Bayesian model checking: A comparison of tests

12/20/2017
by   Leon B. Lucy, et al.
0

Two procedures for checking Bayesian models are compared using a simple test problem based on the local Hubble expansion. Over four orders of magnitude, p-values derived from a global goodness-of-fit criterion for posterior probability density functions (Lucy 2017) agree closely with posterior predictive p-values. The former can therefore serve as an effective proxy for the difficult-to-calculate posterior predictive p-values.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/02/2019

Population Predictive Checks

Bayesian modeling has become a staple for researchers analyzing data. Th...
research
01/05/2022

Systematic assessment of the quality of fit of the stochastic block model for empirical networks

We perform a systematic analysis of the quality of fit of the stochastic...
research
04/18/2018

Checking the Model and the Prior for the Constrained Multinomial

The multinomial model is one of the simplest statistical models. When co...
research
03/29/2022

Calibrated Model Criticism Using Split Predictive Checks

Checking how well a fitted model explains the data is one of the most fu...
research
05/09/2021

Statistical Assessment of Replicability via Bayesian Model Criticism

Assessment of replicability is critical to ensure the quality and rigor ...
research
06/06/2018

Check yourself before you wreck yourself: Assessing discrete choice models through predictive simulations

Typically, discrete choice modelers develop ever-more advanced models an...
research
10/04/2021

Posterior predictive model checking using formal methods in a spatio-temporal model

We propose an interdisciplinary framework, Bayesian formal predictive mo...

Please sign up or login with your details

Forgot password? Click here to reset