Wessa.net

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Data:
4030 4320 4840 4410 4180 4240 3680 4270 4140 4470 4180 4510 4490 3960 3750 3670 3590 2840 3530 4320 3740 3710 3830 3490 4200 4280 4650 2100 2410 1230 2420 2360 1870 2250 1960 2550 3180 3330 3760 3930 3710 3250 3450 3480 3090 3690 3250 3300 4040 3630 3820 3400 2500 2380 2520 2340 2420 2430 2080 2420 2430 2400 2790 2370 2700 2640 2910 2420 2800 2830 2310 2540 2780 2820 3610 3270 3030 3250 3040 3630 3320 3440 3110 3180 3330 3100 3440 3320 3380 3610 3320 3860 3430 3510 3290 3010 3860 3530 3610 3370 3700 3500 4110 4590 3680 4220 3740 3550 4150 4110 4160 3780 3150 3260 4750 4110 3610 3890 2800 2610 3600 3400 3400 3120 3150 3240

Type of Seasonality


Seasonal Period


Chart options



R Code
par2 <- as.numeric(par2) x <- ts(x,freq=par2) m <- decompose(x,type=par1) m$figure bitmap(file='test1.png') plot(m) dev.off() mylagmax <- length(x)/2 bitmap(file='test2.png') op <- par(mfrow = c(2,2)) acf(as.numeric(x),lag.max = mylagmax,main='Observed') acf(as.numeric(m$trend),na.action=na.pass,lag.max = mylagmax,main='Trend') acf(as.numeric(m$seasonal),na.action=na.pass,lag.max = mylagmax,main='Seasonal') acf(as.numeric(m$random),na.action=na.pass,lag.max = mylagmax,main='Random') par(op) dev.off() bitmap(file='test3.png') op <- par(mfrow = c(2,2)) spectrum(as.numeric(x),main='Observed') spectrum(as.numeric(m$trend[!is.na(m$trend)]),main='Trend') spectrum(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal') spectrum(as.numeric(m$random[!is.na(m$random)]),main='Random') par(op) dev.off() bitmap(file='test4.png') op <- par(mfrow = c(2,2)) cpgram(as.numeric(x),main='Observed') cpgram(as.numeric(m$trend[!is.na(m$trend)]),main='Trend') cpgram(as.numeric(m$seasonal[!is.na(m$seasonal)]),main='Seasonal') cpgram(as.numeric(m$random[!is.na(m$random)]),main='Random') par(op) dev.off() load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Classical Decomposition by Moving Averages',6,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'t',header=TRUE) a<-table.element(a,'Observations',header=TRUE) a<-table.element(a,'Fit',header=TRUE) a<-table.element(a,'Trend',header=TRUE) a<-table.element(a,'Seasonal',header=TRUE) a<-table.element(a,'Random',header=TRUE) a<-table.row.end(a) for (i in 1:length(m$trend)) { a<-table.row.start(a) a<-table.element(a,i,header=TRUE) a<-table.element(a,x[i]) if (par1 == 'additive') a<-table.element(a,signif(m$trend[i]+m$seasonal[i],6)) else a<-table.element(a,signif(m$trend[i]*m$seasonal[i],6)) a<-table.element(a,signif(m$trend[i],6)) a<-table.element(a,signif(m$seasonal[i],6)) a<-table.element(a,signif(m$random[i],6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab')

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