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Type 'q()' to quit R. > x <- c(88.1,101.7,114.8,103.4,96.4,110,71.1,79.4,119.2,99.1,113.2,103.6,97.5,102.4,120.8,89.5,101.7,112.5,72.4,84.7,117.2,112.8,111.3,102.3,95.2,103,116.4,95.1,100.7,112.4,75.3,93.3,118.6,118.7,110.7,113.3,89.5,106.3,115.1,105.7,95.8,114.7,79.6,80.6,125,127.5,99.5,104.3,90,96,108.9,95.8,87.2,108.4,74.9,80.8,119.1,107.9,106.9,96.8,93.7,95.2,112.7,98.5,91.5,112,76.7,84.7,114.9,108.4,104.6,111.3,90.8,109.1,121,95.2,110.5,102.4,86.7,99.1,126,110.3,104.6,103.1,102) > par3 = 'additive' > par2 = 'Triple' > par1 = '12' > par1 <- as.numeric(par1) > if (par2 == 'Single') K <- 1 > if (par2 == 'Double') K <- 2 > if (par2 == 'Triple') K <- par1 > nx <- length(x) > nxmK <- nx - K > x <- ts(x, frequency = par1) > if (par2 == 'Single') fit <- HoltWinters(x, gamma=F, beta=F) > if (par2 == 'Double') fit <- HoltWinters(x, gamma=F) > if (par2 == 'Triple') fit <- HoltWinters(x, seasonal=par3) > fit Holt-Winters exponential smoothing with trend and additive seasonal component. Call: HoltWinters(x = x, seasonal = par3) Smoothing parameters: alpha: 0.1059123 beta : 0 gamma: 0.5714541 Coefficients: [,1] a 107.4391364 b 0.1485577 s1 0.3610466 s2 13.2974263 s3 -7.4532504 s4 -2.4498079 s5 2.0800624 s6 -22.5518151 s7 -13.2139993 s8 16.3684687 s9 4.9940957 s10 -0.3685878 s11 -0.3461235 s12 -8.0173158 > myresid <- x - fit$fitted[,'xhat'] > postscript(file="/var/fisher/rcomp/tmp/1p2j61353708047.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow=c(2,1)) > plot(fit,ylab='Observed (black) / Fitted (red)',main='Interpolation Fit of Exponential Smoothing') > plot(myresid,ylab='Residuals',main='Interpolation Prediction Errors') > par(op) > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/2swle1353708047.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > p <- predict(fit, par1, prediction.interval=TRUE) > np <- length(p[,1]) > plot(fit,p,ylab='Observed (black) / Fitted (red)',main='Extrapolation Fit of Exponential Smoothing') > dev.off() null device 1 > postscript(file="/var/fisher/rcomp/tmp/37ap61353708047.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > op <- par(mfrow = c(2,2)) > acf(as.numeric(myresid),lag.max = nx/2,main='Residual ACF') > spectrum(myresid,main='Residals Periodogram') > cpgram(myresid,main='Residal Cumulative Periodogram') > qqnorm(myresid,main='Residual Normal QQ Plot') > qqline(myresid) > par(op) > dev.off() null device 1 > > #Note: the /var/fisher/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/fisher/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Estimated Parameters of Exponential Smoothing',2,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'Value',header=TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'alpha',header=TRUE) > a<-table.element(a,fit$alpha) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'beta',header=TRUE) > a<-table.element(a,fit$beta) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'gamma',header=TRUE) > a<-table.element(a,fit$gamma) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/4a7wn1353708047.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Interpolation Forecasts of Exponential Smoothing',4,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'t',header=TRUE) > a<-table.element(a,'Observed',header=TRUE) > a<-table.element(a,'Fitted',header=TRUE) > a<-table.element(a,'Residuals',header=TRUE) > a<-table.row.end(a) > for (i in 1:nxmK) { + a<-table.row.start(a) + a<-table.element(a,i+K,header=TRUE) + a<-table.element(a,x[i+K]) + a<-table.element(a,fit$fitted[i,'xhat']) + a<-table.element(a,myresid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/5y7yf1353708047.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Extrapolation Forecasts of Exponential Smoothing',4,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'t',header=TRUE) > a<-table.element(a,'Forecast',header=TRUE) > a<-table.element(a,'95% Lower Bound',header=TRUE) > a<-table.element(a,'95% Upper Bound',header=TRUE) > a<-table.row.end(a) > for (i in 1:np) { + a<-table.row.start(a) + a<-table.element(a,nx+i,header=TRUE) + a<-table.element(a,p[i,'fit']) + a<-table.element(a,p[i,'lwr']) + a<-table.element(a,p[i,'upr']) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/6zq661353708047.tab") > > try(system("convert tmp/1p2j61353708047.ps tmp/1p2j61353708047.png",intern=TRUE)) character(0) > try(system("convert tmp/2swle1353708047.ps tmp/2swle1353708047.png",intern=TRUE)) character(0) > try(system("convert tmp/37ap61353708047.ps tmp/37ap61353708047.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 2.001 0.526 2.502