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Data:
2.6 2.4 2.5 2.7 3.2 2.8 2.8 3 3.1 3.1 3 2.4 2.7 3 2.7 2.7 2 2.4 2.6 2.4 2.3 2.4 2.5 2.6 2.6 2.6 2.7 2.8 2.6 2.6 2 2 2.1 1.9 2 2.5 2.9 3.3 3.5 3.8 4.6 4.4 5.3 5.8 5.9 5.6 5.8 5.5 4.6 4.2 4 3.5 2.3 2.2 1.4 0.6 0 0.5 0.1 0.1
Seasonal Period
36
12
1
2
3
4
6
12
Chart options
R Code
par1 <- as.numeric(par1) 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) 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(x,lag=1,differences=smalld) if (bigd > 0) myx <- diff(myx,lag=par1,differences=bigd) a<-table.element(a,var(myx)) a<-table.element(a,'Range',header=TRUE) a<-table.element(a,max(myx)-min(myx)) a<-table.element(a,'Trim Var.',header=TRUE) smyx <- sort(myx) sn <- length(smyx) a<-table.element(a,var(smyx[smyx>quantile(smyx,0.05) & smyx<quantile(smyx,0.95)])) a<-table.row.end(a) } } a<-table.end(a) table.save(a,file='mytable.tab')
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