gaussHermite

Returns <code>(nodes, weights)</code> for approximating \(\int f(x) e^{-x^2} dx\),
ignoring any normalizing constant. This is a simple demonstration; for serious
applications, more robust libraries or expansions might be used.

Provides likelihood-based and hierarchical estimation methods
for thresholded (binomial-probit) data. Supports fixed-mean and random-mean
models with maximum likelihood estimation (MLE), generalized linear mixed model
(GLMM), and Bayesian Markov chain Monte Carlo (MCMC) implementations.
For methodological background, see Albert and Chib (1993)
<doi:10.1080/01621459.1993.10476321> and McCulloch (1994)
<doi:10.2307/2297959>.

Zhaoze Liu

bin2norm

Hierarchical Probit Estimation for Dichotomized Data

gaussHermite function

<dl><dt>n</dt>
<dd>integer number of quadrature points</dd></dl>

Arguments

Minimal Gauss-Hermite Quadrature — gaussHermite

<dl>

<dt>n</dt>
<dd>integer number of quadrature points</dd>

</dl>

gaussHermite: Minimal Gauss-Hermite Quadrature

Description

Usage

Value

Arguments