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Type 'q()' to quit R. > x <- c(83.36,83.61,83.41,83.64,84.06,83.93,84.1,84.37,84.18,84.11,84.56,84.2,84.45,84.28,84.28,84.7,85.04,85.31,85.18,85.02,86.31,86.56,86.4,86.84,87.42,87.28,87.27,87.73,87.32,87.15,87.5,87.43,88.81,89.38,88.83,88.91,89.34,89.56,89.32,89.31,89.45,88.92,89.35,88.89,90.1,90.49,89.96,89.93,90.32,90.24,90.61,91.06,90.81,91.09,91.17,90.87,91.92,92.67,92.03,92.09,92.61,92.19,92.68,92.66,92.77,92.21,92.58,91.9,93.81,94.05,94.51,94.49,94.36,94.72,95.57,95.87,95.93,96.09,95.82,96.06,97.09,97.67,98.53,98.12,98.84,98.98,100.04,99.47,99.84,99.52,99.81,99.55,100.21,101.44,101,101.32,101.84,101.81,101.83,102.18,101.97,101.8,101.69,101.91,102.27,102.73,102.61,102.89) > par3 = 'additive' > par2 = 'Triple' > par1 = '12' > par3 <- 'additive' > par2 <- 'Triple' > 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$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_exponentialsmoothing.wasp/ > #Source of accompanying publication: > # > par1 <- as.numeric(par1) > if (par2 == 'Single') K <- 1 > if (par2 == 'Double') K <- 2 > if (par2 == 'Triple') K <- par1 > nx <- length(x) > nxmK <- nx - K > x <- ts(x, frequency = par1) > if (par2 == 'Single') fit <- HoltWinters(x, gamma=F, beta=F) > if (par2 == 'Double') fit <- HoltWinters(x, gamma=F) > if (par2 == 'Triple') fit <- HoltWinters(x, seasonal=par3) > fit Holt-Winters exponential smoothing with trend and additive seasonal component. Call: HoltWinters(x = x, seasonal = par3) Smoothing parameters: alpha: 0.3795388 beta : 0.09290786 gamma: 1 Coefficients: [,1] a 102.61207705 b 0.15746498 s1 0.64707121 s2 0.36081395 s3 0.44240937 s4 0.45303166 s5 0.12460708 s6 -0.25003518 s7 -0.48640494 s8 -0.61097086 s9 -0.37029440 s10 0.19139257 s11 0.07634784 s12 0.27792295 > myresid <- x - fit$fitted[,'xhat'] > postscript(file="/var/wessaorg/rcomp/tmp/1xgjh1448470387.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/wessaorg/rcomp/tmp/2kbmn1448470387.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/wessaorg/rcomp/tmp/3c1cs1448470387.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/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,'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$gamma) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/4aw3r1448470387.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,'Interpolation Forecasts of Exponential Smoothing',4,TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'t',header=TRUE) > a<-table.element(a,'Observed',header=TRUE) > a<-table.element(a,'Fitted',header=TRUE) > a<-table.element(a,'Residuals',header=TRUE) > a<-table.row.end(a) > for (i in 1:nxmK) { + a<-table.row.start(a) + a<-table.element(a,i+K,header=TRUE) + a<-table.element(a,x[i+K]) + a<-table.element(a,fit$fitted[i,'xhat']) + a<-table.element(a,myresid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/wessaorg/rcomp/tmp/5x2la1448470387.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/wessaorg/rcomp/tmp/61mgp1448470387.tab") > > try(system("convert tmp/1xgjh1448470387.ps tmp/1xgjh1448470387.png",intern=TRUE)) character(0) > try(system("convert tmp/2kbmn1448470387.ps tmp/2kbmn1448470387.png",intern=TRUE)) character(0) > try(system("convert tmp/3c1cs1448470387.ps tmp/3c1cs1448470387.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 1.219 0.266 1.494