Testing equality of regression coefficients in heteroscedastic normal regression models

DOI10.1016/j.jspi.2003.12.016zbMath1062.62047OpenAlexW2018805755MaRDI QIDQ1776858

Niranjan Chakravarthy

Publication date: 12 May 2005

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2003.12.016

zbMATH Keywords

Bayes factorsHeteroscedasticityIntrinsic priorsNormal regression models

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Hypothesis testing in multivariate analysis (62H15) Bayesian inference (62F15)

Related Items (13)

Training samples in objective Bayesian model selection. ⋮ Prior distributions for objective Bayesian analysis ⋮ Objective Bayesian methods for one-sided testing ⋮ On intrinsic priors for nonnested models ⋮ A computational approach test for comparing two linear regression models with unequal variances ⋮ A fiducial p-value approach for comparing heteroscedastic regression models ⋮ A consistent on‐line Bayesian procedure for detecting change points ⋮ Accounting for uncertainty in heteroscedasticity in nonlinear regression ⋮ A Bayesian joinpoint regression model with an unknown number of break-points ⋮ Objective Testing Procedures in Linear Models: Calibration of the p‐values ⋮ Objective priors for hypothesis testing in one‐way random effects models ⋮ A Parametric Bootstrap Test for Comparing Heteroscedastic Regression Models ⋮ Bayes Factors for Comparison of Restricted Simple Linear Regression Coefficients

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