scholarly journals Accelerated Bayesian model-selection and parameter-estimation in continuous gravitational-wave searches with pulsar-timing arrays

2014 ◽  
Vol 90 (10) ◽  
Author(s):  
Stephen Taylor ◽  
Justin Ellis ◽  
Jonathan Gair
Keyword(s):  
Parameter Estimation ◽  
Model Selection ◽  
Gravitational Wave ◽  
Bayesian Model ◽  
Bayesian Model Selection ◽  
Pulsar Timing

The Survivor Problem Continued: Introduction to Bayesian Model Selection

2019 ◽  
pp. 308-324
Author(s):  
Therese M. Donovan ◽  
Ruth M. Mickey
Keyword(s):  
Parameter Estimation ◽  
Model Selection ◽  
Bayesian Model ◽  
Formal Education ◽  
Deviance Information Criterion ◽  
Information Criterion ◽  
Bayesian Model Selection ◽  
Assessment Model ◽  
Model Fit ◽  
Model Assessment

This chapter provides a very brief introduction to Bayesian model selection. The “Survivor Problem” is expanded in this chapter, where the focus is now on comparing two models that predict how long a contestant will last in a game of Survivor: one model uses years of formal education as a predictor, and a second model uses grit as a predictor. Gibbs sampling is used for parameter estimation. Deviance Information Criterion (commonly abbreviated as DIC) is used as a guide for model selection. Details of how this measure is computed are described. The chapter also discusses model assessment (model fit) and Occam’s razor.

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