View source: R/prepare_shiftfit.R
prepare_shiftfit | R Documentation |
prepare_shiftfit
prepare_shiftfit( data, shiftfit.model = NULL, diag.var, order.var = diag.var[1] )
data |
data |
shiftfit.model |
shiftfit.model |
diag.var |
diag.var |
order.var |
order.var |
## Not run: data(simulshift) # 1. subsample to a reasonable size subdata <- simulshift[seq(1,30000,by = 100),] # 2. use algorithm from marcher package MWN.fit <- with(subdata, marcher::estimate_shift(T=indice, X=x, Y=y,n.clust = 3)) # 3. convert output MWN.segm <- prepare_shiftfit(subdata,MWN.fit,diag.var = c("x","y")) # 4. use segclust2d functions plot(MWN.segm) plot(MWN.segm,stationarity = TRUE) segmap(MWN.segm) ## End(Not run)
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