| Gene selection: a Bayesian variable selection approach KE Lee, N Sha, ER Dougherty, M Vannucci, BK Mallick Bioinformatics 19 (1), 90-97, 2003 | 458 | 2003 |
| Bayesian variable selection in clustering high-dimensional data MG Tadesse, N Sha, M Vannucci Journal of the American Statistical Association 100 (470), 602-617, 2005 | 318 | 2005 |
| Bayesian variable selection in multinomial probit models to identify molecular signatures of disease stage N Sha, M Vannucci, MG Tadesse, PJ Brown, I Dragoni, N Davies, ... Biometrics 60 (3), 812-819, 2004 | 179 | 2004 |
| Variable selection for nonparametric Gaussian process priors: Models and computational strategies T Savitsky, M Vannucci, N Sha Statistical science: a review journal of the Institute of Mathematical …, 2011 | 122 | 2011 |
| Bayesian variable selection for the analysis of microarray data with censored outcomes N Sha, MG Tadesse, M Vannucci Bioinformatics 22 (18), 2262-2268, 2006 | 122 | 2006 |
| NIR and mass spectra classification: Bayesian methods for wavelet-based feature selection M Vannucci, N Sha, PJ Brown Chemometrics and Intelligent Laboratory Systems 77 (1-2), 139-148, 2005 | 87 | 2005 |
| Bayesian analysis for step-stress accelerated life testing using Weibull proportional hazard model N Sha, R Pan Statistical Papers 55, 715-726, 2014 | 56 | 2014 |
| Gene selection in arthritis classification with large‐scale microarray expression profiles N Sha, M Vannucci, PJ Brown, MK Trower, G Amphlett, F Falciani Comparative and functional genomics 4 (2), 171-181, 2003 | 34 | 2003 |
| Modeling antitumor activity by using a non-linear mixed-effects model H Liang, N Sha Mathematical Biosciences 189 (1), 61-73, 2004 | 26 | 2004 |
| Parameter inference in a hybrid system with masked data R Wang, N Sha, B Gu, X Xu IEEE Transactions on Reliability 64 (2), 636-644, 2015 | 24 | 2015 |
| Identifying biomarkers from mass spectrometry data with ordinal outcome D Kwon, MG Tadesse, N Sha, RM Pfeiffer, M Vannucci Cancer informatics 3, 117693510700300024, 2007 | 23 | 2007 |
| Discussion on the meeting on ‘Statistical Modelling and analysis of genetic data’. DJ Balding, AD Carothers, JL Marchini, LR Cardon, B Griffiths, BS Weir, ... Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2002 | 23 | 2002 |
| Statistical analysis of a Weibull extension with bathtub‐shaped failure rate function R Wang, N Sha, B Gu, X Xu Advances in Statistics 2014 (1), 304724, 2014 | 21 | 2014 |
| Reliability estimation for accelerated life tests based on a Cox proportional hazard model with error effect MI Rodríguez‐Borbón, MA Rodríguez‐Medina, LA Rodríguez‐Picón, ... Quality and Reliability Engineering International 33 (7), 1407-1416, 2017 | 17 | 2017 |
| Comparison analysis of efficiency for step-down and step-up stress accelerated life testing R Wang, N Sha, B Gu, X Xu IEEE Transactions on Reliability 61 (2), 590-603, 2012 | 15 | 2012 |
| A Bayes inference for ordinal response with latent variable approach N Sha, BO Dechi Stats 2 (2), 321-331, 2019 | 12 | 2019 |
| Statistical inference for progressive stress accelerated life testing with Birnbaum-Saunders distribution N Sha Stats 1 (1), 189-203, 2018 | 11 | 2018 |
| Statistical inference in dependent component hybrid systems with masked data N Sha, R Wang, P Hu, X Xu Advances in Statistics 2015 (1), 525136, 2015 | 10 | 2015 |
| A copula approach of reliability analysis for hybrid systems N Sha Reliability: Theory & Applications 16 (1 (61)), 231-242, 2021 | 8 | 2021 |
| On parameter inference for step-stress accelerated life test with geometric distribution R Wang, X Xu, R Pan, N Sha Communications in Statistics-Theory and Methods 41 (10), 1796-1812, 2012 | 8 | 2012 |
