Hemant Ishwaran


  1. Lyu J. and Ishwaran H. (2023). Commentary: "To classify means to choose a threshold". J. Thor. Card. Surg., 165(4), 1443-1445. [pdf]
  2. Qiu J., Xu B., Ye D., Ren D., Wang S., Benci J.L., Xu Y., Ishwaran H., Beltra J-.C., Wherry E.J. and Minn A.J. (2023). Cancer cells resistant to immune checkpoint blockade acquire interferon-associated epigenetic memory to sustain T Cell dysfunction. Nature Cancer, 4, 43-61. [pdf]
  3. Ishwaran H. and O'Brien R. (2022): Reply: "The standardization and automation of machine learning for biomedical data". J. Thor. Card. Surg., 163(1), e102-e103. [pdf]
  4. Ishwaran H. and Blackstone E.H. (2022). Commentary: "Dabblers beware of hidden dangers in machine learning comparisons". J. Thor. Card. Surg., 163(6), 2088-2090. [pdf]
  5. Pande A., Ishwaran H. Blackstone E.H, Rajeswaran J. and Gillanov M. (2022). Application of gradient boosting in evaluating surgical ablation for atrial fibrillation. SN Computer Science, 3:466 [pdf]
  6. Pande A., Ishwaran H. and Blackstone E.H. (2022). Boosting for multivariate longitudinal responses. SN Computer Science, 3:186. [pdf]
  7. Raja S., Rice T.W., Lu M. Semple M.E., Blackstone E.H., Murthy S.C., Ahmad U., McNamara M., Toth A.J. and Ishwaran H. for the Worldwide Esophageal Cancer Collaboration Investigators. (2022). Adjuvant therapy after neoadjuvant therapy for esophageal cancer: who needs it?. Ann. Surg. [pdf]
  8. Lu M. and Ishwaran H. (2021). Cure and death play a role in understanding dynamics for COVID-19: data-driven competing risk compartmental models, with and without vaccination. PloS ONE, 16(7), e0254397. [pdf] [supplemental pdf]
  9. Raja S., Rice T.W., Murthy S.C., Ahmad U., Semple M.E., Blackstone E.H and Ishwaran H. (2021). Value of lymphadenectomy in patients receiving neoadjuvant therapy for esophageal adenocarcinoma. Ann. Surg., 274(4), e320-e327. [pdf]
  10. Lu M. and Ishwaran H. (2021). Discussion to "Nonparametric Variable Importance Assessment Using Machine Learning Techniques," by Brian D. Williamson, Peter B. Gilbert, Marco Carone, and Noah Simon. Biometrics, 77, 23-27. [pdf]
  11. Lee D.K., Chen N., Ishwaran H, Wang X. and Pakbin A. (2021). Theory and software for boosted nonparametric hazard estimation. Proceedings of Machine Learning Research, 1, 1-10. [pdf]
  12. Mantero A. and Ishwaran H. (2021). Unsupervised random forests. Stat. Anal. Data Mining, 14(2), 144-167. [pdf]
  13. Lu M. and Ishwaran H. (2021). Tree variable selection for paired case-control studies with application to microbiome data. In S. Datta and S.Guha (Eds., pp 295-310) "Statistical Analysis of Microbiome Data", Springer, Switzerland. [pdf]  [eBook pdf]
  14. Marzouka G R., Rivner H., Mehta V., Lopez, J., Vaz I., Tang F., Ishwaran H. and Goldberger J.J. (2021). The CHA2DS2-VASc score for risk stratification of stroke in heart failure with-vs-without atrial fibrillation. American J. Cardiology, 155, 72-77 [pdf]
  15. Lee D.K., Chen N. and Ishwaran H. (2021). Boosted nonparametric hazards with time-dependent covariates. Ann. Statist, 49(4), 2101-2128. [pdf]
  16. Ishwaran H. and O'Brien R. (2021). Commentary: "The problem of class imbalance in biomedical data". J. Thor. Card. Surg., 161(6), 1940-1941 [pdf]
  17. O'Brien R., Ishwaran H., Szczotka-Flynn L.B., Lass J.H. (2021). Random survival forest analysis of intraoperative complications as predictors of graft failure in the cornea preservation time study. JAMA Ophthamology, 139(2), 191-197. [pdf]
  18. Hsich E.M., Blackstone E.H., Thuita L., McNamara D.M., Rogers J.G., Yancy C.W., Goldberg L.R., Valapour M., Xu G., and Ishwaran, H. (2020). Heart transplantation: an in-depth survival analysis. JACC Heart Failure, 8(7), 557-568. [pdf]
  19. O'Brien R. and Ishwaran H. (2019). A random forests quantile classifier for class imbalanced data. Pattern Recognit., 90, 232-249. [pdf] [html]
  20. Ishwaran H. and Lu M. (2019). Standard errors and confidence intervals for variable importance in random forest regression, classification, and survival. Stat. Med., 38, 558-582. [pdf]
  21. Blackstone E.H. et al. (2019). Biatrial maze procedure versus pulmonary vein isolation for atrial fibrillation during mitral valve surgery: New analytical approaches and end points. J. Thor. Card. Surg., 157(1), 234-243. [pdf]
  22. Hsich E.M., Thuita L., McNamara D.M., Rogers J.G., Valapour M., Goldberg, L.R.,Yancy C.W., Blackstone E.H. and Ishwaran H. (2019). Variables of importance in the scientific registry of transplant recipients database predictive of heart transplant waitlist mortality. Amer. J. Transp., 19, 2067-2076. [pdf]
  23. Rice T.W., Lu M., Ishwaran H., Blackstone E.H. (2019). Precision surgical therapy for adenocarcinoma of the esophagus and esophagogastric junction. J. Thor. Oncol., 14(12), 2165-2175. [pdf]
  24. Benci J.L., Johnson L.R., Choa, R., Xu Y., Qiu J., Zhou Z., Xu B., Ye, D., Nathanson K.L., June C.H., Wherry, E.J. Zhang, N.R., Ishwaran H., Hellman M.D., Wolchok, J.D., Kambayashi T. and Minn A.J. (2019). Opposing functions of interferon coordinate adaptive and innate immune responses to cancer immune checkpoint blockade. Cell, 178 (4), 933-948. [pdf]
  25. Ishwaran H. and Lu M. (2018). Random Survival Forests. Wiley StatsRef: Statistics Reference Online. [pdf]
  26. Lu M. and Ishwaran H. (2018). Expert Opinion: A prediction-based alternative to P values in regression models. J. Thor. Card. Surg, 155(3), 1130-1136. [pdf] Editorial Commentary [pdf] [R code for implementing methods described in the paper]
  27. Lu M., Sadiq S., Feaster D.J. and Ishwaran H. (2018). Estimating individual treatment effect in observational data using random forest methods. J. Comp. Graph. Statist, 27(1), 209-219 [pdf] [arXiv:1701.05306]
  28. Dazard J-E., Ishwaran H., Mehlotra R., Weinberg A. and Zimmerman P. (2018). Ensemble survival tree models to reveal pairwise interactions of variables with time-to-events outcomes in low-dimensional setting. Stat. Appl. Genetics Molecular Bio., 17 (1).
  29. Rech A.J., Balli D., Mantero A., Ishwaran H., Nathanson K.L., Stanger B.Z. and Vonderheide R.H. (2018). Tumor immunity and survival as a function of alternative neoepitopes in human cancer. Cancer Immunology Research, 6(3), 276-287. [pdf]
  30. Rajeswaran J., Blackstone E.H., Ehrlinger J., Li L., Ishwaran H. and Parides M.K. (2018). Probability of atrial fibrillation after ablation: using a parametric nonlinear temporal decomposition mixed effects model. Statist. Meth. Med. Research, 27(1), 126-141. [pdf]
  31. Lamont, A. E., Lyons, M. D., Jaki, T., Stuart E. A., Feaster, D. J., Ishwaran, H., Tharmaratnam, K. and Van Horn, M. L. (2018). Identification of predicted individual treatment effects in randomized clinical trials. Statist. Meth. Med. Research, 27(1), 142-157. [pdf]
  32. Lu M., Blackstone E.H. and Ishwaran H. (2017). Personalized treatment for ischemic cardiomyopathy: incorporating expert knowledge in random forest approaches using observational survival data with non-overlapping groups.
  33. Pande A., Li L. Rajeswaran J., Ehrlinger J., Kogalur U.B., Blackstone E.H and Ishwaran H. (2017). Boosted multivariate trees for longitudinal data. Machine Learning, 106(2), 277-305. [pdf]
  34. Tang F. and Ishwaran H. (2017). Random forest missing data algorithms. Stat. Anal. Data Mining, 10, 363–377. [pdf] arXiv:1701.05305
  35. Hsich E., Blackstone E.H, Thuita L., McNamara D., Rogers J., Ishwaran H.* and Schold J. (2017). Sex-differences in mortality based on UNOS status while awaiting heart transplantation. Circulation: Heart Failure, 10(6), 1-10. *shared senior authorship. [pdf]
  36. Li L., Mao H., Ishwaran H., Rajeswaran J., Ehrlinger J. and Blackstone E.H. (2017). Estimating the prevalence of atrial fibrillation from a three-class mixture model for repeated diagnoses. Biometrical Journal, 59(2), 331-343. [pdf]
  37. Rice T.W., Ishwaran H., et al. (2017). Esophageal cancer: associations with (pN+) lymph node metastases. Annals of Surgery, 265(1), 122-129. [pdf]
  38. Rice T.W., Kelsen D., Blackstone E.H., Ishwaran H., Patil D. T., Bass A.J., Erasmus J.J., Gerdes H., and Hofstetter W.L. (2017). Eighth Edition of the AJCC Cancer Staging Manual: Esophagus and esophagogastric junction, pp 185-202. [pdf]
  39. Rice T.W., Ishwaran H., Ferguson M.K., Blackstone E.H. and Goldstraw P. (2017). Adenocarcinoma of the esophagus and esophagogastric junction: An 8th edition staging primer. J. Thoracic Oncology, 12(1), 36-42. [pdf]
  40. Benci J. et al. (2016). Tumor interferon signaling regulates a multigenic resistance program to immune checkpoint blockade. Cell, 167, 1540–1554. [pdf]
  41. Sadiq S., Yan Y., Shyu M-L., Chen S-C. and Ishwaran H. (2016). Enhancing multimedia imbalanced concept detection using VIMP in random forests. To appear in IEEE 17th International Conference on Information Reuse and Integration (IRI). [pdf]
  42. Rice T.W., Ishwaran H., Hofstetter W.L., Kelsen D.P., Hansen. C.A., and Blackstone E.H. (2016). Recommendations for pathologic staging (pTNM) of cancer of the esophagus and esophagogastric junction for the 8th Edition AJCC/UICC Staging Manuals. Diseases of the Esophagus, 29(8), 897-905. [pdf]
  43. Rice T.W., Ishwaran H., Kelsen D.P., Hofstetter W.L. Hansen. C.A., and Blackstone E.H. (2016). Recommendations for neoadjuvant pathologic staging (ypTNM) of cancer of the esophagus and esophagogastric junction for the 8th Edition AJCC/UICC staging manuals. Diseases of the Esophagus, 29(8), 906-912. [pdf]
  44. Rice T.W., Ishwaran H., Blackstone E.H., Hofstetter W.L. Kelsen D.P., and Hansen. C.A. (2016). Recommendations for clinical staging (cTNM) of cancer of the esophagus and esophagogastric junction for the 8th Edition AJCC/UICC Staging Manuals. Diseases of the Esophagus, 29(8), 913-919. [pdf]
  45. Rice, T. W., et al. Worldwide Esophageal Cancer Collaboration: pathologic staging data. (2016). Diseases of the Esophagus, 29(7), 724-733. [pdf]
  46. Rice, T. W., et al. Worldwide Esophageal Cancer Collaboration: neoadjuvant pathologic staging data. (2016). Diseases of the Esophagus, 29(7), 715-723. [pdf]
  47. Rice, T. W., et al. Worldwide Esophageal Cancer Collaboration: clinical staging data. (2016). Diseases of the Esophagus, 29.(7), 707-714. [pdf]
  48. Twyman-Saint Victor C., et al. (2015). Radiation and dual checkpoint blockade activate non-redundant immune mechanisms in cancer. Nature, 520, 373-377. doi:10.1038/nature14292 [pdf, news article]
  49. Rice T.W., Ishwaran H. and Blackstone E.H. (2015). Esophageal cancer: location, location, location. Eur. J. Cardiothorac. Surg., 48(2), 194-195. doi:10.1093/ejcts/ezv125 [pdf]
  50. Ishwaran H. (2015). The effect of splitting on random forests. Machine Learning, 99, 75-118. [pdf]
  51. Boelens M.C., Wu T.J., Nabet B.Y., Xu B., Qui Y., Yoon T., Azzam D.J.,Twyman-Saint Victor C., Wiemann B.Z., Ishwaran H., ter Brugge P.J., Jonkers J., Slingerland J. and Minn A.J. (2014). Exosome transfer from stromal to breast cancer cells regulates therapy resistance pathways. Cell, 159(3), 499-513. [pdf]
  52. Ishwaran H. and Malley J.D. (2014). Synthetic learning machines. BioData Mining, 7:28. [html] [pdf]
  53. Ishwaran H., Gerds T.A., Kogalur U.B., Moore R.D., Gange S.J. and Lau B.M. (2014). Random survival forests for competing risks. Biostatistics, 15(4), 757-773. doi:10.1093/biostatistics/kxu010 [pdf] supplementary [pdf] (R-code for simulations)
  54. Ishwaran H. and Rao J.S (2014). Geometry and properties of generalized ridge regression in high dimensions. Contemporary Mathematics, 62, 82-93. [pdf]
  55. Chen X. and Ishwaran H. (2012). Pathway hunting by random survival forests. Bioinformatics 2012; 29:99-105. [pdf]
  56. Mogensen U.B., Ishwaran H. and Gerds T.A. (2012). Evaluating random forests for survival analysis using prediction error curves. J. Statist. Software, 50(11):1-23. [pdf]
  57. Chen X. and Ishwaran H. (2012). Random forests for genomic data analysis. Genomics, 99, 323-329. [pdf]
  58. Ehrlinger J. and Ishwaran H. (2012). Characterizing L2Boosting. Ann. Statist, 40, 1074-1101. [pdf]
  59. Yun, J., Frankenberger, C. A., Kuo, W. L., Boelens, M. C., Eves, E. M., Cheng, N., Liang, H., Li, W. H., Ishwaran, H., Minn A.J. and Rosner, M. R. (2011). Signaling pathway for RKIP and let-7 regulates and predicts metastatic breast cancer. EMBO J., 30:4500-4514. [pdf]
  60. Ishwaran H., Kogalur U.B., Chen X. and Minn A.J. (2011). Random survival forests for high-dimensional data. Stat. Anal. Data Mining, 4, 115-132. [pdf]
  61. Blackstone E.H., Lenat, D.B. and Ishwaran H. (2011). Infrastructure required to learn which care is best: methods that need to be developed, in "Learning What Works: Infrastructure Required for Comparative Effectiveness Research." Washington, The National Academies Press, pp. 123-144. [pdf]
  62. Gorodeski E.Z., Ishwaran H*., Kogalur U.B., Blackstone E.H., Hsich E., Zhang Z-M., Vitolins M.Z, Manson J.E., Curb J.D., Martin L.W., Prineas R.J and Lauer M.S. (2011). Use of hundreds of electrocardiographic biomarkers for prediction of mortality in post-menopausal women: The Women's Health Initiative. Circulation: Cardiovascular Quality and Outcomes, 4:521-532. *shared first authorship [pdf]
  63. Ishwaran H. (2011). Discussion to "Nonparametric Inference Based on Panel Count Data,'' by X. Zhao, N. Balakrishnan and J. Sun. TEST, 20(1), 48-53.
  64. Hsich E., Gorodeski E.Z.,Blackstone E.H., Ishwaran H. and Lauer M.S. (2011). Identifying important risk factors for survival in systolic heart failure patients using random survival forests. Circulation: Cardio. Qual. Outcomes, 4(1), 39-45 [pdf]
  65. Ishwaran H. and Rao J.S. (2011). Consistency of spike and slab regression. Stat. Prob. Letters, 81, 1920-1928. [pdf]
  66. Viny A.D., Clemente M.J, Jasek M., Askar M., Ishwaran H., Nowacki A., Zhang A. and Maciejewski J.P. (2010). MICA polymorphism identified by whole genome array associated with NKG2D-mediated cytotoxicity in T-cell large granular lymphocyte leukemia. Haematologica, 95(10), 1713-1721. [pdf]
  67. Ishwaran H., Kogalur U.B. and Rao J.S. (2010). spikeslab: prediction and variable selection using spike and slab regression. R Journal, 2(2), 68-73. [pdf]
  68. Ishwaran H., Kogalur U.B., Gorodeski E.Z., Minn A.J. and Lauer M.S. (2010). High-dimensional variable selection for survival data. J. Amer. Stat. Assoc, 105, 205-217. [pdf]
  69. Rice T.W., Rusch V.W., Ishwaran H. and Blackstone E.H. (2010). Cancer of the esophagus and esophagogastric junction: data-driven staging for the 7th Edition of the AJCC/UICC cancer staging manuals. Cancer, 116(16), 3763-3773. [pdf]
  70. Kalady M.F., DeJulius K., Church J.M., Lavery I.C,, Fazio V.W. and Ishwaran H. (2010). Gene signature is associated with early stage rectal cancer recurrence. J. Amer. College of Surgeons, 211(2), 187-195. [pdf]
  71. Chen X., Wang, L and Ishwaran H. (2010). An integrative pathway-based clinical-genomic model for cancer survival prediction. Stat. Prob. Letters, 80, 1313-1319. [pdf]
  72. Ishwaran H., Kogalur U.B. (2010). Consistency of random survival forests. Stat. Prob. Letters, 80, 1056-1064. [pdf]
  73. Rizk N.P., Ishwaran H., Rice T.W., Chen L-Q., Schipper P.H., Kesler K.A., Law S., Lerut T.E., Reed C.E., Salo J.A., Scott W.J., Hofstetter W.L., Watson T.J., Allen M.S., Rusch V.W. and Blackstone E.H. (2010). Optimum lymphadenectomy for esophageal cancer. Ann. Surgery, 251, 46-50. [pdf]
  74. Messick C.A., Sanchez J., Dejulius K.L., Hammel J., Ishwaran H. and Kalady M.F. (2010). CEACAM-7: a predictive marker for rectal cancer recurrence. Surgery, 147(5), 713-719. [pdf]
  75. Ishwaran H. and Zarepour M. (2009). Series representations for multivariate generalized gamma processes via a scale invariance principle. Statistica Sinica, 19, 1665-1682. [pdf] (supplemental proofs [pdf])
  76. Ishwaran H., Blackstone E.H., Hansen. C.A. and Rice T.W. (2009). A novel approach to cancer staging: application to esophageal cancer. Biostatistics, 10, 603-620. [pdf]
  77. Hsich E., Gorodeski E.Z., Starling R.C., Blackstone E.H., Ishwaran H. and Lauer M.S. (2009). Importance of treadmill exercise time as an initial prognostic screening tool in patients with systolic left ventricular dysfunction. Circulation, 119, 3189-3197. [pdf]
  78. Ishwaran H., James L.F. and Zarepour M. (2009). An alternative to the m out of n bootstrap. J. Stat. Plann. Inference, 139, 788-801. [pdf]
  79. Ishwaran H. and Rao J.S. (2009). Decision tree: introduction. In "Encyclopedia of Medical Decision Making," (ed. M. Kattan), 323-328. California, Sage Inc. [pdf]
  80. Ishwaran H. and Rao J.S. (2009). Decision trees, advanced techniques in constructing. In "Encyclopedia of Medical Decision Making", (ed. M. Kattan), 328-332. Calfornia, Sage Inc. [pdf]
  81. Gorodeski E.Z., Ishwaran H., Blackstone E.H. and Lauer M.S. (2009). Quantitative electrocardiographic measures and long-term mortality in exercise test patients with clinically normal resting electrocardiograms. Amer. Heart J. 158, 61-70. [pdf]
  82. Papana A. and Ishwaran H. (2009). Gene hunting with forests for multigroup time course data. Stat. Prob. Letters, 79, 1146-1154. [pdf]
  83. Weichselbaum R.R., Ishwaran H., Yoon T., Nuyten D.S.A., Baker, S.W., Khodarev N., Su A.W., Shaikh, A.Y., Roach P., Kreike B., Roizman B., Bergh, J., Pawitan, Y., van de Vijver M.J. and Minn A.J. (2008). An interferon-related gene signature for DNA damage resistance is a predictive marker for chemotherapy and radiation for breast cancer. PNAS (Medical Sciences), 105(47) 18490-18495. [pdf]
  84. Atreja A., Mehta N.B., Jain A.K., Harris C.M., Ishwaran H., Avital M. and Fishleder A.J. (2008). Satisfaction with web-based training in an integrated healthcare delivery network: do age, education, computer skills or attitude matter? BMC Medical Education, 8:48.
  85. Dey T., Ishwaran H. and Rao J.S. (2008). An in-depth look at highest posterior model selection. Econometric Theory, 24, 377-403. [pdf]
  86. Ishwaran H. and Rao J.S. (2008). Clustering gene expression profile data by selective shrinkage. Stat. Prob. Letters, 78, 1490-1497. [pdf]
  87. Ishwaran H., Kogalur U.B., Blackstone E.H. and Lauer M.S. (2008). Random survival forests. Ann. Appl. Statist., 2, 841-860. [pdf]
  88. Ishwaran H., Jahandideh M.T. and Zarepour, M. (2008). Option pricing for infinite variance data. Statistics, 42(3), 245-260.
  89. Ishwaran H. and Papana, A. (2008). Orthogonalized smoothing for rescaled spike and slab models. IMS Collections, "Pushing the Limits of Contemporary Statistics: Contributions in Honor of Jayanta K. Ghosh", 3, 267-281. [pdf]
  90. Lauer M.S., Martino D., Ishwaran H. and Blackstone E.H. (2007). Quantitative measures of electrocardiographic left ventricular mass, conduction, and repolarization, and long-term survival following coronary artery bypass grafting. Circulation, 116, 888-893. [pdf]
  91. Kim E.S.H., Ishwaran H., Blackstone E.H. and Lauer M.S. (2007). External prognostic validations and comparisons of age- and gender-adjusted exercise capacity predictions. J. Amer. College Cardiol. 50, 1867-1875. [pdf]
  92. Ishwaran H. (2007). Variable importance in binary regression trees and forests. Electronic J. Statist., 1, 519-537. [pdf]
  93. Minn A.J., Gupta P.G., Padua D., Bos P., Nguyen D.X. Nuyten D., Kreike B., Zhang Y., Wang Y., Ishwaran H., Foekens J.A., van de Vijver M.J. and Massagué J. (2007). Lung metastasis genes couple breast tumor size and metastatic spread. PNAS (Genetics), 104 (16), 6740-6745. [pdf]
  94. Ishwaran H., and Kogalur U.B. (2007). Random survival forests for R. Rnews, 7/2, 25-31. [pdf]
  95. Ishwaran H., Rao, J.S. and Kogalur U.B. (2006). BAMarray™: Java software for Bayesian analysis of variance for microarray data. BMC Bioinformatics, 7:59. [pdf]
  96. Papana A. and Ishwaran H. (2006). CART variance stabilization and regularization for high-throughput genomic data. Bioinformatics, 22 (18), 2254-2261. [pdf]
  97. Ishwaran H. and Rao J.S. (2005). Spike and slab gene selection for multigroup microarray data. J. Amer. Stat. Assoc., 100, 764-780 [pdf]
  98. Ishwaran H. and Rao J.S. (2005). Spike and slab variable selection: frequentist and Bayesian strategies. Ann. of Stat., 33, 730-773. [pdf]
  99. Ishwaran H. Blackstone E.H., Pothier C.E. and Lauer M.S. (2004). Relative risk forests for exercise heart rate recovery as a predictor of mortality. J. Amer. Stat. Assoc., 99, 591-600. [pdf]   [Figure 6 in color]
  100. Obuchowski N.A., Beiden S.V., Berbaum K.S., Hillis S., Ishwaran H., Song H.H. and Wagner R.F. (2004). Multi-reader, multi-case ROC analysis: an empirical comparison of five methods. Academic Radiology, 11, 980-995. [pdf]
  101. Koch C.G, Khandwala F., Cywinski J.B., Ishwaran H., Estafanous F., Loop E. and Blackstone E.H. (2004). Health-related quality of life following coronary artery bypass grafting: a gender analysis utilizing the Duke activity status index. J. Thoracic and Cardiovascular Surgery, 128, 284-295.
  102. Ishwaran H. and James L.F. (2004). Computational methods for multiplicative intensity models using weighted gamma processes: proportional hazards, marked point processes and panel count data. J. Amer. Stat. Assoc., 99, 175-190. [pdf]
  103. Ishwaran H. (2004). Discussion to "Least Angle Regression,'' by Efron, B., Hastie, T., Johnstone, I., and Tibshirani, R. Ann. Statist. 32, 452-458. [pdf]
  104. Belin T.R., Ishwaran H., Duan N., Berry S.H., Kanouse D.E. (2004). Identifying likely duplicates by record linkage in a survey of prostitutes, in "Applied Bayesian Modeling and Causal Inference from an Incomplete-Data Perspectives", eds. A. Gelman and X.L. Meng. New York: John Wiley and Sons, pp 319-329. [pdf]   [figure]
  105. Ishwaran H. and Rao J.S. (2003). Discussion to "Frequentist Model Average Estimators and The Focussed Information Criteria," by Hjort, N. and Claeskens, G. J. Amer. Stat. Assoc., 98, 922-925. [pdf
  106. Ishwaran H. and James L.F. (2003). Generalized weighted Chinese restaurant processes for species sampling mixture models. Statistica Sinica, 13, 1211-1235. [pdf]
  107. Ishwaran H. and Zarepour M. (2003). Random probability measures via Polya sequences: revisiting the Blackwell-MacQueen urn scheme. ArXiv:math.PR/030904.
  108. Ishwaran H. and Rao J.S. (2003). Detecting differentially expressed genes in microarrays using Bayesian model selection. J. Amer. Stat. Assoc., 98, 438-455. [pdf]
  109. Alexe S., Blackstone E.H., Hammer P. L, Ishwaran H. Lauer M.S. and Pothier C.E. (2003). Coronary risk prediction by logical analysis of data. Ann. Oper. Research, 119, 15-42. [pdf]
  110. Ishwaran H. and James L.F. (2003). Some further developments for stick-breaking priors: finite and infinite clustering and classification. Sankhya Series A, 65, 577-592. [pdf]
  111. Ishwaran H. and Zarepour M. (2002). Dirichlet prior sieves in finite normal mixtures. Statistica Sinica 12, 941-963. [pdf]
  112. Lauer M.S., Alexe S., Pothier C.E., Blackstone E.H., Ishwaran H., Hammer P.L. (2002). Use of the "Logical Analysis of Data'' method for assessing long-term mortality risk after exercise electrocardiography. Circulation, 106, 685 - 690. [pdf]
  113. Ishwaran H. and Zarepour M. (2002). Exact and approximate sum-representations for the Dirichlet process. Can. J. Statist. 30, 269-283. [pdf]
  114. Banjevic D., Ishwaran H. and Zarepour M. (2002). A recursive method for functionals of Poisson processes. Bernoulli 8, 295-311. [pdf]
  115. Siegel M.J., Ishwaran H., Fletcher B.D., Meyer J., Hoffer F.A., Jaramillo D., Hernandez, R., Siegel B.A., Caudry D.J. and McNeil B.J. (2002). Staging of neuroblastoma at imaging: Report of the radiology diagnostic oncology group. Radiology 223, 168-175. [pdf]
  116. Ishwaran H. and Takahara G. (2002). Independent and identically distributed Monte Carlo algorithms for semiparametric linear mixed models. J. Amer. Stat. Assoc. 97, 1154-1166. [pdf]
  117. Ishwaran H. and James L.F. (2002). Approximate Dirichlet process computing in finite normal mixtures: smoothing and prior information. J. Comp. Graph. Statist. 11, 508-532. [pdf]
  118. Ishwaran H., James L.F. and Sun J. (2001). Bayesian model selection in finite mixtures by marginal density decompositions. J. Amer. Stat. Assoc. 96, 1316-1332. [pdf]
  119. Ishwaran H. and James L.F. (2001). Gibbs sampling methods for stick-breaking priors. J. Amer. Stat. Assoc. 96, 161-173. [pdf]
  120. Ishwaran H. (2000). Univariate and multirater ordinal cumulative link regression with covariate specific cutpoints. Can. J. Statist., 28, 715-730. [pdf]
  121. Ishwaran H. and Gatsonis C. (2000). A general class of hierarchical ordinal regression models with applications to correlated ROC analysis. Can. J. Statist., 28, 731-750. [pdf]
  122. Ishwaran H. (2000). Inference for the random effects in Bayesian generalized linear mixed models. ASA Proceedings of the Bayesian Statistical Science Section, pp 1-10. [ps]
  123. Ishwaran H. and Zarepour M. (2000). Markov chain Monte Carlo in approximate Dirichlet and beta two-parameter process hierarchical models. Biometrika, 87, 371-390. [pdf]
  124. Ishwaran H. (1999). Applications of hybrid Monte Carlo to Bayesian generalized linear models: quasicomplete separation and neural networks. J. Comp. Graph. Statist., 8, 779-799. [pdf]
  125. Ishwaran H. (1999). Information in semiparametric mixtures of exponential families. Ann. Statist., 27, 159-177. [pdf]
  126. Ishwaran H. (1998). Exponential posterior consistency via generalized Polya urn schemes in finite semiparametric mixtures. Ann. Statist., 26, 2157-2178. [pdf]
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