TY - JOUR
AU - Smith, Brian J.
PY - 2007/11/13
Y2 - 2022/12/03
TI - boa: An R Package for MCMC Output Convergence Assessment and Posterior Inference
JF - Journal of Statistical Software
JA - J. Stat. Soft.
VL - 21
IS - 11
SE - Articles
DO - 10.18637/jss.v021.i11
UR - https://www.jstatsoft.org/index.php/jss/article/view/v021i11
SP - 1 - 37
AB - Markov chain Monte Carlo (MCMC) is the most widely used method of estimating joint posterior distributions in Bayesian analysis. The idea of MCMC is to iteratively produce parameter values that are representative samples from the joint posterior. Unlike frequentist analysis where iterative model fitting routines are monitored for convergence to a single point, MCMC output is monitored for convergence to a distribution. Thus, specialized diagnostic tools are needed in the Bayesian setting. To this end, the R package boa was created. This manuscript presents the user's manual for boa, which outlines the use of and methodology upon which the software is based. Included is a description of the menu system, data management capabilities, and statistical/graphical methods for convergence assessment and posterior inference. Throughout the manual, a linear regression example is used to illustrate the software.
ER -