ambit (version 0.2.3)

LebA_slice_est_approx: Nonparametric estimation of the trawl (sub-) sets Leb(A), Leb(A intersection A_h), Leb(A setdifference A_h)

Description

This function estimates Leb(A), Leb(A intersection A_h), Leb(A\ A_h).

Usage

LebA_slice_est_approx(esttrawl, Delta, h, adjust_neg = FALSE)

Value

LebA

LebAintersection

LebAsetdifference

Arguments

esttrawl

Vector containing estimated trawl function.

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

adjust_neg

A binary variable determining whether negative estimates of the trawl function should be set to 0, the default is FALSE

Details

Estimation of the trawl function using the methodology proposed in Sauri and Veraart (2022).

Examples

# \donttest{
##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
# }