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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