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Data:
14731798.37 16471559.62 15213975.95 17637387.4 17972385.83 16896235.55 16697955.94 19691579.52 15930700.75 17444615.98 17699369.88 15189796.81 15672722.75 17180794.3 17664893.45 17862884.98 16162288.88 17463628.82 16772112.17 19106861.48 16721314.25 18161267.85 18509941.2 17802737.97 16409869.75 17967742.04 20286602.27 19537280.81 18021889.62 20194317.23 19049596.62 20244720.94 21473302.24 19673603.19 21053177.29 20159479.84 18203628.31 21289464.94 20432335.71 17180395.07 15816786.32 15071819.75 14521120.61 15668789.39 14346884.11 13881008.13 15465943.69 14238232.92 13557713.21 16127590.29 16793894.2 16014007.43 16867867.15 16014583.21 15878594.85 18664899.14 17962530.06 17332692.2 19542066.35 17203555.19
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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Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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