est_uncertainty: linear model of kernel density estimate

In SaskiaSchirmer/CONSURE: Estimating Spatially Continuous Survival, Migratory Connectivity and Recovery Probability

linear model of kernel density estimate

Description

This function estimates the uncertainty of the parameters survival, migratory connectivity and recovery probability by bootstrapping the marking data.

Usage

est_uncertainty(
  mark_recapture_object,
  parameters = c("s", "m", "r"),
  iterations = NULL,
  bootstrap_data = NULL,
  res = NULL,
  filename
)

Arguments

mark_recapture_object	object of class mark_recapture_object (see mark_recapture_object())
parameters	vector of characters specifying the parameter names considered for uncertainty estimation, possible values are s for survival, m for migratory connectivity and r for recovery probability. Defaults to c("s","m","r").
iterations	numeric. Number of bootstraps performed. Defaults to NULL.
bootstrap_data	data prepared by bootstrapMarkingData, offers the option to compute bootstrap in parallel. Defauls to NULL.
res	spatial resolution. Defaults to NULL. If NULL, resolution of the mark_recapture_object$spatial_resolution is used.
filename	(path to file) and filename to store the mark_recapture_object with bootstrap estimates.

Value

mark_recapture_object with added bootstrap uncertainty for parameters

Examples

{
mro  <- mro1D
mro <- est_uncertainty(mro, parameters = "s",
iterations = 1, filename = "test")
}

SaskiaSchirmer/CONSURE documentation built on Sept. 3, 2023, 8:52 a.m.