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Data:
286.1 307 358.1 341.8 378.8 375.2 295.6 362.7 409.6 336.8 389.1 389.3 355.9 542 648.4 452 582.4 506.5 555.5 530.4 609.4 543.9 616.2 634.6 541.7 549.8 627.6 797.4 689.8 1576.6 1572.1 1626.4 1972.4 1509.6 1584.9 1880 1324 1777.7 2172.4 1780.3 2134.9 1838.4 1557 1755.2 1702 1577.5 1485.9 2179.1 1740.9 1724.5 2328.1 1774.1 2224.2 1536.3 1521.2 2051.8 2483.1 1929.8 1808.6 2584.9 1997.9 1639.9 2379.1 1715 2750.9 1865.4 1647.4 2180.4 2593 2057.2 2635.8 2315.4 1863.6 2038 2235.8 2222.1 2636.9 2076.8 1935.5 2086.3 2470.9 1854.6 2041.3 2170.8 1905.5 2130.2 2791.2 2539.7 2661.3 1764.9 2176.9 2458.5 2179 2242.5 2089.6 2661.6 2112 2367.3 2543 2603.9 3146.7 1789.2 2114.8 2236.3 2288.1 2173.2 1877.7 2807.4 2357.4 2107.7 2856.8 2510.8 2875 2229.7 2055.1 2545.4 2775.1 2252.2 2091.7 2433
Seasonal Period
12
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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