Steven N. MacEachern - Publications

Affiliations: 
Ohio State University, Columbus, Columbus, OH 
Area:
Statistics

53/70 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2020 Jung Y, MacEachern SN, Kim HJ. Modified check loss for efficient estimation via model selection in quantile regression Journal of Applied Statistics. 1-21. DOI: 10.1080/02664763.2020.1753023  0.8
2016 Houpt JW, MacEachern SN, Peruggia M, Townsend JT, Van Zandt T. Semiparametric Bayesian approaches to systems factorial technology Journal of Mathematical Psychology. DOI: 10.1016/J.Jmp.2016.02.008  1
2015 Xu Z, MacEachern S, Xu X. Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model. Ieee Transactions On Pattern Analysis and Machine Intelligence. 37: 372-82. PMID 26353248 DOI: 10.1109/Tpami.2013.222  0.48
2015 Kim HJ, MacEachern SN. The Generalized Multiset Sampler Journal of Computational and Graphical Statistics. 24: 1134-1154. DOI: 10.1080/10618600.2014.962701  1
2015 Jung Y, Lee Y, MacEachern SN. Efficient quantile regression for heteroscedastic models Journal of Statistical Computation and Simulation. 85: 2548-2568. DOI: 10.1080/00949655.2014.967244  1
2014 Lee J, MacEachern SN. Inference functions in high dimensional Bayesian inference Statistics and Its Interface. 7: 477-486. DOI: 10.4310/Sii.2014.V7.N4.A5  1
2014 Kadane JB, MacEachern SN. Toward rational social decisions: A review and some results Bayesian Analysis. 9: 685-698. DOI: 10.1214/14-Ba876  1
2014 Lee J, MacEachern SN, Lu Y, Mills GB. Local-mass preserving prior distributions for nonparametric bayesian models Bayesian Analysis. 9: 307-330. DOI: 10.1214/13-Ba857  1
2014 MacEachern SN. Contributed discussion on article by Finegold and Drton: Comment by Steven N. MacEachern Bayesian Analysis. 9: 574-576. DOI: 10.1214/13-Ba856D  1
2013 Yu Q, MacEachern SN, Peruggia M. Clustered bayesian model averaging Bayesian Analysis. 8: 883-908. DOI: 10.1214/13-Ba859  1
2013 Ozturk O, Maceachern SN. Inference based on general linear models for order restricted randomization Communications in Statistics - Theory and Methods. 42: 2543-2566. DOI: 10.1080/03610926.2011.624246  1
2013 Williamson SA, MacEachern SN, Xing EP. Restricting exchangeable nonparametric distributions Advances in Neural Information Processing Systems 1
2012 Lee Y, MacEachern SN, Jung Y. Regularization of case-specific parameters for robustness and efficiency Statistical Science. 27: 350-372. DOI: 10.1214/11-Sts377  1
2012 Hans C, Allenby GM, Craigmile PF, Lee J, MacEachern SN, Xu X. Covariance decompositions for accurate computation in Bayesian scale-usage models Journal of Computational and Graphical Statistics. 21: 538-557. DOI: 10.1080/10618600.2012.672087  1
2012 Paul R, MacEachern SN, Berliner LM. Assessing convergence and mixing of MCMC implementations via stratification Journal of Computational and Graphical Statistics. 21: 693-712. DOI: 10.1080/10618600.2012.663293  1
2011 Yu Q, MacEachern SN, Peruggia M. Bayesian synthesis: Combining subjective analyses, with an application to ozone data Annals of Applied Statistics. 5: 1678-1698. DOI: 10.1214/10-Aoas444  1
2011 Lee J, MacEachern SN. Consistency of Bayes estimators without the assumption that the model is correct Journal of Statistical Planning and Inference. 141: 748-757. DOI: 10.1016/J.Jspi.2010.07.022  1
2011 Maceachern SN, Guha S. Parametric and semiparametric hypotheses in the linear model Canadian Journal of Statistics. 39: 165-180. DOI: 10.1002/Cjs.10091  1
2010 Westman JA, Ferketich AK, Kauffman RM, MacEachern SN, Wilkins JR, Wilcox PP, Pilarski RT, Nagy R, Lemeshow S, de la Chapelle A, Bloomfield CD. Low cancer incidence rates in Ohio Amish. Cancer Causes & Control : Ccc. 21: 69-75. PMID 19779840 DOI: 10.1007/S10552-009-9435-7  1
2010 Bush CA, Lee J, MacEachern SN. Minimally informative prior distributions for non-parametric Bayesian analysis Journal of the Royal Statistical Society. Series B: Statistical Methodology. 72: 253-268. DOI: 10.1111/J.1467-9868.2009.00735.X  1
2009 Chen H, Stasny EA, Wolfe DA, MacEachern SN. Unbalanced ranked set sampling for estimating a population proportion under imperfect rankings Communications in Statistics - Theory and Methods. 38: 2116-2125. DOI: 10.1080/03610920802677208  1
2008 Du J, MacEachern SN. Judgement post-stratification for designed experiments. Biometrics. 64: 345-54. PMID 17888038 DOI: 10.1111/J.1541-0420.2007.00898.X  1
2008 Epifani I, MacEachern SN, Peruggia M. Case-deletion importance sampling estimators: Central limit theorems and related results Electronic Journal of Statistics. 2: 774-806. DOI: 10.1214/08-Ejs259  0.72
2008 MacEachern SN. The nested Dirichlet process: Commentary Journal of the American Statistical Association. 103: 1149-1151. DOI: 10.1198/016214508000000607  1
2008 Duncan KA, MacEachern SN. Nonparametric Bayesian modelling for item response Statistical Modelling. 8: 41-66. DOI: 10.1177/1471082X0700800104  1
2008 Ruan S, MacEachern SN, Otter T, Dean AM. The dependent poisson race model and modeling dependence in conjoint choice experiments Psychometrika. 73: 261-288. DOI: 10.1007/S11336-007-9035-Y  1
2008 Otter T, Johnson J, Rieskamp J, Allenby GM, Brazell JD, Diederich A, Hutchinson JW, MacEachern S, Ruan S, Townsend J. Sequential sampling models of choice: Some recent advances Marketing Letters. 19: 255-267. DOI: 10.1007/S11002-008-9039-0  1
2007 MacEachern SN. Comment on article by Jain and Neal Bayesian Analysis. 2: 483-494. DOI: 10.1214/07-Ba219C  1
2007 MacEachern SN, Rao Y, Wu C. A robust-likelihood cumulative sum chart Journal of the American Statistical Association. 102: 1440-1447. DOI: 10.1198/016214507000001102  1
2007 Ozturk O, MacEachern SN. Order restricted randomized designs and two sample inference Environmental and Ecological Statistics. 14: 365-381. DOI: 10.1007/S10651-007-0023-2  1
2006 Guha S, Maceachern SN. Generalized poststratification and importance sampling for subsampled Markov chain Monte Carlo estimation Journal of the American Statistical Association. 101: 1175-1184. DOI: 10.1198/016214506000000474  1
2006 Fligner MA, MacEachern SN. Nonparametric two-sample methods for ranked-set sample data Journal of the American Statistical Association. 101: 1107-1118. DOI: 10.1198/016214506000000410  1
2005 Gelfand AE, Kottas A, Maceachern SN. Bayesian nonparametric spatial modeling with dirichlet process mixing Journal of the American Statistical Association. 100: 1021-1035. DOI: 10.1198/016214504000002078  1
2005 Müller P, Rosner GL, De Iorio M, MacEachern S. A nonparametric Bayesian model for inference in related longitudinal studies Journal of the Royal Statistical Society. Series C: Applied Statistics. 54: 611-626. DOI: 10.1111/J.1467-9876.2005.05475.X  1
2004 MacEachern SN, Stasny EA, Wolfe DA. Judgement post-stratification with imprecise rankings. Biometrics. 60: 207-15. PMID 15032791 DOI: 10.1111/J.0006-341X.2004.00144.X  1
2004 Guha S, MacEachern SN, Peruggia M. Benchmark estimation for Markov Chain Monte Carlo samples Journal of Computational and Graphical Statistics. 13: 683-701. DOI: 10.1198/106186004X2598  1
2004 De Iorio M, Müller P, Rosner GL, MacEachern SN. An ANOVA Model for Dependent Random Measures Journal of the American Statistical Association. 99: 205-215. DOI: 10.1198/016214504000000205  1
2004 Ozturk O, Maceachern SN. Order restricted randomized designs for control versus treatment comparison Annals of the Institute of Statistical Mathematics. 56: 701-720. DOI: 10.1007/Bf02506484  1
2003 Evans M, Robert CP, Davison AC, Jiang W, Tanner MA, Doss H, Qin J, Fokianos K, MacEachern SN, Peruggia M, Guha S, Chib S, Ritov Y, Robins JM, Vardi Y. Discussion on the paper by Kong, McCullagh, Meng, Nicolas and Tan Journal of the Royal Statistical Society. Series B: Statistical Methodology. 65: 604-618. DOI: 10.1111/1467-9868.00405  1
2002 MacEachern SN, Öztürk O, Wolfe DA, Stark GV. A new ranked set sample estimator of variance Journal of the Royal Statistical Society. Series B: Statistical Methodology. 64: 177-188. DOI: 10.1111/1467-9868.00331  1
2000 MacEachern SN, Peruggia M. Importance link function estimation for Markov chain Monte Carlo methods Journal of Computational and Graphical Statistics. 9: 99-121. DOI: 10.1080/10618600.2000.10474868  1
2000 MacEachern SN, Peruggia M. Subsampling the Gibbs sampler: Variance reduction Statistics and Probability Letters. 47: 91-98. DOI: 10.1080/00031305.1994.10476054  1
2000 MacEachern SN, Peruggia M. Subsampling the Gibbs sampler: Variance reduction Statistics and Probability Letters. 47: 91-98. DOI: 10.1016/S0167-7152(99)00142-X  1
1999 Ibrahim JG, Chen MH, MacEachern SN. Bayesian variable selection for proportional hazards models Canadian Journal of Statistics. 27: 701-717. DOI: 10.2307/3316126  1
1999 Cooley CA, MacEachern SN. Prior elicitation in the classification problem Canadian Journal of Statistics. 27: 299-313. DOI: 10.2307/3315640  1
1999 MacEachern SN, Clyde M, Liu JS. Sequential importance sampling for nonparametric Bayes models: The next generation Canadian Journal of Statistics. 27: 251-267. DOI: 10.2307/3315637  1
1999 MacEachern SN, Shen X. Variable Selection and Function Estimation in Additive Nonparametric Regression Using a Data-Based Prior: Comment Journal of the American Statistical Association. 94: 799. DOI: 10.2307/2669993  0.36
1998 Cooley CA, Maceachern SN. Classification via kernel product estimators Biometrika. 85: 823-833. DOI: 10.1093/Biomet/85.4.823  1
1998 MacEachern SN, Müller P. Estimating mixture of Dirichlet process models Journal of Computational and Graphical Statistics. 7: 223-238. DOI: 10.1080/10618600.1998.10474772  1
1996 Bush CA, MacEachern SN. A semiparametric Bayesian model for randomised block designs Biometrika. 83: 275-285. DOI: 10.1093/Biomet/83.2.275  1
1995 MacEachern SN, Notz WI, Whittinghill DC, Zhu Y. Robustness to the unavailability of data in the linear model, with applications Journal of Statistical Planning and Inference. 48: 207-213. DOI: 10.1016/0378-3758(95)00002-Q  1
1995 MacEachern SN, Berliner LM. Asymptotic inference for dynamical systems observed with error Journal of Statistical Planning and Inference. 46: 277-292. DOI: 10.1016/0378-3758(94)00117-E  1
1993 Berliner LM, MacEachern SN. Examples of inconsistent Bayes procedures based on observations on dynamical systems Statistics and Probability Letters. 17: 355-360. DOI: 10.1016/0167-7152(93)90255-H  1
Low-probability matches
2020 Gory JJ, Craigmile PF, MacEachern SN. A class of generalized linear mixed models adjusted for marginal interpretability. Statistics in Medicine. PMID 33094523 DOI: 10.1002/sim.8782  0.08
2020 Lee J, MacEachern SN. A new proof of the stick-breaking representation of Dirichlet processes Journal of the Korean Statistical Society. 49: 389-394. DOI: 10.1007/S42952-019-00008-W  0.12
2019 Yin J, Craigmile PF, Xu X, MacEachern S. Shape-constrained semiparametric additive stochastic volatility models Statistical Theory and Related Fields. 3: 71-82. DOI: 10.1080/24754269.2019.1573410  0.01
2019 Xu X, Lu P, MacEachern SN, Xu R. Calibrated Bayes factors for model comparison Journal of Statistical Computation and Simulation. 89: 591-614. DOI: 10.1080/00949655.2018.1563091  0.48
2018 Hans EC, Pinard C, van Nimwegen SA, Kirpensteijn J, Singh A, MacEachern S, Naber S, Dudley RM. 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. Veterinary Surgery : Vs. PMID 30303552 DOI: 10.1111/Vsu.13105  0.01
2018 Thomas ZM, MacEachern SN, Peruggia M. Reconciling Curvature and Importance Sampling Based Procedures for Summarizing Case Influence in Bayesian Models Journal of the American Statistical Association. 113: 1669-1683. DOI: 10.1080/01621459.2017.1360777  0.01
2017 Strait J, Kurtek S, Bartha E, MacEachern SN. Landmark-Constrained Elastic Shape Analysis of Planar Curves Journal of the American Statistical Association. 112: 521-533. DOI: 10.1080/01621459.2016.1236726  0.01
2016 MacEachern SN. Nonparametric Bayesian methods: a gentle introduction and overview Communications For Statistical Applications and Methods. 23: 445-466. DOI: 10.5351/Csam.2016.23.6.445  0.01
2016 Bean A, Xu X, MacEachern S. Transformations and Bayesian density estimation Electronic Journal of Statistics. 10: 3355-3373. DOI: 10.1214/16-Ejs1158  0.48
2016 Som A, Hans CM, MacEachern SN. A conditional Lindley paradox in Bayesian linear models Biometrika. 103: 993-999. DOI: 10.1093/Biomet/Asw037  0.32
2012 Nesselroade JR. Foreword Current Topics in the Theory and Application of Latent Variable Models. ix-x. DOI: 10.4324/9780203813409  0.01
2006 MacEachern SN. Introduction to Statistical Thought Journal of the American Statistical Association. 101: 1719-1719. DOI: 10.1198/Jasa.2006.S137  0.01
1997 Müller P, West M, MacEachern S. Bayesian Models for Non‐linear Autoregressions Journal of Time Series Analysis. 18: 593-614. DOI: 10.1111/1467-9892.00070  0.04
1994 Maceachern SN. Estimating normal means with a conjugate style dirichlet process prior Communications in Statistics - Simulation and Computation. 23: 727-741. DOI: 10.1080/03610919408813196  0.01
1993 MacEachern S, Stasny EA. An Easy Ridiculous Unbiased Estimator Teaching Statistics. 15: 12-14. DOI: 10.1111/J.1467-9639.1993.Tb00248.X  0.12
1993 Maceachern S. An evaluation of bayes posterior probability regions for a survival curve Journal of Nonparametric Statistics. 3: 175-186. DOI: 10.1080/10485259308832580  0.01
1993 MacEachern SN, Berliner LM. Aperiodic Chaotic Orbits American Mathematical Monthly. 100: 237-241. DOI: 10.1080/00029890.1993.11990394  0.04
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