Semantic Scholar Open Access 2007 893 sitasi

Information criteria for astrophysical model selection

A. Liddle

Lihat Sumber DOI

Abstrak

Model selection is the problem of distinguishing competing models, perhaps featuring different numbers of parameters. The statistics literature contains two distinct sets of tools, those based on information theory such as the Akaike Information Criterion (AIC), and those on Bayesian inference such as the Bayesian evidence and Bayesian Information Criterion (BIC). The Deviance Information Criterion combines ideas from both heritages; it is readily computed from Monte Carlo posterior samples and, unlike the AIC and BIC, allows for parameter degeneracy. I describe the properties of the information criteria, and as an example compute them from Wilkinson Microwave Anisotropy Probe 3-yr data for several cosmological models. I find that at present the information theory and Bayesian approaches give significantly different conclusions from that data.

Topik & Kata Kunci

Physics

Penulis (1)

A. Liddle

Format Sitasi

APA MLA BibTeX

Liddle, A. (2007). Information criteria for astrophysical model selection. https://doi.org/10.1111/j.1745-3933.2007.00306.x

Akses Cepat

Lihat di Sumber doi.org/10.1111/j.1745-3933.2007.00306.x

Informasi Jurnal

Tahun Terbit: 2007
Bahasa: en
Total Sitasi: 893×
Sumber Database: Semantic Scholar
DOI: 10.1111/j.1745-3933.2007.00306.x
Akses: Open Access ✓