 1218 11 2.5114 0 7 1219 12 7.0821 0 8 1202 15 -3.0946 0 9 1195 16 -2.4128 0 10 1203 17 2.1579 0 11 1170 19 -0.9229 1 12 1189 20 4.2034 1 13 1199 21 2.6630 0 14 1196 22 4.4560 0 15 1189 23 -2.6400 0 16 1185 25 4.2792 0 17 1192 26 1.0722 0 18 1188 27 -1.0238 0 19 1176 28 -2.5641 0 20 1166 31 -7.7409 0 21 1176 32 -0.9479 0 22 1181 33 1.9561 0 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) DATE TEMP RAIN 1216.473 -1.156 2.198 -15.468 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -15.479 -2.251 1.255 4.501 9.672 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1216.4734 3.8122 319.101 < 2e-16 *** DATE -1.1563 0.1774 -6.517 3.98e-06 *** TEMP 2.1978 0.4290 5.123 7.11e-05 *** RAIN -15.4677 4.3891 -3.524 0.00242 ** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 6.927 on 18 degrees of freedom Multiple R-squared: 0.7998, Adjusted R-squared: 0.7665 F-statistic: 23.98 on 3 and 18 DF, p-value: 1.645e-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 + } > postscript(file="/var/wessaorg/rcomp/tmp/10ocm1338990367.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$resid) > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/2xeaf1338990367.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/3jetm1338990367.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/4p55j1338990367.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/5c09s1338990367.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 = 22 Frequency = 1 1 2 3 4 5 6 -9.1154756 5.1262496 -15.4791589 6.2946001 1.0685788 8.7262019 7 8 9 10 11 12 0.8371726 9.6719538 2.3297967 1.4407674 -7.0080722 1.8818226 13 14 15 16 17 18 0.9557831 -4.8285259 4.9230612 -11.9711332 3.2333620 4.9961449 19 20 21 22 -2.4623679 2.3838289 -1.3892843 -1.6153056 > postscript(file="/var/wessaorg/rcomp/tmp/6b2g41338990367.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 = 22 Frequency = 1 lag(myerror, k = 1) myerror 0 -9.1154756 NA 1 5.1262496 -9.1154756 2 -15.4791589 5.1262496 3 6.2946001 -15.4791589 4 1.0685788 6.2946001 5 8.7262019 1.0685788 6 0.8371726 8.7262019 7 9.6719538 0.8371726 8 2.3297967 9.6719538 9 1.4407674 2.3297967 10 -7.0080722 1.4407674 11 1.8818226 -7.0080722 12 0.9557831 1.8818226 13 -4.8285259 0.9557831 14 4.9230612 -4.8285259 15 -11.9711332 4.9230612 16 3.2333620 -11.9711332 17 4.9961449 3.2333620 18 -2.4623679 4.9961449 19 2.3838289 -2.4623679 20 -1.3892843 2.3838289 21 -1.6153056 -1.3892843 22 NA -1.6153056 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 5.1262496 -9.1154756 [2,] -15.4791589 5.1262496 [3,] 6.2946001 -15.4791589 [4,] 1.0685788 6.2946001 [5,] 8.7262019 1.0685788 [6,] 0.8371726 8.7262019 [7,] 9.6719538 0.8371726 [8,] 2.3297967 9.6719538 [9,] 1.4407674 2.3297967 [10,] -7.0080722 1.4407674 [11,] 1.8818226 -7.0080722 [12,] 0.9557831 1.8818226 [13,] -4.8285259 0.9557831 [14,] 4.9230612 -4.8285259 [15,] -11.9711332 4.9230612 [16,] 3.2333620 -11.9711332 [17,] 4.9961449 3.2333620 [18,] -2.4623679 4.9961449 [19,] 2.3838289 -2.4623679 [20,] -1.3892843 2.3838289 [21,] -1.6153056 -1.3892843 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 5.1262496 -9.1154756 2 -15.4791589 5.1262496 3 6.2946001 -15.4791589 4 1.0685788 6.2946001 5 8.7262019 1.0685788 6 0.8371726 8.7262019 7 9.6719538 0.8371726 8 2.3297967 9.6719538 9 1.4407674 2.3297967 10 -7.0080722 1.4407674 11 1.8818226 -7.0080722 12 0.9557831 1.8818226 13 -4.8285259 0.9557831 14 4.9230612 -4.8285259 15 -11.9711332 4.9230612 16 3.2333620 -11.9711332 17 4.9961449 3.2333620 18 -2.4623679 4.9961449 19 2.3838289 -2.4623679 20 -1.3892843 2.3838289 21 -1.6153056 -1.3892843 > 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/wessaorg/rcomp/tmp/76fhk1338990367.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/8o7no1338990367.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/wessaorg/rcomp/tmp/9wzbt1338990367.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/wessaorg/rcomp/tmp/10el9x1338990367.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } > > #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/wessaorg/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$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/wessaorg/rcomp/tmp/11z3kp1338990367.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/wessaorg/rcomp/tmp/129q8l1338990367.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/wessaorg/rcomp/tmp/13qhe21338990367.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/wessaorg/rcomp/tmp/14ku6r1338990367.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/wessaorg/rcomp/tmp/159oby1338990367.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/wessaorg/rcomp/tmp/16wyns1338990367.tab") + } > > try(system("convert tmp/10ocm1338990367.ps tmp/10ocm1338990367.png",intern=TRUE)) character(0) > try(system("convert tmp/2xeaf1338990367.ps tmp/2xeaf1338990367.png",intern=TRUE)) character(0) > try(system("convert tmp/3jetm1338990367.ps tmp/3jetm1338990367.png",intern=TRUE)) character(0) > try(system("convert tmp/4p55j1338990367.ps tmp/4p55j1338990367.png",intern=TRUE)) character(0) > try(system("convert tmp/5c09s1338990367.ps tmp/5c09s1338990367.png",intern=TRUE)) character(0) > try(system("convert tmp/6b2g41338990367.ps tmp/6b2g41338990367.png",intern=TRUE)) character(0) > try(system("convert tmp/76fhk1338990367.ps tmp/76fhk1338990367.png",intern=TRUE)) character(0) > try(system("convert tmp/8o7no1338990367.ps tmp/8o7no1338990367.png",intern=TRUE)) character(0) > try(system("convert tmp/9wzbt1338990367.ps tmp/9wzbt1338990367.png",intern=TRUE)) character(0) > try(system("convert tmp/10el9x1338990367.ps tmp/10el9x1338990367.png",intern=TRUE)) convert: unable to open image `tmp/10el9x1338990367.ps': No such file or directory @ blob.c/OpenBlob/2480. convert: missing an image filename `tmp/10el9x1338990367.png' @ convert.c/ConvertImageCommand/2838. character(0) Warning message: running command 'convert tmp/10el9x1338990367.ps tmp/10el9x1338990367.png' had status 1 > > > proc.time() user system elapsed 3.134 0.767 4.042