Papers using TMB

Mollie Brooks edited this page Dec 14, 2017 · 26 revisions

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

In press

  • Wang, S., Cadigan, N.G., and Benoît, H. 2016. Inference about regression parameters using highly stratified survey count data with over-dispersion and repeated measurements. Journal of Applied Statistics. In Press.
  • C. Konrad, N.G. Cadigan, and J. Brattey. 2016. Reporting rate of tagging experiments for cod (Gadus morhua). Environmental and Ecological Statistics. In press.
  • Thorson, J.T., and Barnett, L.A.K. In press. Comparing estimates of abundance trends and distribution shifts using single- and multispecies models of fishes and biogenic habitat. ICES J. Mar. Sci.
  • Thorson, J.T., Fonner, R., Haltuch, M., Ono, K., and Winker, H. In press. 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. (
  • Kai, Mikihiko, Thorson, J. T., Piner, Kevin, and Maunder, Mark N. In press. 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., Munch, S, and Swain, D. In press. Identifying partial regulation in community dynamics using spatio-temporal models. Ecology.
  • Albertsen, C. M., Nielsen, A., and Thygesen, U. H. In press. Choosing the observational likelihood in state-space stock assessment models. Canadian Journal of Fisheries and Aquatic Sciences. doi: 10.1139/cjfas-2015-0532
  • Whoriskey, K., Auger-Méthé, M., Albertsen, C. M., Whoriskey, F. G., Binder, T. R., Krueger, C. C., and Flemming, J. M. In press. A Hidden Markov Movement Model for rapidly identifying behavioral states from animal tracks. Ecology and Evolution. doi: 10.1002/ece3.2795


  • 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.



  • 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. (
  • 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. (
  • 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.
  • 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. (
  • 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.
  • 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
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