remGRMS: remGRMS

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

remGRMS

Description

remGRMS fits the generalized removal model to 'stacked' data collected from repeated removal episodes from M sites over T primary periods with each primary consisting of J secondary periods. The model also facilitates the analysis of index (count) data collected in conjunction with the removal data to make joint inference on abundance. Currently supported models include the Poisson and Negative Binomial

Usage

remGRMS(lamformula, detformula, mdetformula, data, mixture = c("P", "NB"), K,
                  starts, method="BFGS", se=TRUE, ...)

Arguments

lamformula	formula for the latent abundance component.
detformula	formula for the removal detection component.
mdetformula	formula for the index detection component.
data	A eFrameGRM object containing the response (counts, index) and site-level covariates. see eFrameGRM for how to format the required data.
K	upper bound for superpopulation abundance
starts	Initial values for parameters
method	Optimisation method
se	flag to return the standard error (hessian).
model	for abundance, either Poisson 'P' or negative binomial 'NB'

Value

a efitGRMS model object.

Examples

 rem<- san_nic_open$removals
 ym<- san_nic_open$index
 emf <- eFrameGRMS(rem, ym)
 mod <- remGRMS(~.season, ~1, ~1, data=emf)
 Nhat<- calcN(mod)

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