normal_ll

<p>vector of gaussian scale parameter followed by model coefficients</p>

Learning and using the Metropolis algorithm for
Bayesian fitting of a generalized linear model. The package vignette
includes examples of hand-coding a logistic model using several
variants of the Metropolis algorithm. The package also contains R
functions for simulating posterior distributions of Bayesian
generalized linear model parameters using guided, adaptive,
guided-adaptive and random walk Metropolis algorithms. The random walk
Metropolis algorithm was originally described in Metropolis et al
(1953); <doi:10.1063/1.1699114>.

Alexander Keil

normal_ll: Gaussian log likelihood

Description

Usage

Arguments

Value