remMN: remMN

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

remMN

Description

remMN fits multinomial removal models (e.g. Haines 2019, Dorazio et al 2005) to data from a number of primary periods where individuals removed are recorded for each site. Currently supported models include the Poisson, Negative binomial and zero-inflated Poisson (ZIP).

Usage

remMN(lamformula, detformula, data, starts, method="BFGS", se=TRUE, ...)

Arguments

lamformula	formula for the latent abundance component.
detformula	formula for the removal detection component. Only site-level covariates are allowed for the removal detection component. This differs from the similar model in unmarked.
data	A eFrameR object containing the response (counts) and site-level covariates. see eFrameR for how to format the required data.
mixture	model for the latent abundance, either Poisson (P), negative binomial (NB) or zero-inflated Poisson (ZIP).
starts	Initial values for parameters
method	Optimisation method
se	flag to return the standard error (hessian).

Value

a efit model object.

Examples

 rem<- san_nic_rem$rem
 emf <- eFrameR(y=rem)
 mod <- remMN(~1, ~1, data=emf)
 Nhat<- calcN(mod)

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