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Department of Statistics College of Liberal Arts and Sciences

Publications

  • Doss, H. and Sellke, T. (1982). The tails of probabilities chosen from a Dirichlet prior. The Annals of Statistics 10 1302–1305. 3
  • Doss, H. (1984). Bayesian estimation in the symmetric location problem. Zeitschrift fur¨Wahrscheinlichkeitstheorie und verwandte Gebiete 68 127–147.
  • Doss, H. (1985). Bayesian nonparametric estimation of the median; Part I: Computation of the estimates. The Annals of Statistics 13 1432–1444.
  • Doss, H. (1985). Bayesian nonparametric estimation of the median; Part II: Asymptotic properties of the estimates. The Annals of Statistics 13 1445–1464.
  • Doss, H. (1986). Discussion of “On the consistency of Bayes estimates” by P. Diaconis and D. Freedman. The Annals of Statistics 14 45–47.
  • Doss, H. and Sethuraman, J. (1989). The price of bias reduction when there is no unbiased estimate. The Annals of Statistics 17 440–442.
  • Doss, H. (1989). On estimating the dependence between two point processes. The Annals of Statistics 17 749–763.
  • Doss, H., Freitag, S., and Proschan, F. (1989). Estimating jointly system and component reliabilities using a mutual censorship approach. The Annals of Statistics 17 764–782.
  • Doss, H. and Gill, R.D. (1992). An elementary approach to weak convergence for quantile processes, with applications to censored survival data. Journal of the American Statistical Association 87 869–877.
  • Li, G. and Doss, H. (1993). Generalized Pearson-Fisher chi-square goodness-of-fit tests,with applications to models with life history data. The Annals of Statistics 21 772–797.
  • Antoine, R., Doss, H., and Hollander, M. (1993). On identifiability in the autopsy model of reliability theory. Journal of Applied Probability 30 913–930.
  • Burr, D. and Doss, H. (1993). Confidence bands for the median survival time as a function of the covariates in the Cox model. Journal of the American Statistical Association 88 1330–1340.
  • Doss, H. (1994). Bayesian estimation for censored data: An experiment in sensitivity analysis. Proceedings of the Fifth Purdue Symposium on Statistical Decision Theory and Related Topics 171–181.
  • Doss, H. and Chiang, Y.C. (1994). Choosing the resampling scheme when bootstrapping: A case study in reliability. Journal of the American Statistical Association 89 298–308.
  • Doss, H. (1994). Discussion of “Markov chains for exploring posterior distributions” by Luke Tierney. The Annals of Statistics 22 1728–1734.
  • Doss, H. (1994). Bayesian nonparametric estimation for incomplete data via successive substitution sampling. The Annals of Statistics 22 1763–1786.
  • Li, G. and Doss, H. (1995). An approach to nonparametric regression for life history data using local linear fitting. The Annals of Statistics 23 787–823. 4
  • Athreya, K.B., Doss, H., and Sethuraman, J. (1996). On the convergence of the Markov chain simulation method. The Annals of Statistics 24 69–100.
  • Doss, H., Huffer, F., and Lawson, K. (1997). Bayesian nonparametric estimation via Gibbs sampling for coherent systems with redundancy. The Annals of Statistics 25 1109–1139.
  • Doss, H. and Narasimhan, B. (1998). Dynamic display of changing posterior in Bayesian survival analysis. In Practical Nonparametric and Semiparametric Bayesian Statistics, D.
  • Dey, P. Mueller, and D. Sinha, eds., 63–87, Springer-Verlag, New York.
  • Doss, H. and Narasimhan, B. (1999). Dynamic display of changing posterior in Bayesian survival analysis: The software. Journal of Statistical Software 4(3).
  • Li, S., Pearl, D.K., and Doss, H. (2000). Phylogenetic tree construction using Markov chain Monte Carlo. Journal of the American Statistical Association 95 493–508.
  • Burr, D., Doss, H., Goldschmidt-Clermont, P., and Cooke, G. (2003). A meta-analysis of studies on the association of the platelet PlA polymorphism of Glycoprotein IIIa and risk of coronary heart disease. Statistics in Medicine 22 1741–1760.
  • Doss, H. and Huffer, F. (2003). Monte Carlo methods for Bayesian analysis of survival data using mixtures of Dirichlet process priors. Journal of Computational and Graphical Statistics 12 282–307.
  • Doss, H. (2003). Discussion of “A theory of statistical models for Monte Carlo integration” by A. Kong, P. McCullagh, X.-L. Meng, D. Nicolae, and Z. Tan. Journal of the Royal Statistical Society, Series B 65 610–611.
  • Burr, D. and Doss, H. (2005). A Bayesian semi-parametric model for random effects metaanalysis. Journal of the American Statistical Association 100 242–251.
  • Liu, Y., Shen, X. and Doss, H. (2005). Multicategory ψ-learning and support vector machines: computational tools. Journal of Computational and Graphical Statistics 14 219–236.
  • Harris, R., Beebe-Donk, J., Doss, H., and Burr, D. (2005). Aspirin, Ibuprofen and other nonsteroidal anti-inflammatory drugs in cancer prevention: A critical review of non-selective COX-2 blockade. Oncology Reports 13 559–584.
  • Schwartzbaum, J., Ahlbom, A., Malmer, B., Lonn, S., Brookes, A., Doss, H., Debinski, W., Henriksson, R., and Feychting, M. (2005). Polymorphisms associated with asthma are inversely related to risk of glioblastoma multiforme. Cancer Research 65 6459–6465. For an exchange of letters on this paper see the same journal, 66 2878–2879, 2006.
  • Doss, H. (2007). Bayesian model selection: Some thoughts on future directions. Statistica Sinica 17 413–421.
  • Doss, H. (2008). Quantifying information loss in survival studies. Statistical Science 23 313–317. (This is a discussion of “Quantifying the fraction of missing information for hypothesis testing in statistical and genetic studies” by D. Nicolae, X.-L. Meng, and A. Kong.) 5
  • Doss, H. (2010). Estimation of large families of Bayes factors from Markov chain output. Statistica Sinica 20 537–560.
  • Doss, H. and Hobert, J. (2010). Estimation of Bayes factors in a class of hierarchical random effects models using a geometrically ergodic MCMC algorithm. Journal of Computational and Graphical Statistics 19 295–312.
  • Buta, E. and Doss, H. (2011). Computational approaches for empirical Bayes methods and Bayesian sensitivity analysis. The Annals of Statistics 39 2658–2685.
  • Doss, H. (2012). Hyperparameter and model selection for nonparametric Bayes problems via Radon-Nikodym derivatives. Statistica Sinica 22 1–26. Anton, S., Embry, C., Marsiske, M., Lu, X., Doss, H., Leeuwenburgh, C., and Manini, T. (2014). Safety and metabolic outcomes of resveratrol supplementation in older adults: Results of a twelve-week, placebo-controlled pilot study. Experimental Gerontology 57 181–187.
  • Doss, H. and Tan, A. (2014). Estimates and standard errors for ratios of normalizing constants from multiple Markov chains via regeneration. Journal of the Royal Statistical Society, Series B 76 683–712.
  • Cesari, M., Vellas, B., Hsu, F., Newman, A., Doss, H., King, A., Manini, T., Church, T., Gill, T., Miller, M., and Pahor, M. (2015). A physical activity intervention to treat the frailty syndrome in older persons: Results from the LIFE-P study. Journal of Gerontology: Medical Sciences 70 216–222.
  • Tan, A., Doss, H., and Hobert, J. (2015). Honest importance sampling with multiple Markov chains. Journal of Computational and Graphical Statistics 24 792 826.
  • George, C.P. and Doss, H. (2018). Principled selection of hyperparameters in the latent Dirichlet allocation model. Journal of Machine Learning Research 18 No. 162, 1–38.
  • Doss, H. and Park, Y. (2018). An MCMC approach to empirical Bayes inference and Bayesian sensitivity analysis via empirical processes. The Annals of Statistics 46 1630–1663.
  • Chen, Z. and Doss, H. (2019). Inference for the number of topics in the latent Dirichlet allocation model via Bayesian mixture modelling. To appear in Journal of Computational and Graphical Statistics.