Case-deletion importance sampling estimators: Central limit theorems and related results (2008)
Epifani, Ilenia, MacEachern, Steven N., Peruggia, Mario
Case-deleted analysis is a popular method for evaluating the influence of a subset of cases on inference. The use of Monte Carlo estimation strategies in complicated Bayesian settings leads naturally...
Ergodic Distributions of Random Dynamical Systems (2007)
L. Mark Berliner, Steven N. Maceachern, Catherine Scipione Forbes
. Typical analyses of data obtained from randomly perturbed dynamical systems rely on the assumption of a stationary ergodic distribution. Though rich theoretical results concerning existence are...
Regularization of Case-Specific Parameters for Robustness and Efficiency (2007)
Yoonkyung Lee, The Ohio, Steven N. Maceachern, Yoonkyung Lee, Steven N. Maceachern, Yoonsuh Jung
Regularization methods allow one to handle a variety of inferential problems where there are more covariates than cases. This allows one to consider a potentially enormous number of covariates for a...
in BIOSTATISTICS c ○ Copyright by (2006)
Steven N. Maceachern, Daniel Janies, Liang Liu
The desire to infer the evolutionary history of a group of species should be more viable now that a considerable amount of multilocus molecular data is available. However, the current molecular...
Spatial Nonparametric Bayesian Models (2001)
Steven N. Maceachern, Athanasios Kottas, Alan E. Gelf
The prior distribution is an essential ingredient of any Bayesian analysis, and it plays a major role in determining the final results. As such, Bayesians attempt
Spatial Nonparametric Bayesian Models (2001)
Steven N. Maceachern, Athanasios Kottas, Alan E. Gelf
The prior distribution is an essential ingredient of any Bayesian analysis, and it plays a major role in determining the final results. As such, Bayesians attempt to use prior distributions that have...
Sequential Importance Sampling for Nonparametric Bayes Models: The Next Generation (1998)
Steven N. Maceachern, Merlise Clyde, Jun S. Liu
this paper, we exploit the similarities between the Gibbs sampler and the SIS, bringing over the improvements for Gibbs sampling algorithms to the SIS setting for nonparametric Bayes problems. These...
Sequential Importance Sampling for Nonparametric Bayes Models: The Next Generation (1998)
Steven N. Maceachern, Merlise Clyde, Jun S. Liu
this paper, we exploit the similarities between the Gibbs sampler and the SIS, bringing over the improvements for Gibbs sampling algorithms to the SIS setting for nonparametric Bayes problems. These...
Classification via kernel product estimators (1998)
COOLEY, CRAIG A., MACEACHERN, STEVEN N.
Multivariate kernel density estimation is often used as the basis for a nonparametric classification technique. However, the multivariate kernel classifier suffers from the curse of dimensionality,...
Bayesian Variable Selection for Proportional Hazards Models (1996)
Joseph G. Ibrahim, Ming-hui Chen, Steven N. Maceachern
The authors consider the problem of Bayesian variable selection for proportional hazards regression models with right censored data. They propose a semi-parametric approach in which a nonparametric...
A semiparametric Bayesian model for randomised block designs (1996)
BUSH, CHRISTOPHER A., MACEACHERN, STEVEN N.
A model is proposed for a Bayesian semiparametric analysis of randomised block experiments. The model is a hierarchical model in which a Dirichlet process is inserted at the middle stage for the...
A new ranked set sample estimator of variance
Steven N. MacEachern, Ömer Öztürk, Douglas A. Wolfe, Gregory V. Stark
We develop an unbiased estimator of the variance of a population based on a ranked set sample. We show that this new estimator is better than estimating the variance based on a simple random sample...
An ANOVA Model for Dependent Random Measures
De Iorio, Maria, Muller, Peter, Rosner, Gary L., MacEachern, Steven N.
Subsampling the Gibbs sampler: variance reduction
MacEachern, Steven N., Peruggia, Mario
Subsampling the output of a Gibbs sampler in a non-systematic fashion can improve the efficiency of marginal estimators if the subsampling strategy is tied to the actual updates made. We illustrate...
Examples of inconsistent Bayes procedures based on observations on dynamical systems
Berliner, L. Mark, MacEachern, Steven N.
We consider observations from distributions whose parameters evolve according to dynamical systems. Under conditions on the prior distribution for the unknown initial condition, it is shown that the...