M. Escobar

发表

Markov Chain Sampling Methods for Dirichlet Process Mixture Models

M. Escobar, M. West, 2000 .

Bayesian Density Estimation and Inference Using Mixtures

M. Escobar, M. West, 1995 .

Estimating Normal Means with a Dirichlet Process Prior

M. Escobar, 1994 .

Hierarchical priors and mixture models, with applications in regression and density estimation

Michael A. West, Peter Müller, Michael Escobar, 2006 .

The use of the Tobit model for analyzing measures of health status

M. Escobar, P. Austin, J. Kopec, 2004, Quality of Life Research.

A Metropolis-Hastings based method for sampling from the G-Wishart distribution in Gaussian graphical models

Nicholas Mitsakakis, Hélène Massam, Michael Escobar, 2011 .

Nonparametric Bayesian methods in hierarchical models

Michael Escobar, M. Escobar, 1995 .

The use of finite mixture models to estimate the distribution of the health utilities index in the presence of a ceiling effect

M. Escobar, P. Austin, 2003 .

Incidence and estimated rates of residual risk for HIV, hepatitis C, hepatitis B and human T-cell lymphotropic viruses in blood donors in Canada, 1990-2000.

M. Escobar, S. Deeks, P. Driezen, 2003, CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne.

A Time Series-Based Point Estimation of Stop Signal Reaction Times: More Evidence on the Role of Reactive Inhibition-Proactive Inhibition Interplay on the SSRT Estimations †

M. Escobar, K. Knight, R. Schachar, 2020, Brain sciences.

Algorithm AS 262: A Two-Sample Test for Incomplete Multivariate Data

M. Escobar, R. Makuch, S. Merrill, 1991 .

A Bayesian Mixture Modelling of Stop Signal Reaction Time Distributions: The Second Contextual Solution for the Problem of Aftereffects of Inhibition on SSRT Estimations

M. Escobar, R. Schachar, M. Soltanifar, 2020, Brain sciences.

The AL-Gaussian Distribution as the Descriptive Model for the Internal Proactive Inhibition in the Standard Stop Signal Task

M. Escobar, A. Chevrier, M. Soltanifar, 2021 .

Measuring heterogeneity in forensic databases using hierarchical Bayes models

Kathryn Roeder, Michael Escobar, Joseph B. Kadane, 1998 .

Analyzing differences between microbiome communities using mixture distributions

M. Escobar, Wei Xu, K. Shestopaloff, 2018, Statistics in Medicine.

The Asymmetric Laplace Gaussian (ALG) Distribution as the Descriptive Model for the Internal Proactive Inhibition in the Standard Stop Signal Task

M. Escobar, R. Schachar, A. Chevrier, 2021, Brain sciences.

A frequentist mixture modeling of stop signal reaction times

Annie Dupuis, Russell Schachar, Mohsen Soltanifar, 2019, Biostatistics & Epidemiology.

Computing Nonparametric Hierarchical Models

Michael A. West, Michael Escobar, M. Escobar, 1998 .

Mixture models for eye-tracking data: a case study.

D K Pauler, M D Escobar, J A Sweeney, 1996, Statistics in medicine.

Generalised Binomial Models to Examine the Historical Control Assumption in Active Control Equivalence Studies

Robert W. Makuch, Michael Escobar, Michael A. Stephens, 1989 .

Nonparametric statistical inference method for partial areas under receiver operating characteristic curves, with application to genomic studies

Michael Escobar, M. Escobar, Yaohua He, 2008, Statistics in medicine.

Estimating total species using a weighted combination of expected mixture distribution component counts

M. Escobar, W. Xu, K. Shestopaloff, 2020, Environmental and Ecological Statistics.