26 Publikationen
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2024 | Zeitschriftenaufsatz | E-Veröff. vor dem Druck | PUB-ID: 2999960Lennox, R. J., Adam, T., Riha, M., Klappstein, N., Monk, C. T., Vollset, K. W., & Beumer, L. T. (2024). Movement in 3D: Novel Opportunities for Understanding Animal Behaviour and Space Use. Ethology . https://doi.org/10.1111/eth.13529PUB | DOI | WoS
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2024 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2990082Adam, T., Ötting, M., & Michels, R. (2024). Markov-switching decision trees. AStA Advances in Statistical Analysis, 108(2), 461–476. https://doi.org/10.1007/s10182-024-00501-6PUB | PDF | DOI | WoS
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2023 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2982750Glennie, R., Adam, T., Leos‐Barajas, V., Michelot, T., Photopoulou, T., & McClintock, B. T. (2023). Hidden Markov models: pitfalls and opportunities in ecology. Methods in Ecology and Evolution, 14(1), 43-56. https://doi.org/10.1111/2041-210X.13801PUB | DOI
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2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982760Adam, T., Ötting, M., & Michels, R. (2023). State-switching decision trees. In E. Bergherr, A. Groll, & A. Mayr (Eds.), Proceedings of the 37th International Workshop on Statistical Modelling. Part II (pp. 321-325). Dortmund: TU Dortmund.PUB
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2022 | Blogbeitrag | Veröffentlicht | PUB-ID: 2982761Adam, T. (2022). Hidden Markov models have pitfalls…. Methods Blog: the Latest Methods in Ecology and EvolutionPUB | Download (ext.)
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2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982759Adam, T., Glennie, R., & Michelot, T. (2022). State-switching varying-coefficient stochastic differential equations. In N. Torelli, R. Bellio, & V. Muggeo (Eds.), Proceedings of the 36th International Workshop on Statistical Modelling. Part II (pp. 53-57). Edizioni Università di Trieste.PUB
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2022 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2961460Nathan, R., Monk, C. T., Arlinghaus, R., Adam, T., Alos, J., Assaf, M., Baktoft, H., et al. (2022). Big-data approaches lead to an increased understanding of the ecology of animal movement. Science, 375(6582), eabg1780. https://doi.org/10.1126/science.abg1780PUB | DOI | WoS | PubMed | Europe PMC
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2022 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2963807Pohle, J. M., Adam, T., & Beumer, L. T. (2022). Flexible estimation of the state dwell-time distribution in hidden semi-Markov models. Computational Statistics & Data Analysis , 172, 107479. https://doi.org/10.1016/j.csda.2022.107479PUB | DOI | WoS
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2022 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2962700Adam, T., Mayr, A., & Kneib, T. (2022). Gradient boosting in Markov-switching generalized additive models for location, scale, and shape. Econometrics and Statistics , 22, 3-16. https://doi.org/10.1016/j.ecosta.2021.04.002PUB | DOI | WoS
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2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2955071Nagel, R., Mews, S., Adam, T., Stainfield, C., Fox-Clarke, C., Toscani, C., Langrock, R., et al. (2021). Movement patterns and activity levels are shaped by the neonatal environment in Antarctic fur seal pups. Scientific reports, 11(1), 14323. https://doi.org/10.1038/s41598-021-93253-1PUB | PDF | DOI | WoS | PubMed | Europe PMC | Preprint
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2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2982762Aquino‐Baleytó, M., Leos‐Barajas, V., Adam, T., Hoyos‐Padilla, M., Santana‐Morales, O., Galván‐Magaña, F., González‐Armas, R., et al. (2021). Diving deeper into the underlying white shark behaviors at Guadalupe Island, Mexico. Ecology and Evolution, 11(21), 14932-14949. https://doi.org/10.1002/ece3.8178PUB | DOI
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2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2982757Lennox, R. J., Westrelin, S., Souza, A. T., Šmejkal, M., Říha, M., Prchalová, M., Nathan, R., et al. (2021). A role for lakes in revealing the nature of animal movement using high dimensional telemetry systems. Movement Ecology, 9(1), 40. https://doi.org/10.1186/s40462-021-00244-yPUB | DOI | WoS | PubMed | Europe PMC
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2021 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2957037Oelschläger, L., & Adam, T. (2021). Detecting bearish and bullish markets in financial time series using hierarchical hidden Markov models. Statistical Modelling, 23(2), 107-126. https://doi.org/10.1177/1471082X211034048PUB | DOI | WoS
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2021 | Wissenschaftliche Software | PUB-ID: 2982764Oelschläger, L., Adam, T., & Michels, R. (2021). fHMM: fitting hidden Markov models to financial data (R package). CRAN.PUB
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2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982766Adam, T., & Oelschläger, L. (2020). Hidden Markov models for multi-scale time series: an application to stock market data. In I. Irigoien, D. - J. Lee, J. Martínez-Minaya, & M. X. Rodríguez-Álvarez (Eds.), Proceedings of the 35th International Workshop on Statistical Modelling. Part I (pp. 2-7). Bilbao: Universidad del País Vasco.PUB
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2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982763Pohle, J. M., Adam, T., Langrock, R., & Beumer, L. (2020). Flexible estimation of the state dwell-time distribution in hidden semi-Markov models. In I. Irigoien, D. - J. Lee, J. Martínez-Minaya, & M. X. Rodríguez-Álvarez (Eds.), Proceedings of the 35th International Workshop on Statistical Modelling. Part I (pp. 189-193). Bilbao: Universidad del País Vasco.PUB
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2019 | Wissenschaftliche Software | PUB-ID: 2982765Adam, T. (2019). countHMM: penalized estimation of flexible hidden Markov models for time series of counts (R package). CRAN.PUB
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2019 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2941675Adam, T., Langrock, R., & Weiß, C. (2019). Non-parametric inference in hidden Markov models for time series of counts. Proceedings of the 34th International Workshop on Statistical Modelling, Volume I, 135-140.PUB
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2019 | Konferenzbeitrag | PUB-ID: 2941674Adam, T., Langrock, R., & Kneib, T. (2019). Model-based clustering of time series data: a flexible approach using non-parametric state-switching quantile regression models. Proceedings of the 12th Scientific Meeting on Classification and Data Analysis, 19-22.PUB
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2019 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2937689Adam, T., Griffiths, C. A., Leos-Barajas, V., Meese, E. N., Lowe, C. G., Blackwell, P. G., Righton, D., et al. (2019). Joint modelling of multi‐scale animal movement data using hierarchical hidden Markov models. Methods in Ecology and Evolution, 10(9), 1536-1550. doi:10.1111/2041-210x.13241PUB | DOI | WoS
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2018 | Konferenzbeitrag | PUB-ID: 2933002Adam, T., Mayr, A., Kneib, T., & Langrock, R. (2018). Statistical boosting for Markov-switching distributional regression models. Proceedings of the 33rd International Workshop on Statistical Modelling, Vol. 1, 30-35.PUB
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2018 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2916816Langrock, R., Adam, T., Leos-Barajas, V., Mews, S., Miller, D. L., & Papastamatiou, Y. P. (2018). Spline-based nonparametric inference in general state-switching models. Statistica Neerlandica, 72(3), 179-200. doi:10.1111/stan.12133PUB | DOI | Download (ext.) | WoS
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2017 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2911528Leos-Barajas, V., Gangloff, E. J., Adam, T., Langrock, R., van Beest, F. M., Nabe-Nielsen, J., & Morales, J. M. (2017). Multi-scale modeling of animal movement and general behavior data using hidden Markov models with hierarchical structures. Journal of Agricultural, Biological and Environmental Statistics, 22(3), 232–248. https://doi.org/10.1007/s13253-017-0282-9PUB | DOI | WoS
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2017 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2913894Adam, T., Leos-Barajas, V., Langrock, R., & van Beest, F. (2017). Using hierarchical hidden Markov models for joint inference at multiple temporal scales. In M. Grzegorczyk & G. Ceoldo (Eds.), Proceedings of the 32nd International Workshop on Statistical Modelling, Vol. 2, Groningen, Netherlands 3-7 July, 2017 Groningen: Univ. of Groningen.PUB