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Type 'q()' to quit R. > x <- c(13953.3,14657.7,16686.2,15232.4,15014.1,16688.6,13969.6,14546.8,16292,15039,17433.8,17798.4,16870.9,16659.3,19620.4,15953.5,17420.9,17647.5,15200.8,15637.3,17124.5,17659.4,17815,16165.6,17416.6,16823.9,19171.2,16806.8,18112.8,18485.5,17668,16324.3,17877.5,20136.7,19307,17776.3,19861.3,18757,19879.3,21068.4,19358,20639.2,20008.1,18150.1,21180.4,20428.9,17241.2,15969.3,14972.4,14488.3,15885.1,14305.3,13891.5,15431.6,14199.3,13542.6,16226.3,16786.1,16034.3,16744.5,15896.5,15781.8,18590.3,17416.8,16983,18829.4,16748.6,16502.8,18616.6,19136.4,19523.9,18970.2,20118.2,20125.4,23117.8,20014.6,22228.5,20819.1,19208.9,19953.3,21041.3,20006.8,21045.1,20496.3,20873.5,21304.2,23137.8,20514.2,21343.5,20967.2,20024.4,19602.7,19804.1,22173.9,21802.6,19452.2) > par3 = 'additive' > par2 = 'Double' > par1 = '12' > par3 <- 'additive' > par2 <- 'Double' > par1 <- '12' > #'GNU S' R Code compiled by R2WASP v. 1.2.327 () > #Author: root > #To cite this work: Wessa P., (2013), Exponential Smoothing (v1.0.5) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_exponentialsmoothing.wasp/ > #Source of accompanying publication: > # > par1 <- as.numeric(par1) > if (par2 == 'Single') K <- 1 > if (par2 == 'Double') K <- 2 > if (par2 == 'Triple') K <- par1 > nx <- length(x) > nxmK <- nx - K > x <- ts(x, frequency = par1) > if (par2 == 'Single') fit <- HoltWinters(x, gamma=F, beta=F) > if (par2 == 'Double') fit <- HoltWinters(x, gamma=F) > if (par2 == 'Triple') fit <- HoltWinters(x, seasonal=par3) > fit Holt-Winters exponential smoothing with trend and without seasonal component. Call: HoltWinters(x = x, gamma = F) Smoothing parameters: alpha: 0.513796 beta : 0.10096 gamma: FALSE Coefficients: [,1] a 20478.52409 b -14.90616 > myresid <- x - fit$fitted[,'xhat'] > postscript(file="/var/fisher/rcomp/tmp/1bc0o1386927993.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/2040w1386927993.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/3r0uw1386927993.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$gamma) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/fisher/rcomp/tmp/47p811386927993.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Interpolation Forecasts of Exponential Smoothing',4,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'t',header=TRUE) > a<-table.element(a,'Observed',header=TRUE) > a<-table.element(a,'Fitted',header=TRUE) > a<-table.element(a,'Residuals',header=TRUE) > a<-table.row.end(a) > for (i in 1:nxmK) { + a<-table.row.start(a) + a<-table.element(a,i+K,header=TRUE) + a<-table.element(a,x[i+K]) + a<-table.element(a,fit$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/53zoi1386927993.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/640ji1386927993.tab") > > try(system("convert tmp/1bc0o1386927993.ps tmp/1bc0o1386927993.png",intern=TRUE)) character(0) > try(system("convert tmp/2040w1386927993.ps tmp/2040w1386927993.png",intern=TRUE)) character(0) > try(system("convert tmp/3r0uw1386927993.ps tmp/3r0uw1386927993.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.869 1.225 6.044