View source: R/NonparTrawlEstimation.R
LebA_slice_est | R Documentation |
This function estimates Leb(A), Leb(A intersection A_h), Leb(A\ A_h).
LebA_slice_est(data, Delta, h, biascor = FALSE)
data |
Data to be used in the trawl function estimation. |
Delta |
Width of the grid on which we observe the data |
h |
Time point used in A intersection A_h and the setdifference A setdifference A_h |
biascor |
A binary variable determining whether a bias correction should be computed, the default is FALSE |
Estimation of the trawl function using the methodology proposed in Sauri and Veraart (2022).
LebA
LebAintersection
LebAsetdifference
##Simulate a trawl process ##Determine the sampling grid my_n <- 5000 my_delta <- 0.1 my_t <- my_n*my_delta ###Choose the model parameter #Exponential trawl function: my_lambda <- 2 #Poisson marginal distribution trawl my_v <- 1 #Set the seed set.seed(1726) #Simulate the trawl process Poi_data<-ambit::sim_weighted_trawl(my_n, my_delta, "Exp", my_lambda, "Poi", my_v)$path #Estimate the trawl set and its two slices at time h=2 without bias correction est1 <- LebA_slice_est(Poi_data, my_delta, h=2) est1$LebA est1$LebAintersection est1$LebAsetdifference #Estimate the trawl set and its two slices at time h=2 without bias correction est2 <- LebA_slice_est(Poi_data, my_delta, h=2, biascor=TRUE) est2$LebA est2$LebAintersection est2$LebAsetdifference #Note that Leb(A)=1/my_lambda for an exponential trawl
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