ic.all

A list of character vectors, with each
  vector containing column names from the associated
  log-linear design matrix. For example, see the output of
  <code><a href="/link/make.hierarchical.term.sets?package=lllcrc&version=1.1" rd-options="" data-mini-rdoc="lllcrc::make.hierarchical.term.sets">make.hierarchical.term.sets</a>()</code>.

models

ddat

The information criterion, such as AIC, AICc,
  BIC, or BICpi.

Logical: TRUE means that beta0 will be
  adjusted so that the log-linear model corresponds to cell
  probabilities instead of expected cell counts.

normalized

Given several sets of log-linear terms, compute the IC
corresponding to each model.

Applies local log-linear capture-recapture models (LLLMs) a for
    closed populations, as described in the ongoing doctoral thesis work of
    Zachary Kurtz in the department of statistics at Carnegie Mellon
    University.  The method is relevant when there are 3-4 capture occasions,
    with auxiliary covariates available for all capture occasions.  As part of
    estimating the number of missing population units, the method estimates the
    "rate of missingness" as it varies over the covariate space.  In addition,
    user-friendly functions are provided to recreate (approximately) the method
    of Zwane and Van der Heijden (2004), which applied the VGAM package in a
    way that is closely related to LLLMs.

ic.all: Compute an IC for several LLMs

Description

Usage

Arguments

Value