abun_oi.control: Control parameters in EM algorithm

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

Description

Various parameters that control performing EM algorithm using abun_oi.

Usage

abun_oi.control(
  epsilon = 1e-05,
  maxit = 5000,
  maxN = NULL,
  maxN_ci = 1e+09,
  start_beta = NULL,
  start_eta = NULL
)

Arguments

epsilon	positive convergence tolerance ε. The iterations converge when the increase of the log-EL is less than ε.
maxit	integer specifying the maximal number of iterations.
maxN	number specifying the largest value of N when calculating the estimate of the abundance N. If NULL the default is 100 times the number of individuals captured.
maxN_ci	number specifying the largest value of N when calculating the confidence interval of N.
start_beta	vector specifying the starting value of the coefficient β in count regression model. If NULL the default is zero.
start_eta	vector specifying the starting value of the coefficient η in one-inflated logistic regression model. If NULL the default is zero.

Value

A list with the arguments specified.

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