bootN: bootN

In dslramsey/eradicate: Functions to support the "eradication tools" shiny app

bootN

Description

bootN estimates abundance from a fitted model for the region covered by the sampled sites. Standard errors and confidence intervals are estimated using a bootstrap procedure by resampling sites.

Usage

bootN(obj, ...)

## S3 method for class 'efitMS'
bootN(obj, B = 50, trim = 0.1, ...)

Arguments

obj	A fitted model object.
B	The number of bootstrap replicates (default = 50). There must by covariate values for every parameter in obj.
trim	The fraction of bootstrap samples to be trimmed before computation of the mean and standard errors. Samples are trimmed symmetrically from the ends of the bootstrap distribution.

Value

a data.frame giving the predictions for each spatial unit as well as the overall abundance estimate for the region with associated SE and confidence intervals.

Examples

 rem<- san_nic_open$removals
 emf <- eFrameMNO(y=rem, numPrimary=8)
 mod <- remMNO(~1, ~1, ~1, ~1, data=emf)
 Nhat<- bootN(mod)

dslramsey/eradicate documentation built on March 16, 2024, 1:40 p.m.