| label.switching: An R Package for Dealing with the Label Switching Problem in MCMC Outputs P Papastamoulis Journal of Statistical Software 69 (1), 1-24, 2016 | 148 | 2016 |
| An artificial allocations based solution to the label switching problem in Bayesian analysis of mixtures of distributions P Papastamoulis, G Iliopoulos Journal of Computational and Graphical Statistics, 2010 | 126 | 2010 |
| Evolution of IgE responses to multiple allergen components throughout childhood R Howard, D Belgrave, P Papastamoulis, A Simpson, M Rattray, ... Journal of Allergy and Clinical Immunology 142 (4), 1322-1330, 2018 | 57 | 2018 |
| Fast and accurate approximate inference of transcript expression from RNA-seq data J Hensman, P Papastamoulis, P Glaus, A Honkela, M Rattray Bioinformatics 31 (24), 3881-3889, 2015 | 42 | 2015 |
| On the identifiability of Bayesian factor analytic models P Papastamoulis, I Ntzoufras Statistics and Computing 32 (10.1007/s11222-022-10084-4), 2022 | 33 | 2022 |
| Handling the label switching problem in latent class models via the ECR algorithm P Papastamoulis Communications in Statistics-Simulation and Computation 43 (4), 913-927, 2014 | 32 | 2014 |
| On the estimation of mixtures of Poisson regression models with large number of components P Papastamoulis, ML Martin-Magniette, C Maugis-Rabusseau Computational Statistics & Data Analysis 93, 97-106, 2016 | 31 | 2016 |
| On the convergence rate of random permutation sampler and ECR algorithm in missing data models P Papastamoulis, G Iliopoulos Methodology and Computing in Applied Probability 15, 293-304, 2013 | 25 | 2013 |
| Reversible jump MCMC in mixtures of normal distributions with the same component means P Papastamoulis, G Iliopoulos Computational statistics & data analysis 53 (4), 900-911, 2009 | 23 | 2009 |
| Improved variational Bayes inference for transcript expression estimation P Papastamoulis, J Hensman, P Glaus, M Rattray Statistical Applications in Genetics and Molecular Biology 13 (2), 203 - 216, 2014 | 15 | 2014 |
| Bayesian detection of piecewise linear trends in replicated time-series with application to growth data modelling P Papastamoulis, T Furukawa, N van Rhijn, M Bromley, E Bignell, ... The International Journal of Biostatistics, 2019 | 11 | 2019 |
| BayesBinMix: an R Package for Model Based Clustering of Multivariate Binary Data P Papastamoulis, M Rattray The R Journal 9 (1), 403-420, 2017 | 11 | 2017 |
| Overfitting Bayesian Mixtures of Factor Analyzers with an Unknown Number of Components P Papastamoulis Computational Statistics & Data Analysis 124, 220 - 234, 2018 | 10 | 2018 |
| A Bayesian model selection approach for identifying differentially expressed transcripts from RNA sequencing data P Papastamoulis, M Rattray Journal of the Royal Statistical Society Series C: Applied Statistics 67 (1 …, 2018 | 9 | 2018 |
| Clustering Multivariate Data using Factor Analytic Bayesian Mixtures with an Unknown Number of Components P Papastamoulis Statistics and Computing 30, 485-506, 2020 | 8 | 2020 |
| Bayesian estimation of Differential Transcript Usage from RNA-seq data P Papastamoulis, M Rattray Statistical Applications in Genetics and Molecular Biology 16 (5-6), 387 - 405, 2017 | 5 | 2017 |
| Distinct cohorts of Aspergillus fumigatus transcription factors are required for epithelial damage occurring via contact-or soluble effector-mediated mechanisms S Rahman, N Van Rhijn, P Papastamoulis, DD Thomson, Z Carter, ... Frontiers in Cellular and Infection Microbiology 12 (10.3389/fcimb.2022.907519), 2022 | 4 | 2022 |
| poisson.glm.mix: Fit high dimensional mixtures of Poisson GLMs P Papastamoulis, ML Martin-Magniette, C Maugis-Rabusseau http://cran.r-project.org/web/packages/poisson.glm.mix/index.html, 2012 | 1* | 2012 |
| Package ‘bayesCureRateModel’ P Papastamoulis, F Milienos | | 2024 |
| Multinomial mixture for spatial data A Nalpantidi, D Karlis, P Papastamoulis arXiv preprint arXiv:2402.09888, 2024 | | 2024 |
Magnus RattrayUniversity of Manchester在 manchester.ac.uk 的电子邮件经过验证
