loglikelihood_zt: EL log-likelihood under zero-truncated models

In ecnuliuyang/AbunOI: Semiparametric empirical likelihood inference for abundance from one-inflated capture-recapture data

Description

EL log-likelihood under zero-truncated models

Usage

loglikelihood_zt(N, y, x, beta, alpha, prob, dist, K)

Arguments

N	number specifying the value of abundance.
y	number of times that individuals were captured
x	matrix containing the individual covariates which have influence on the capture probability.
beta	vector of regression cofficients in the capture probability model
alpha	number, the probability of never being captured
prob	vector, the probability mass function of covariates
dist	character specification of count regression model family, "poisson" or "binomial".
K	number specifying the number of capture occasions when dist is "binomial".

Value

The value of EL log-likelihood under zero-truncated models.

References

Liu, Y., Li, P., Liu, Y., and Zhang, R. (2021). Semiparametric empirical likelihood inference for abundance from one-inflated capture-recapture data. Biometrical Journal.

ecnuliuyang/AbunOI documentation built on Feb. 13, 2022, 4:32 p.m.