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TMB: Automatic Differentiation and Laplace Approximation

Citations

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Cited by:

  1. Craiu, Radu V. & Duchesne, Thierry, 2018. "A scalable and efficient covariate selection criterion for mixed effects regression models with unknown random effects structure," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 154-161.
  2. Céline Cunen & Nils Lid Hjort, 2022. "Combining information across diverse sources: The II‐CC‐FF paradigm," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(2), pages 625-656, June.
  3. Katherine Wilson & Jon Wakefield, 2022. "A probabilistic model for analyzing summary birth history data," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 47(11), pages 291-344.
  4. Herbert Susmann & Monica Alexander & Leontine Alkema, 2022. "Temporal Models for Demographic and Global Health Outcomes in Multiple Populations: Introducing a New Framework to Review and Standardise Documentation of Model Assumptions and Facilitate Model Compar," International Statistical Review, International Statistical Institute, vol. 90(3), pages 437-467, December.
  5. Aaron Osgood‐Zimmerman & Jon Wakefield, 2023. "A Statistical Review of Template Model Builder: A Flexible Tool for Spatial Modelling," International Statistical Review, International Statistical Institute, vol. 91(2), pages 318-342, August.
  6. David L. Miller & Richard Glennie & Andrew E. Seaton, 2020. "Understanding the Stochastic Partial Differential Equation Approach to Smoothing," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(1), pages 1-16, March.
  7. Ding, Bowei & Karunamuni, Rohana J. & Wu, Jingjing, 2025. "Minimum profile Hellinger distance estimation of general covariate models," Computational Statistics & Data Analysis, Elsevier, vol. 202(C).
  8. Wei Zhang & Simon J. Bonner & Rachel S. McCrea, 2023. "Latent multinomial models for extended batch‐mark data," Biometrics, The International Biometric Society, vol. 79(3), pages 2732-2742, September.
  9. Théo Michelot & Richard Glennie & Catriona Harris & Len Thomas, 2021. "Varying-Coefficient Stochastic Differential Equations with Applications in Ecology," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(3), pages 446-463, September.
  10. Ingrid Sandvig Thorsen & Bård Støve & Hans J. Skaug, 2023. "A TMB Approach to Study Spatial Variation in Weather-Generated Claims in Insurance," SN Operations Research Forum, Springer, vol. 4(4), pages 1-27, December.
  11. Øystein Sørensen & Anders M. Fjell & Kristine B. Walhovd, 2023. "Longitudinal Modeling of Age-Dependent Latent Traits with Generalized Additive Latent and Mixed Models," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 456-486, June.
  12. Ruggero Bellio & Nicola Soriani, 2021. "Maximum likelihood estimation based on the Laplace approximation for p2 network regression models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(1), pages 24-41, February.
  13. Jenni Niku & Francis K. C. Hui & Sara Taskinen & David I. Warton, 2021. "Analyzing environmental‐trait interactions in ecological communities with fourth‐corner latent variable models," Environmetrics, John Wiley & Sons, Ltd., vol. 32(6), September.
  14. Simon N. Wood, 2020. "Inference and computation with generalized additive models and their extensions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(2), pages 307-339, June.
  15. Yan Cui & Qi Li & Fukang Zhu, 2020. "Flexible bivariate Poisson integer-valued GARCH model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(6), pages 1449-1477, December.
  16. Devin S. Johnson & Brian M. Brost & Mevin B. Hooten, 2022. "Greater Than the Sum of its Parts: Computationally Flexible Bayesian Hierarchical Modeling," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 382-400, June.
  17. Lamarche, Carlos & Shi, Xuan & Young, Derek S., 2024. "Conditional Quantile Functions for Zero-Inflated Longitudinal Count Data," Econometrics and Statistics, Elsevier, vol. 31(C), pages 49-65.
  18. David M Keith & Jessica A Sameoto & Freya M Keyser & Christine A Ward-Paige, 2020. "Evaluating socio-economic and conservation impacts of management: A case study of time-area closures on Georges Bank," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-25, October.
  19. Ingvild M. Helgøy & Hans J. Skaug, 2022. "The Sibling Distribution for Multivariate Life Time Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(1), pages 340-363, May.
  20. Daniel Ovando & Gary D. Libecap & Katherine D. Millage & Lennon Thomas, 2020. "Coasean Approaches to Ending Overfishing: Bigeye Tuna Conservation in the Western and Central Pacific Ocean," NBER Working Papers 27801, National Bureau of Economic Research, Inc.
  21. William H. Aeberhard & Eva Cantoni & Chris Field & Hans R. Künsch & Joanna Mills Flemming & Ximing Xu, 2021. "Robust estimation for discrete‐time state space models," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(4), pages 1127-1147, December.
  22. Andreia Monteiro & Raquel Menezes & Maria Eduarda Silva, 2021. "Modelling informative time points: an evolutionary process approach," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 364-382, June.
  23. Cole C Monnahan & Kasper Kristensen, 2018. "No-U-turn sampling for fast Bayesian inference in ADMB and TMB: Introducing the adnuts and tmbstan R packages," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-10, May.
  24. Andersson, Jonas & Sheybanivaziri, Samaneh, 2023. "Probabilistic forecasting of electricity prices using an augmented LMARX-model," Discussion Papers 2023/11, Norwegian School of Economics, Department of Business and Management Science.
  25. Daniel McGuire & Havell Markus & Lina Yang & Jingyu Xu & Austin Montgomery & Arthur Berg & Qunhua Li & Laura Carrel & Dajiang J. Liu & Bibo Jiang, 2024. "Dissecting heritability, environmental risk, and air pollution causal effects using > 50 million individuals in MarketScan," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
  26. Roland Langrock & Timo Adam & Vianey Leos‐Barajas & Sina Mews & David L. Miller & Yannis P. Papastamatiou, 2018. "Spline‐based nonparametric inference in general state‐switching models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 179-200, August.
  27. Ben C. Stevenson & Rachel M. Fewster & Koustubh Sharma, 2022. "Spatial correlation structures for detections of individuals in spatial capture–recapture models," Biometrics, The International Biometric Society, vol. 78(3), pages 963-973, September.
  28. Riki Herliansyah & Ruth King & Stuart King, 2022. "Laplace Approximations for Capture–Recapture Models in the Presence of Individual Heterogeneity," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(3), pages 401-418, September.
  29. Han, Jeongseop & Lee, Youngjo, 2024. "Enhanced Laplace approximation," Journal of Multivariate Analysis, Elsevier, vol. 202(C).
  30. Ethan Lawler & Kim Whoriskey & William H. Aeberhard & Chris Field & Joanna Mills Flemming, 2019. "The Conditionally Autoregressive Hidden Markov Model (CarHMM): Inferring Behavioural States from Animal Tracking Data Exhibiting Conditional Autocorrelation," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(4), pages 651-668, December.
  31. Yuan Yan & Eva Cantoni & Chris Field & Margaret Treble & Joanna Mills Flemming, 2023. "Spatiotemporal modeling of mature‐at‐length data using a sliding window approach," Environmetrics, John Wiley & Sons, Ltd., vol. 34(2), March.
  32. Flores-Agreda, Daniel & Cantoni, Eva, 2019. "Bootstrap estimation of uncertainty in prediction for generalized linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 130(C), pages 1-17.
  33. Maunder, Mark N., 2024. "Towards a comprehensive framework for providing management advice from statistical inference using population dynamics models," Ecological Modelling, Elsevier, vol. 498(C).
  34. Geir D. Berentsen & Jan Bulla & Antonello Maruotti & Bård Støve, 2022. "Modelling clusters of corporate defaults: Regime‐switching models significantly reduce the contagion source," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(3), pages 698-722, June.
  35. Junker, Rune Grønborg & Kallesøe, Carsten Skovmose & Real, Jaume Palmer & Howard, Bianca & Lopes, Rui Amaral & Madsen, Henrik, 2020. "Stochastic nonlinear modelling and application of price-based energy flexibility," Applied Energy, Elsevier, vol. 275(C).
  36. Xin Jin, 2021. "Can we imitate the principal investor's behavior to learn option price?," Papers 2105.11376, arXiv.org, revised Jan 2022.
  37. Paul Roddy & Ursula Dalrymple & Tomas O Jensen & Sabine Dittrich & V Bhargavi Rao & Daniel A Pfeffer & Katherine A Twohig & Teri Roberts & Oscar Bernal & Ethan Guillen, 2019. "Quantifying the incidence of severe-febrile-illness hospital admissions in sub-Saharan Africa," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-19, July.
  38. Jenni Niku & David I. Warton & Francis K. C. Hui & Sara Taskinen, 2017. "Generalized Linear Latent Variable Models for Multivariate Count and Biomass Data in Ecology," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(4), pages 498-522, December.
  39. Benny Ren & Ian Barnett, 2023. "Combining mixed effects hidden Markov models with latent alternating recurrent event processes to model diurnal active–rest cycles," Biometrics, The International Biometric Society, vol. 79(4), pages 3402-3417, December.
  40. Tim C. D. Lucas & Anita K. Nandi & Elisabeth G. Chestnutt & Katherine A. Twohig & Suzanne H. Keddie & Emma L. Collins & Rosalind E. Howes & Michele Nguyen & Susan F. Rumisha & Andre Python & Rohan Ara, 2021. "Mapping malaria by sharing spatial information between incidence and prevalence data sets," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 733-749, June.
  41. Zheng, Nan & Cadigan, Noel, 2021. "Frequentist delta-variance approximations with mixed-effects models and TMB," Computational Statistics & Data Analysis, Elsevier, vol. 160(C).
  42. Mikkel L. Sørensen & Peter Nystrup & Mathias B. Bjerregård & Jan K. Møller & Peder Bacher & Henrik Madsen, 2023. "Recent developments in multivariate wind and solar power forecasting," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 12(2), March.
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