Papers using TMB

List of papers that uses TMB (first come, first served):

2019

• Weiss D.J., Lucas T.C.D., Nguyen M., et al. (2019) Mapping the global prevalence, incidence, and mortality of Plasmodium falciparum, 2000–17: a spatial and temporal modelling study. Lancet. doi: 10.1016/S0140-6736(19)31097-9
• Battle K.E., Lucas T.C.D., Nguyen M., et al. (2019) Mapping the global endemicity and clinical burden of Plasmodium vivax, 2000–17: a spatial and temporal modelling study. Lancet. doi: 10.1016/S0140-6736(19)31096-7

2017

• Whoriskey, K., Auger-Méthé, M., Albertsen, C. M., Whoriskey, F. G., Binder, T. R., Krueger, C. C., and Flemming, J. M. 2017. A Hidden Markov Movement Model for rapidly identifying behavioral states from animal tracks. Ecology and Evolution. doi: 10.1002/ece3.2795
• Thorson, J., Munch, S, and Swain, D. 2017. Estimating partial regulation in spatiotemporal models of community dynamics. Ecology.
• Kai, Mikihiko, Thorson, J. T., Piner, Kevin, and Maunder, Mark N. 2017. Spatio-temporal variation in size-structured populations using fishery data: an application to shortfin mako (Isurus oxyrinchus) in the Pacific Ocean. Canadian Journal of Fisheries and Aquatic Sciences
• Thorson, J.T., Fonner, R., Haltuch, M., Ono, K., and Winker, H. 2017. Accounting for spatiotemporal variation and fisher targeting when estimating abundance from multispecies fishery data. Can. J. Fish. Aquat. Sci. doi:10.1139/cjfas-2015-0598. (http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0598)
• Thorson, J.T., and Barnett, L.A.K. 2017. Comparing estimates of abundance trends and distribution shifts using single- and multispecies models of fishes and biogenic habitat. ICES J. Mar. Sci.
• Wang, S., Cadigan, N.G., and Benoît, H. 2017. Inference about regression parameters using highly stratified survey count data with over-dispersion and repeated measurements. Journal of Applied Statistics. http://www.tandfonline.com/doi/full/10.1080/02664763.2016.1191622
• Auger-Méthé, M., Albertsen, C. M., Jonsen, I. D., Derocher, A. E., Lidgard, D. C., Studholme, K. R., Bowen, W. D., Crossin, G. T., and Flemming, J. M. 2017. Spatiotemporal modelling of marine movement data using Template Model Builder. Marine Ecology Progress Series 565:237-249. doi: 10.3354/meps12019
• Brooks, M. E., Clements, C., Pemberton, J., and Ozgul, A. 2017. Estimation of Individual Growth Trajectories When Repeated Measures Are Missing. The American Naturalist 190(3): 377-388. https://doi.org/10.1086/692797

2016

• C. Konrad, N.G. Cadigan, and J. Brattey. 2016. Reporting rate of tagging experiments for cod (Gadus morhua). Environmental and Ecological Statistics. http://link.springer.com/article/10.1007/s10651-016-0344-0?wt_mc=internal.event.1.SEM.ArticleAuthorOnlineFirst
• Albertsen, C. M., Nielsen, A., and Thygesen, U. H. 2016. Choosing the observational likelihood in state-space stock assessment models. Canadian Journal of Fisheries and Aquatic Sciences. doi: 10.1139/cjfas-2015-0532
• Berg, C. W., & Nielsen, A. 2016. Accounting for correlated observations in an age-based state-space stock assessment model. ICES Journal of Marine Science, 73(7), 1788-1797.
• Thorson, J., Pinsky, M., and Ward, E. 2016. Model-based inference for estimating shifts in species distribution, area occupied, and center of gravity. Methods in Ecology and Evolution, 7(8): 990–1002. DOI: 10.1111/2041-210X.12567. (http://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12567/abstract?campaign=woletoc)
• Kristensen, K., Nielsen, A., Berg, C.W., Skaug, H.J., Bell, B. 2016, TMB: Automatic Differentiation and Laplace Approximation https://www.jstatsoft.org/article/view/v070i05
• Cadigan, N.G. 2016. A state-space stock assessment model for northern cod, including under-reported catches and variable natural mortality rates." Canadian Journal of Fisheries and Aquatic Sciences 73(2), 296-308 (http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2015-0047)
• Webber, D.N., and Thorson, J.T. 2016. Variation in growth among individuals and over time: A case study and simulation experiment involving tagged Antarctic toothfish. Fish. Res. 180: 67–76. doi:10.1016/j.fishres.2015.08.016. (http://www.sciencedirect.com/science/article/pii/S016578361530062X)
• Thorson, J.T., and Kristensen, K. 2016. Implementing a generic method for bias correction in statistical models using random effects, with spatial and population dynamics examples. Fish. Res. 175: 66–74. doi:10.1016/j.fishres.2015.11.016. (http://www.sciencedirect.com/science/article/pii/S0165783615301399)
• Auger-Méthé, M., Field, C., Albertsen, C.M., Derocher, A.E., Lewis, M.A., Jonsen, I.D. and Mills Flemming, J. 2016. State-space model's dirty little secrets: even simple linear Gaussian models can have estimation problems. Scientific Reports 6:26677. doi: 10.1038/srep26677. (http://www.nature.com/articles/srep26677)
• Thorson, J.T., Jannot, J.E., and Somers, K. In press. Using spatio-temporal models of population growth and movement to monitor overlap between human impacts and population density. J. Appl. Ecol. (http://onlinelibrary.wiley.com/doi/10.1111/1365-2664.12664/abstract)
• Thorson, J.T., Ianelli, J.N., Larsen, E., Ries, L., Scheuerell, M.D., Szuwalski, C., and Zipkin, E. 2016. Joint dynamic species distribution models: a tool for community ordination and spatiotemporal monitoring. Glob. Ecol. Biogeogr. 25(9): 1144–1158. doi:10.1111/geb.12464. (http://onlinelibrary.wiley.com/doi/10.1111/geb.12464/abstract.)
• Thorson, J.T., Rindorf, A., Gao, J., Hanselman, D.H., and Winker, H. 2016. Density-dependent changes in effective area occupied for sea-bottom-associated marine fishes. Proc R Soc B 283(1840): 20161853. doi:10.1098/rspb.2016.1853. (http://rspb.royalsocietypublishing.org/content/283/1840/20161853)

2015

• Thorson, J.T., Ianelli, J.N., Munch, S.B., Ono, K., and Spencer, P.D. 2015. Spatial delay-difference models for estimating spatiotemporal variation in juvenile production and population abundance. Can. J. Fish. Aquat. Sci. 72(12): 1897–1915. doi:10.1139/cjfas-2014-0543. (http://www.nrcresearchpress.com/doi/abs/10.1139/cjfas-2014-0543)
• Thorson, J., Skaug, H., Kristensen, K., Shelton, A., Ward, E., Harms, J., and Benante, J. 2015. The importance of spatial models for estimating the strength of density dependence. Ecology. 96:1202–1212. (http://www.esajournals.org/doi/abs/10.1890/14-0739.1)
• Thorson, J. Shelton, A., Ward, E., and Skaug, H. 2015. Geostatistical delta-generalized linear mixed models improve precision for estimated abundance indices for West Coast groundfishes. ICES Journal of Marine Science. 72 (5): 1297-1310. http://icesjms.oxfordjournals.org/content/72/5/1297.abstract?etoc
• Thorson, J.T., Scheuerell, M.D., Shelton, A.O., See, K.E., Skaug, H.J., and Kristensen, K. 2015. Spatial factor analysis: a new tool for estimating joint species distributions and correlations in species range. Methods Ecol. Evol. 6(6): 627–637. doi:10.1111/2041-210X.12359. (http://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12359/abstract)
• Thorson, J. 2015. Spatio-temporal variation in fish condition is not consistently explained by density, temperature, or season for Northeast Pacific groundfishes. Mar. Ecol. Progress Series. 526:101-112. http://www.int-res.com/abstracts/meps/v526/p101-112/
• Albertsen, C. M., Whoriskey, K., Yurkowski, D., Nielsen, A., and Flemming, J. M. 2015. Fast fitting of non-Gaussian state-space models to animal movement data via Template Model Builder. Ecology 96(10):2598-2604. doi: 10.1890/14-2101.1
• Karlsen, J. D., Krag, L. A., Albertsen, C. M., and Frandsen, R. P. 2015. From Fishing to Fish Processing: Separation of Fish from Crustaceans in the Norway Lobster-Directed Multispecies Trawl Fishery Improves Seafood Quality. PLoS ONE 10(11):e0140864. doi: 10.1371/journal.pone.0140864