Zobrazeno 1 - 10
of 381
pro vyhledávání: '"Parnell, A. C."'
Autor:
Govan, Emma, Jackson, Andrew L, Bearhop, Stuart, Inger, Richard, Stock, Brian C, Semmens, Brice X, Ward, Eric J, Parnell, Andrew C
The study of animal diets and the proportional contribution that different foods make to their diets is an important task in ecology. Stable Isotope Mixing Models (SIMMs) are an important tool for studying an animal's diet and understanding how the a
Externí odkaz:
http://arxiv.org/abs/2408.17230
Seemingly unrelated Bayesian additive regression trees for cost-effectiveness analyses in healthcare
Autor:
Esser, Jonas, Maia, Mateus, Parnell, Andrew C., Bosmans, Judith, van Dongen, Hanneke, Klausch, Thomas, Murphy, Keefe
In recent years, theoretical results and simulation evidence have shown Bayesian additive regression trees to be a highly-effective method for nonparametric regression. Motivated by cost-effectiveness analyses in health economics, where interest lies
Externí odkaz:
http://arxiv.org/abs/2404.02228
We introduce an R package for fitting Stable Isotope Mixing Models (SIMMs) via both Markov chain Monte Carlo and Variational Bayes. The package is mainly used for estimating dietary contributions from food sources taken via measurements of stable iso
Externí odkaz:
http://arxiv.org/abs/2306.07817
We propose a Bayesian tensor regression model to accommodate the effect of multiple factors on phenotype prediction. We adopt a set of prior distributions that resolve identifiability issues that may arise between the parameters in the model. Simulat
Externí odkaz:
http://arxiv.org/abs/2301.03655
In plant breeding the presence of a genotype by environment (GxE) interaction has a strong impact on cultivation decision making and the introduction of new crop cultivars. The combination of linear and bilinear terms has been shown to be very useful
Externí odkaz:
http://arxiv.org/abs/2207.00011
The Bayesian additive regression trees (BART) model is an ensemble method extensively and successfully used in regression tasks due to its consistently strong predictive performance and its ability to quantify uncertainty. BART combines "weak" tree m
Externí odkaz:
http://arxiv.org/abs/2204.02112
Autor:
Daly, Patrick, Nejad, Amin Shoari, Domijan, Katarina, McCaughey, Jamie W., Brassard, Caroline, Kathiravelu, Laavanya, Marques, Mateus, Sarti, Danilo, Parnell, Andrew C., Horton, Benjamin
Publikováno v:
In Progress in Disaster Science December 2024 24
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:
In Computational Statistics and Data Analysis February 2024 190
Autor:
Inglis, Alan1 (AUTHOR) alan.inglis@mu.ie, Parnell, Andrew C.1 (AUTHOR), Subramani, Natarajan2 (AUTHOR) natarajan.subramani@ucd.ie, Doohan, Fiona M.2 (AUTHOR) fiona.doohan@ucd.ie
Publikováno v:
Toxins. Jun2024, Vol. 16 Issue 6, p268. 30p.