| Programming with models: writing statistical algorithms for general model structures with NIMBLE P de Valpine, D Turek, CJ Paciorek, C Anderson-Bergman, DT Lang, ... Journal of Computational and Graphical Statistics 26 (2), 403-413, 2017 | 765 | 2017 |
| NIMBLE: MCMC, particle filtering, and programmable hierarchical modeling P de Valpine, C Paciorek, D Turek, N Michaud, C Anderson-Bergman, ... R package version 0.11 1, 2021 | 114 | 2021 |
| The practice of reproducible research: case studies and lessons from the data-intensive sciences J Kitzes, D Turek, F Deniz Univ of California Press, 2018 | 114 | 2018 |
| Diversity of artists in major US museums CM Topaz, B Klingenberg, D Turek, B Heggeseth, PE Harris, ... PloS one 14 (3), e0212852, 2019 | 111 | 2019 |
| Estimating and forecasting spatial population dynamics of apex predators using transnational genetic monitoring R Bischof, C Milleret, P Dupont, J Chipperfield, M Tourani, A Ordiz, ... Proceedings of the National Academy of Sciences 117 (48), 30531-30538, 2020 | 100 | 2020 |
| Model-averaged Wald confidence intervals D Turek, D Fletcher Computational Statistics & Data Analysis 56 (9), 2809-2815, 2012 | 59 | 2012 |
| Metabolic rate interacts with resource availability to determine individual variation in microhabitat use in the wild SK Auer, RD Bassar, D Turek, GJ Anderson, S McKelvey, JD Armstrong, ... The American Naturalist 196 (2), 132-144, 2020 | 53 | 2020 |
| Efficient Markov chain Monte Carlo sampling for hierarchical hidden Markov models D Turek, P de Valpine, CJ Paciorek Environmental and ecological statistics 23, 549-564, 2016 | 45 | 2016 |
| Recommendations to funding agencies for supporting reproducible research K Broman, M Cetinkaya-Rundel, A Nussbaum, C Paciorek, R Peng, ... American Statistical Association 2, 1-4, 2017 | 40 | 2017 |
| Efficient estimation of large‐scale spatial capture–recapture models D Turek, C Milleret, T Ergon, H Brøseth, P Dupont, R Bischof, ... Ecosphere 12 (2), e03385, 2021 | 39 | 2021 |
| NIMBLE user manual P de Valpine, C Paciorek, D Turek, N Michaud, C Anderson-Bergman, ... R package manual version 0.9 1, 2020 | 37 | 2020 |
| IPM2: toward better understanding and forecasting of population dynamics F Plard, D Turek, MU Grüebler, M Schaub Ecological Monographs 89 (3), e01364, 2019 | 33 | 2019 |
| Model-averaged profile likelihood intervals D Fletcher, D Turek Journal of Agricultural, Biological, and Environmental Statistics 17, 38-51, 2012 | 33 | 2012 |
| One size does not fit all: Customizing MCMC methods for hierarchical models using NIMBLE LC Ponisio, P de Valpine, N Michaud, D Turek Ecology and evolution 10 (5), 2385-2416, 2020 | 29 | 2020 |
| Automated parameter blocking for efficient Markov chain Monte Carlo sampling D Turek, P de Valpine, CJ Paciorek, C Anderson-Bergman | 29 | 2017 |
| nimbleSCR: spatial capture-recapture (SCR) methods using ‘nimble’ R Bischof, D Turek, C Milleret, T Ergon, P Dupont, P de Valpine R package version 0.1. 0, 2020 | 22 | 2020 |
| Estimating abundance with interruptions in data collection using open population spatial capture–recapture models C Milleret, P Dupont, J Chipperfield, D Turek, H Brøseth, O Gimenez, ... Ecosphere 11 (7), e03172, 2020 | 20 | 2020 |
| Bayesian inference for high-dimensional nonstationary Gaussian processes MD Risser, D Turek Journal of Statistical Computation and Simulation 90 (16), 2902-2928, 2020 | 19 | 2020 |
| Distribution and abundance of Hector's dolphins off Otago, New Zealand J Turek, E Slooten, S Dawson, W Rayment, D Turek New Zealand Journal of Marine and Freshwater Research 47 (2), 181-191, 2013 | 16 | 2013 |
| Design of efficient digital interpolation filters for integer upsampling DB Turek Massachusetts Institute of Technology, 2004 | 16 | 2004 |
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