Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Prado, Estevao"'
The Metropolis-Hastings (MH) algorithm is one of the most widely used Markov Chain Monte Carlo schemes for generating samples from Bayesian posterior distributions. The algorithm is asymptotically exact, flexible and easy to implement. However, in th
Externí odkaz:
http://arxiv.org/abs/2407.19602
We propose an extension of the N-mixture model which allows for the estimation of both abundances of multiple species simultaneously and their inter-species correlations. We also propose further extensions to this multi-species N-mixture model, one o
Externí odkaz:
http://arxiv.org/abs/2109.14966
Autor:
Prado, Estevão B., Parnell, Andrew C., Murphy, Keefe, McJames, Nathan, O'Shea, Ann, Moral, Rafael A.
We propose some extensions to semi-parametric models based on Bayesian additive regression trees (BART). In the semi-parametric BART paradigm, the response variable is approximated by a linear predictor and a BART model, where the linear component is
Externí odkaz:
http://arxiv.org/abs/2108.07636
Publikováno v:
Statistics and Computing 31, 20 (2021)
Bayesian Additive Regression Trees (BART) is a tree-based machine learning method that has been successfully applied to regression and classification problems. BART assumes regularisation priors on a set of trees that work as weak learners and is ver
Externí odkaz:
http://arxiv.org/abs/2006.07493
Akademický článek
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Publikováno v:
Environmental and Ecological Statistics. 29:755-778
We propose an extension of the N-mixture model which allows for the estimation of both abundances of multiple species simultaneously and their inter-species correlations. We also propose further extensions to this multi-species N-mixture model, one o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1fa9c8949174a2706f65008ba7a3a568
https://doi.org/10.1007/s10651-022-00542-7
https://doi.org/10.1007/s10651-022-00542-7
Autor:
Batista Do Prado, Estevao, Sarti, Danilo, Inglis, Alan, Lemos dos Santos, Alessandra, Hurley, Catherine, de Andrade Moral, Rafael, Parnell, Andrew C
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______201::835423da379a32cd211ac9d1b9e61371
https://eprints.lancs.ac.uk/id/eprint/185619/
https://eprints.lancs.ac.uk/id/eprint/185619/
Akademický článek
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