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Data:
3.9 5.9 5.7 3.6 4.9 5.3 8.7 6.8 8.9 9.6 11.2 9.9 9.3 9.2 9.4 12.7 13.6 16.1 14.8 14.1 13.2 8.7 4.9 -1.3 -3.9 -6 -6.6 -8.7 -11.6 -14.6 -12.9 -13.8 -14.1 -13.2 -10.4 -3.3 1 3.1 4.5 1.9 3.9 7 5.6 8.1 6.1 8 6.5 5.6 4.8 5.1 7.8 10.3 8.6 6.8 4.9 5.4 5.5 4.7 4.2 5 5 6 2.9 3.6 5.1 2.9 4.7 3 5 2.6 3.2 2.4 3.2 2.6 2.4 2.1 2.7 4.4 4.3 4.2 5.5 8.8 10.1 7 5.7 5.2 5.5 7.3 5.9 7.1 6.9 6.7 4.7 6.7 8.5 2.1 -0.9 -4.7 4.8 2.6 1.7 -1.8 0.2 1.9 3.2 3.1 4.2 16.2 18.3 21.6 12.6 9.8 10.6 13 9.7 7.9 3.3 3.4 0.4 0.7 1.4 3.8 4 8 6 5.8 3.9 6.4 11
Type of Seasonality
multiplicative
additive
multiplicative
Seasonal Period
12
12
1
2
3
4
5
6
7
8
9
10
11
12
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$trend)) { a<-table.row.start(a) a<-table.element(a,i,header=TRUE) a<-table.element(a,x[i]) if (par1 == 'additive') a<-table.element(a,m$trend[i]+m$seasonal[i]) else a<-table.element(a,m$trend[i]*m$seasonal[i]) a<-table.element(a,m$trend[i]) a<-table.element(a,m$seasonal[i]) a<-table.element(a,m$random[i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable.tab')
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