Bayesian model comparison can be used to decide whether the introduction of a new parameter is warranted by data. I focus on the Savage-Dickey density ratio as a method to compute the Bayes factor of nested models without carrying out a computationally demanding multi-dimensional integration. I present a new procedure (called "PPOD") to forecast the Bayes factor of a future observation. As an illustration, I consider a few central quantities in the current cosmological concordance model. Copyright © 2006 by Imperial College Press.
Cosmological Bayesian model selection / Trotta, R.. - 1:(2006), pp. 15-18. (Intervento presentato al convegno 5th Statistical Problems in Particle Physics, Astrophysics and Cosmology Conference, PHYSTAT 2005 tenutosi a Oxford, gbr nel 2005) [10.1142/9781860948985_0004].
Cosmological Bayesian model selection
Trotta R.
2006-01-01
Abstract
Bayesian model comparison can be used to decide whether the introduction of a new parameter is warranted by data. I focus on the Savage-Dickey density ratio as a method to compute the Bayes factor of nested models without carrying out a computationally demanding multi-dimensional integration. I present a new procedure (called "PPOD") to forecast the Bayes factor of a future observation. As an illustration, I consider a few central quantities in the current cosmological concordance model. Copyright © 2006 by Imperial College Press.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
