This function returns a blockmatrix object containing the gaussian cross-correlation matrices.
This function returns a blockmatrix object containing the gaussian cross-correlation matrices.
CCGammaToBlockmatrix(data, lag =0, p =3,...)
Arguments
data: data frame or 'zoo' R object containing daily precipitation time series for several gauges (one gauge time series per column). See CCGamma.
lag: numeric (expressed as number of days) used for the element [1,1] of the returned blockmatrix.
p: numeric order p of the auto-regeression
...: further argments of CCGamma
Returns
A blockmatrix object containing the gaussian cross-correlation matrices.
Details
This a wrapper for CCGamma with the option only.matrix=TRUE and the function value is transformed into a blockmatrix object.
Examples
data(trentino)year_min <-1961year_max <-1990period <- PRECIPITATION$year>=year_min & PRECIPITATION$year<=year_max
station <- names(PRECIPITATION)[!(names(PRECIPITATION)%in% c("day","month","year"))]prec_mes <- PRECIPITATION[period,station]## removing nonworking stations (e.g. time series with NA)accepted <- array(TRUE,length(names(prec_mes)))names(accepted)<- names(prec_mes)for(it in names(prec_mes)){ accepted[it]<-(length(which(!is.na(prec_mes[,it])))==length(prec_mes[,it]))}prec_mes <- prec_mes[,accepted]## the dateset is reduced!!! prec_mes <- prec_mes[,1:2]p <-1## try p <- 2 !!! CCGamma <- CCGammaToBlockmatrix(data=prec_mes,lag=0,p=p,tolerance=0.001)## Not Run in the examples, uncomment to run the following line CCGamma_1 <- CCGammaToBlockmatrix(data=prec_mes,lag=1,p=p,tolerance=0.001)### Alternatively, recommended ..... ## Not Run in the examples, uncomment to run the following line CCGamma <- CCGammaToBlockmatrix(data=prec_mes,lag=0,p=p+1,tolerance=0.001) CCGamma0 <- CCGamma[1:p,1:p] CCGamma1 <- CCGamma[(1:p),(1:p)+1] CCGamma0_inv <- solve(CCGamma0)## Not Run in the examples, uncomment to run the following linea1 <- blockmatmult(CCGamma0,CCGamma0_inv)a2 <- blockmatmult(CCGamma1,CCGamma0_inv)CCGamma_1t <- t(CCGamma1)CCGamma_0t <- t(CCGamma0) A <- t(solve(CCGamma_0t,CCGamma_1t))