Steve MacEachern | Academic Influence

Steve MacEachern's AcademicInfluence.com Rankings

Steve MacEachern

Mathematics

#8148

World Rank

#11065

Historical Rank

#2168

USA Rank

Statistics

#1141

World Rank

#1246

Historical Rank

#225

USA Rank

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Mathematics

Steve MacEachern's Degrees

PhD Statistics University of California, Berkeley
Masters Statistics University of California, Berkeley
Bachelors Mathematics University of California, Berkeley

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Why Is Steve MacEachern Influential?

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According to Wikipedia, Steve MacEachern is an American Statistician. MacEachern is a Distinguished Arts & Sciences Professor of Statistics at the Ohio State University. He received his B.A. in Mathematics from Carleton College in 1982 and his Ph.D. in Statistics from the University of Minnesota in 1988. His doctoral work focused on nonparametric Bayesian methods under the guidance of Don Berry. MacEachern joined the faculty at Ohio State in 1988 and has been a member of the Department of Statistics ever since. He has a courtesy appointment as a Professor in the Department of Psychology. He is best known for Bayesian modeling and computation, with a particular emphasis on dependent Dirichlet processes. He has published extensively in leading statistical journals, and his work has had a significant impact on the field.

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Steve MacEachern's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Estimating mixture of dirichlet process models (1998) (657)
Estimating normal means with a conjugate style dirichlet process prior (1994) (477)
Bayesian Nonparametric Spatial Modeling With Dirichlet Process Mixing (2005) (399)
An ANOVA Model for Dependent Random Measures (2004) (363)
A semiparametric Bayesian model for randomised block designs (1996) (360)
Sequential importance sampling for nonparametric Bayes models: The next generation (1999) (240)
Subsampling the Gibbs Sampler (1994) (149)
Computational Methods for Mixture of Dirichlet Process Models (1998) (124)
Decision Theoretic Aspects of Dependent Nonparametric Processes (2000) (122)
A new ranked set sample estimator of variance (2002) (117)
Bayesian variable selection for proportional hazards models (1999) (76)
Judgement Post‐Stratification with Imprecise Rankings (2004) (72)
Nonparametric Two-Sample Methods for Ranked-Set Sample Data (2006) (65)
Efficient MCMC Schemes for Robust Model Extensions Using Encompassing Dirichlet Process Mixture Models (2000) (58)
Regularization of Case-Specific Parameters for Robustness and Efficiency (2012) (46)
Sequential sampling models of choice: Some recent advances (2008) (42)
Low cancer incidence rates in Ohio Amish (2009) (40)
The Dependent Dirichlet Process and Related Models (2020) (36)
Case-deletion importance sampling estimators: Central limit theorems and related results (2008) (35)
Nonparametric Bayesian modelling for item response (2008) (27)
Bayesian Models for Non‐linear Autoregressions (1997) (26)
Importance Link Function Estimation for Markov Chain Monte Carlo Methods (2000) (26)
SPATIAL NONPARAMETRIC BAYESIAN MODELS (2001) (25)
A nonparametric Bayesian model for inference in related longitudinal studies (2005) (24)
Classification via kernel product estimators (1998) (24)
Landmark-Constrained Elastic Shape Analysis of Planar Curves (2017) (22)
Bayesian Density Estimation and Inference Using Mixtures (2007) (21)
A Robust-Likelihood Cumulative Sum Chart (2007) (20)
A Probit Model with Structured Covariance for Similarity Effects and Source of Volume Calculations (2015) (20)
Judgement Post‐Stratification for Designed Experiments (2008) (20)
Order restricted randomized designs for control versus treatment comparison (2004) (17)
Minimally informative prior distributions for non‐parametric Bayesian analysis (2010) (16)
The Dependent Poisson Race Model and Modeling Dependence in Conjoint Choice Experiments (2008) (16)
Semiparametric Bayesian approaches to systems factorial technology (2016) (16)
Introduction to Statistical Thought (2006) (15)
Bayesian Restricted Likelihood Methods: Conditioning on Insufficient Statistics in Bayesian Regression (2018) (15)
Subsampling the Gibbs sampler: variance reduction (2000) (15)
Nonparametric Bayesian methods: a gentle introduction and overview (2016) (13)
Bayesian Synthesis: Combining subjective analyses, with an application to ozone data (2011) (13)
Robustness to the unavailability of data in the linear model, with applications (1995) (13)
Unbalanced Ranked Set Sampling for Estimating A Population Proportion Under Imperfect Rankings (2009) (12)
Efficient quantile regression for heteroscedastic models (2014) (12)
Order restricted randomized designs and two sample inference (2007) (10)
Effect of surgical site infection on survival after limb amputation in the curative‐intent treatment of canine appendicular osteosarcoma: a Veterinary Society of Surgical Oncology retrospective study (2018) (9)
Preregistration of Modeling Exercises May Not Be Useful (2019) (9)
Inference functions in high dimensional Bayesian inference (2014) (9)
Transformations and Bayesian density estimation (2016) (9)
The Generalized Multiset Sampler (2015) (9)
Restricting exchangeable nonparametric distributions (2012) (8)
Aperiodic Chaotic Orbits (1993) (8)
Consistency of Bayes estimators without the assumption that the model is correct (2011) (8)
Sequential importance sampling for (1999) (7)
Asymptotics of Lower Dimensional Zero-Density Regions (2020) (6)
Clustered Bayesian Model Averaging (2013) (6)
Assessing Convergence and Mixing of MCMC Implementations via Stratification (2012) (6)
Examples of inconsistent Bayes procedures based on observations on dynamical systems (1993) (6)
Asymptotic inference for dynamical systems observed with error (1995) (6)
Reconciling Curvature and Importance Sampling Based Procedures for Summarizing Case Influence in Bayesian Models (2018) (6)
Block Hyper-g Priors in Bayesian Regression (2014) (6)
Economic variable selection (2019) (6)
Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model (2015) (6)
Bayesian Tools for EDA and Model Building: A Brainy Study (2002) (6)
A conditional Lindley paradox in Bayesian linear models (2016) (5)
Parametric and semiparametric hypotheses in the linear model (2011) (5)
Covariance Decompositions for Accurate Computation in Bayesian Scale-Usage Models (2012) (5)
Calibrated Bayes factors for model comparison (2019) (4)
Local-Mass Preserving Prior Distributions for Nonparametric Bayesian Models (2014) (4)
Bandwidth Selection for Kernel Density Estimation with a Markov Chain Monte Carlo Sample (2016) (4)
A class of generalized linear mixed models adjusted for marginal interpretability (2020) (4)
Bayesian Nonparametric Survival Analysis: A Comparison of the Kaplan-Meier and Berliner-Hill Estimators (1992) (4)
ANOVA DDP Models: A Review (2003) (4)
Bayesian Synthesis (2007) (3)
ISOTONIC MAXIMUM LIKELIHOOD ESTIMATION FOR THE CHANGE POINT OF A HAZARD RATE (1997) (3)
Robust Inference via the Blended Paradigm (2012) (3)
Efficient Estimation of Mixture of Dirichlet Process Models (1994) (3)
Comment on article by Jain and Neal (2007) (3)
The Dependent Poisson Race Model and Modeling Dependence in Conjoint Choice Experiments (2007) (3)
Benchmark Estimation for Markov chain Monte Carlo Samples (2004) (3)
Prior elicitation in the classification problem (1999) (2)
Introduction to Statistical Thought. Michael Lavine (2006) (2)
Generalized Poststratification and Importance Sampling for Subsampled Markov Chain Monte Carlo Estimation (2006) (2)
An evaluation of bayes posterior probability regions for a survival curve (1993) (2)
Inference Based on General Linear Models for Order Restricted Randomization (2013) (2)
Marginally Interpretable Generalized Linear Mixed Models (2016) (2)
A characterization of some conjugate prior distributions for exponential families (1993) (2)
An Easy Ridiculous Unbiased Estimator (1993) (2)
Aggregated pairwise classification of elastic planar shapes (2021) (1)
BOOK REVIEW: Kendall's Advanced Theory Of Statistics. Vol 2B: Bayesian Inference. Anthony O'Hagan, Edward Arnold, London, 1994. No. of pages: 330. Price: £35. ISBN: 0-340-52922-9 (1997) (1)
Discussion on the paper by Kong, McCullagh, Meng, Nicolae and Tan (2003) (1)
Ergodic distributions of random dynamical systems (1997) (1)
A regression approach to the two-dataset problem (2019) (1)
Modified check loss for efficient estimation via model selection in quantile regression (2020) (1)
Variable Selection and Function Estimation in Additive Nonparametric Regression Using a Data-Based Prior: Comment (1999) (1)
Superset model problem (2022) (0)
Rediscovering a little known fact about the t-test: algebraic, geometric and distributional considerations. (2019) (0)
A brief note on the t-test (2019) (0)
HIERARCHICAL MODELS FOR RESPONSE TO THE BUSINESS AND ECONOMIC CENSUSES (2002) (0)
JSM 2012: Call for Contributed Abstracts (2011) (0)
Seminars on Statistics in Marketing and Psychology, Winter 2008 Research seminars in Marketing, Psychology and Statistics on WEDNES- (2008) (0)
7th Workshop on Bayesian Nonparametrics (2009) (0)
JSM 2012 session highlights (2012) (0)
Bridging the design and modeling of causal inference: A Bayesian nonparametric perspective (2023) (0)
Locally-Weighted Elastic Comparison of Planar Shapes (2018) (0)
Familial Inference (2022) (0)
A new proof of the stick-breaking representation of Dirichlet processes (2020) (0)
Shape-constrained semiparametric additive stochastic volatility models (2019) (0)
Rediscovering a little known fact about the t-test: algebraic, geometric, distributional and graphical considerations (2019) (0)
Bayesian Model Calibration and Sensitivity Analysis for Oscillating Biological Experiments (2021) (0)
Efficient Model Selection in Linear and Non-Linear Quantile Regression by Cross-Validation (2016) (0)
A Discussion of the Paper " Using Wavelet-based Functional Mixed Models to Characterize Population Heterogeneity in Accelerometer Profiles: a Case (2008) (0)
Aggregated Pairwise Classification of Statistical Shapes (2019) (0)
Rediscovering a little known fact about the t-test and the F-test: Algebraic, Geometric, Distributional and Graphical Considerations (2019) (0)
Benchmark Estimation for Markov Chain (2016) (0)
Toward Rational Social Decisions: A Review and Some Results (2014) (0)
A robust latent CUSUM chart for monitoring customer attrition (2022) (0)
Ergodic Distributions of Random Dynamical SystemsL (2007) (0)
31 ANOVA DDP Models : A Review (0)
Empirical likelihood for the analysis of experimental designs (2021) (0)
On the two-dataset problem. (2019) (0)

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