s.y.rep

<p>A coda object containing simulated values from the posterior predictive distribution of the outcome of a linear regression with fake data (y ~ N(mu, sigma); mu = beta[1] + beta[2] * X; y.rep ~ N(mu, sigma); where y.rep is a replicated outcome, originally missing data). The purpose of the dataset is only to show the possibilities of the ggmcmc package.</p>

datasets

Tools for assessing and diagnosing convergence of
Markov Chain Monte Carlo simulations, as well as for graphically display
results from full MCMC analysis. The package also facilitates the graphical
interpretation of models by providing flexible functions to plot the
results against observed variables, and functions to work with
hierarchical/multilevel batches of parameters
(Fern<c3><a1>ndez-i-Mar<c3><ad>n, 2016 <doi:10.18637/jss.v070.i09>).

Xavier i Marín

ggmcmc

Tools for Analyzing MCMC Simulations from Bayesian Inference

Xavier Fern<c3><a1>ndez i Mar<c3><ad>n

s.y.rep function

<p>A coda object containing posterior distributions of the posterior predictive distribution of a linear regression with fake data.</p>

s.y.rep: Simulations of the posterior predictive distribution of a simple linear regression with fake data.

Description

Usage

Arguments

Format