Title of article :
Pseudo-Likelihood Inference Underestimates Model Uncertainty: Evidence from Bayesian Nearest Neighbours
Author/Authors :
Wanhua, Su Grant MacEwan University - Department of Mathematics and Statistics, Canada , Hugh, Chipman Acadia University - Department of Mathematics and Statistics, Canada , Mu, Zhu University of Waterloo - Department of Statistics and Actuarial Science, Canada
Abstract :
When using the K-nearest neighbours (KNN) method, one often ignores the uncertainty in the choice of K. To account for such uncertainty, Bayesian KNN (BKNN) has been proposed and studied (Holmes and Adams 2002; Cucala et al. 2009). We present some evidence to show that the pseudo-likelihood approach for BKNN, even after being corrected by Cucala et al. (2009), still significantly underestimates model uncertainty
Keywords :
Bootstrap interval , MCMC , posterior interval , pseudolikelihood
Journal title :
Journal of the Iranian Statistical Society (JIRSS)
Journal title :
Journal of the Iranian Statistical Society (JIRSS)
