Identifying polyglutamine protein species in situ that best predict neurodegeneration J Miller, M Arrasate, E Brooks, CP Libeu, J Legleiter, D Hatters, J Curtis, ... Nature chemical biology 7 (12), 925-934, 2011 | 242 | 2011 |
Quantitative relationships between huntingtin levels, polyglutamine length, inclusion body formation, and neuronal death provide novel insight into huntington's disease … J Miller, M Arrasate, BA Shaby, S Mitra, E Masliah, S Finkbeiner Journal of Neuroscience 30 (31), 10541-10550, 2010 | 202 | 2010 |
A hierarchical max-stable spatial model for extreme precipitation BJ Reich, BA Shaby The annals of applied statistics 6 (4), 1430, 2012 | 199 | 2012 |
Proteostasis of polyglutamine varies among neurons and predicts neurodegeneration AS Tsvetkov, M Arrasate, S Barmada, DM Ando, P Sharma, BA Shaby, ... Nature chemical biology 9 (9), 586-592, 2013 | 198 | 2013 |
Estimation and prediction in spatial models with block composite likelihoods J Eidsvik, BA Shaby, BJ Reich, M Wheeler, J Niemi Journal of Computational and Graphical Statistics 23 (2), 295-315, 2014 | 174 | 2014 |
Nrf2 mitigates LRRK2-and α-synuclein–induced neurodegeneration by modulating proteostasis G Skibinski, V Hwang, DM Ando, A Daub, AK Lee, A Ravisankar, ... Proceedings of the National Academy of Sciences 114 (5), 1165-1170, 2017 | 119 | 2017 |
The role of the range parameter for estimation and prediction in geostatistics CG Kaufman, BA Shaby Biometrika 100 (2), 473-484, 2013 | 119 | 2013 |
Tapered covariance: Bayesian estimation and asymptotics B Shaby, D Ruppert Journal of Computational and Graphical Statistics 21 (2), 433-452, 2012 | 86 | 2012 |
Exploring an adaptive Metropolis algorithm B Shaby, MT Wells Currently under review 1 (1), 17, 2010 | 80 | 2010 |
Machine learning for modeling animal movement DA Wijeyakulasuriya, EW Eisenhauer, BA Shaby, EM Hanks PloS one 15 (7), e0235750, 2020 | 63 | 2020 |
A hierarchical model for serially-dependent extremes: A study of heat waves in the western US BJ Reich, BA Shaby, D Cooley Journal of Agricultural, Biological, and Environmental Statistics 19, 119-135, 2014 | 59 | 2014 |
Bayesian spatial extreme value analysis to assess the changing risk of concurrent high temperatures across large portions of European cropland BA Shaby, BJ Reich Environmetrics 23 (8), 638-648, 2012 | 50 | 2012 |
A hierarchical max-infinitely divisible spatial model for extreme precipitation GP Bopp, BA Shaby, R Huser Journal of the American Statistical Association 116 (533), 93-106, 2021 | 46 | 2021 |
The open-faced sandwich adjustment for MCMC using estimating functions BA Shaby Journal of Computational and Graphical Statistics 23 (3), 853-876, 2014 | 38 | 2014 |
A spatial Markov model for climate extremes BJ Reich, BA Shaby Journal of Computational and Graphical Statistics 28 (1), 117-126, 2019 | 28 | 2019 |
Estimating spatially varying severity thresholds of a forest fire danger rating system using max-stable extreme-event modeling AG Stephenson, BA Shaby, BJ Reich, AL Sullivan Journal of Applied Meteorology and Climatology 54 (2), 395-407, 2015 | 28 | 2015 |
Hierarchical transformed scale mixtures for flexible modeling of spatial extremes on datasets with many locations L Zhang, BA Shaby, JL Wadsworth Journal of the American Statistical Association 117 (539), 1357-1369, 2022 | 24 | 2022 |
A semiparametric spatiotemporal Bayesian model for the bulk and extremes of the Fosberg Fire Weather Index A Hazra, BJ Reich, BA Shaby, AM Staicu arXiv preprint arXiv:1812.11699, 2018 | 22* | 2018 |
A Markov-switching model for heat waves BA Shaby, BJ Reich, D Cooley, CG Kaufman | 21 | 2016 |
Discussion of" statistical modeling of spatial extremes" by ac davison, sa padoan and m. ribatet D Gabda, R Towe, J Wadsworth, J Tawn Statistical science 27 (2), 189-192, 2012 | 19 | 2012 |