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Data:
2622.4 2607.5 2556.6 2569.3 2533.2 2529 2577.8 2556.6 2558.7 2541.7 2473.8 2461 2435.5 2414.3 2350.6 2329.4 2278.4 2252.9 2269.9 2227.4 2195.6 2204.1 2195.6 2202 2157.4 2142.5 2125.5 2110.7 2072.4 2076.7 2095.8 2023.6 2004.5 1985.4 1953.5 1915.3 1881.3 1821.9 1775.2 1790 1758.2 1747.6 1679.6 1692.3 1675.4 1639.3 1622.3 1577.7 1581.9 1562.8 1552.2 1535.2 1507.6
Seasonal Period
0
12
1
2
3
4
6
12
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R Code
par1 <- as.numeric(par1) n.orig <- length(x) x <- na.omit(x) n <- length(x) sx <- sort(x) load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Variance Reduction Matrix',6,TRUE) a<-table.row.end(a) if(n.orig!=n) { a<-table.row.start(a) a<-table.element(a,'Warning: NAs were removed from the time series! The results shown below will only be correct if the NAs are all located at the start and/or end of the time series.',6,F) a<-table.row.end(a) } for (bigd in 0:2) { for (smalld in 0:3) { mylabel <- 'V(Y[t],d=' mylabel <- paste(mylabel,as.character(smalld),sep='') mylabel <- paste(mylabel,',D=',sep='') mylabel <- paste(mylabel,as.character(bigd),sep='') mylabel <- paste(mylabel,')',sep='') a<-table.row.start(a) a<-table.element(a,mylabel,header=TRUE) myx <- x if (smalld > 0) myx <- diff(myx,lag=1,differences=smalld) if (bigd > 0) myx <- diff(myx,lag=par1,differences=bigd) a<-table.element(a,signif(var(myx), digits=6)) a<-table.element(a,'Range',header=TRUE) a<-table.element(a,signif(max(myx)-min(myx), digits=6)) a<-table.element(a,'Trim Var.',header=TRUE) smyx <- sort(myx) sn <- length(smyx) a<-table.element(a,signif(var(smyx[smyx>quantile(smyx,0.05) & smyx<quantile(smyx,0.95)]), digits=6)) a<-table.row.end(a) } } a<-table.end(a) table.save(a,file='mytable.tab') bitmap(file='pic0.png') op <- par(mfrow=c(2,2)) plot(x,type='l',xlab='time',ylab='value',main='d=0, D=0') plot(diff(x,lag=1,differences=1),type='l',xlab='time',ylab='value',main='d=1, D=0') plot(diff(x,lag=par1,differences=1),type='l',xlab='time',ylab='value',main='d=0, D=1') plot(diff(diff(x,lag=1,differences=1),lag=par1,differences=1),type='l',xlab='time',ylab='value',main='d=1, D=1') par(op) dev.off()
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Big Analytics Cloud Computing Center
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