lrData

A list of two elements, a matrix "X" and a numeric vector "x". They came from a linear model: x = X*0.3 + epsilon, where epsilon is Gaussian distributed with mean 0 and variance 25.

datasets

A set of frequently used Bayesian parametric and nonparametric model structures, as well as a set of tools for common analytical tasks. Structures include linear Gaussian systems, Gaussian and Normal-Inverse-Wishart conjugate structure, Gaussian and Normal-Inverse-Gamma conjugate structure, Categorical and Dirichlet conjugate structure, Dirichlet Process on positive integers, Dirichlet Process in general, Hierarchical Dirichlet Process ... Tasks include updating posteriors, sampling from posteriors, calculating marginal likelihood, calculating posterior predictive densities, sampling from posterior predictive distributions, calculating "Maximum A Posteriori" (MAP) estimates ... See <https://chenhaotian.github.io/Bayesian-Bricks/> to get started.

Haotian Chen

bbricks

Bayesian Methods and Graphical Model Structures for Statistical
Modeling

lrData function

A list of two elements:<dl class="dl-horizontal">
 <dt>x</dt><dd>: numeric, linear samples</dd>
 <dt>X</dt><dd>: matrix, the "locations" of the linear samples</dd>
</dl>

Format

Samples from a simple linear model — lrData

A list of two elements:<dl class='dl-horizontal'>
 <dt>x</dt><dd>: numeric, linear samples</dd>
 <dt>X</dt><dd>: matrix, the "locations" of the linear samples</dd>
</dl>

lrData: Samples from a simple linear model

Description

Usage

Arguments

Format