Intrinsic priors for hypothesis testing in normal regression models.

@article{Moreno2003,
abstract = {Testing that some regression coefficients are equal to zero is an important problem in many applications. Homoscedasticity is not necessarily a realistic condition in this setting and, as a consequence, no frequentist test there exist. Approximate tests have been proposed. In this paper a Bayesian analysis of this problem is carried out, from a default Bayesian model choice perspective. Explicit expressions for intrinsic priors are provided, and it is shown that the corresponding Bayes factor is computed with the help of very simple numerical computations.},
author = {Moreno, Elías, Girón, F. Javier, Torres, Francisco},
journal = {RACSAM},
keywords = {Inferencia paramétrica; Inferencia bayesiana; Distribuciones a priori; Regresión lineal; Contraste de hipótesis},
language = {eng},
number = {1},
pages = {53-61},
title = {Intrinsic priors for hypothesis testing in normal regression models.},
url = {http://eudml.org/doc/40954},
volume = {97},
year = {2003},
}

TY - JOUR
AU - Moreno, Elías
AU - Girón, F. Javier
AU - Torres, Francisco
TI - Intrinsic priors for hypothesis testing in normal regression models.
JO - RACSAM
PY - 2003
VL - 97
IS - 1
SP - 53
EP - 61
AB - Testing that some regression coefficients are equal to zero is an important problem in many applications. Homoscedasticity is not necessarily a realistic condition in this setting and, as a consequence, no frequentist test there exist. Approximate tests have been proposed. In this paper a Bayesian analysis of this problem is carried out, from a default Bayesian model choice perspective. Explicit expressions for intrinsic priors are provided, and it is shown that the corresponding Bayes factor is computed with the help of very simple numerical computations.
LA - eng
KW - Inferencia paramétrica; Inferencia bayesiana; Distribuciones a priori; Regresión lineal; Contraste de hipótesis
UR - http://eudml.org/doc/40954
ER -