Zobrazeno 1 - 10
of 42
pro vyhledávání: '"Andrew Golightly"'
Autor:
Laura E. Wadkin, Andrew Golightly, Julia Branson, Andrew Hoppit, Nick G. Parker, Andrew W. Baggaley
Publikováno v:
Diversity, Vol 15, Iss 4, p 496 (2023)
Invasive woodland pests have substantial ecological, economic, and social impacts, harming biodiversity and ecosystem services. Mathematical modelling informed by Bayesian inference can deepen our understanding of the fundamental behaviours of invasi
Externí odkaz:
https://doaj.org/article/5511c6acabe64cd1ae1044f1c32bc086
Autor:
Laura E. Wadkin, Julia Branson, Andrew Hoppit, Nicholas G. Parker, Andrew Golightly, Andrew W. Baggaley
Publikováno v:
Ecology and Evolution, Vol 12, Iss 5, Pp n/a-n/a (2022)
Abstract Invasive pests pose a great threat to forest, woodland, and urban tree ecosystems. The oak processionary moth (OPM) is a destructive pest of oak trees, first reported in the UK in 2006. Despite great efforts to contain the outbreak within th
Externí odkaz:
https://doaj.org/article/f378c59329084110853ec967df16e977
Publikováno v:
Computational Statistics and Data Analysis, 2023, Vol.185, pp.107760 [Peer Reviewed Journal]
Stochastic kinetic models (SKMs) are increasingly used to account for the inherent stochasticity exhibited by interacting populations of species in areas such as epidemiology, population ecology and systems biology. Species numbers are modelled using
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c88986333ec95db99b4948c702ee9e43
http://dro.dur.ac.uk/38253/
http://dro.dur.ac.uk/38253/
Autor:
Andrew Golightly, Chris Sherlock
Publikováno v:
Journal of computational and graphical statistics, 2023, Vol.32(1), pp.36-48 [Peer Reviewed Journal]
We present new methodologies for Bayesian inference on the rate parameters of a discretely observed continuous-time Markov jump processes with a countably infinite state space. The usual method of choice for inference, particle Markov chain Monte Car
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d989df0e6113b5209db3a2fd20b340b6
https://doi.org/10.1080/10618600.2022.2093886
https://doi.org/10.1080/10618600.2022.2093886
Publikováno v:
Biometrics, 2022, Vol.78(3), pp.1195-1208 [Peer Reviewed Journal]
The presence of protein aggregates in cells is a known feature of many human age-related diseases, such as Huntington's disease. Simulations using fixed parameter values in a model of the dynamic evolution of expanded polyglutamine (PolyQ) proteins i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b4e578352f7f01be6ae044181961e16f
https://doi.org/10.1111/biom.13467
https://doi.org/10.1111/biom.13467
Autor:
Naomi E. Hannaford, Sarah E. Heaps, Tom M.W. Nye, Thomas P. Curtis, Ben Allen, Andrew Golightly, Darren J. Wilkinson
Publikováno v:
Computational Statistics and Data Analysis, 2023, Vol.179, pp.107659 [Peer Reviewed Journal]
Proper function of a wastewater treatment plant (WWTP) relies on maintaining a delicate balance between a multitude of competing microorganisms. Gaining a detailed understanding of the complex network of interactions therein is essential to maximisin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e5ce532839c36cd56917d2440b8f8bb
http://arxiv.org/abs/2107.00502
http://arxiv.org/abs/2107.00502
Publikováno v:
Computational Statistics & Data Analysis. 136:92-107
The challenging problem of conducting fully Bayesian inference for the reaction rate constants governing stochastic kinetic models (SKMs) is considered. Given the challenges underlying this problem, the Markov jump process representation is routinely
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b057a50529e12cca41f72809018439f
https://doi.org/10.1016/j.csda.2019.01.006
https://doi.org/10.1016/j.csda.2019.01.006
Publikováno v:
Bayesian Analysis, 2022, Vol.17(1), pp.223-260 [Peer Reviewed Journal]
Particle Markov chain Monte Carlo (pMCMC) is now a popular method for performing Bayesian statistical inference on challenging state space models (SSMs) with unknown static parameters. It uses a particle filter (PF) at each iteration of an MCMC algor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b2f424b0b4aef2d79670af1a38cdffb1
http://wrap.warwick.ac.uk/144625/7/WRAP-ensemble-MCMC-accelerating-pseudo-MCMC-state-space-Kalman-Everitt-2020.pdf
http://wrap.warwick.ac.uk/144625/7/WRAP-ensemble-MCMC-accelerating-pseudo-MCMC-state-space-Kalman-Everitt-2020.pdf
Autor:
Andrew Golightly, Theodore Kypraios
Publikováno v:
Statistics and Computing. 28:1215-1230
Fitting stochastic kinetic models represented by Markov jump processes within the Bayesian paradigm is complicated by the intractability of the observed-data likelihood. There has therefore been considerable attention given to the design of pseudo-ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ecae10a6d54c440d7dc8e42e7cab4df
https://doi.org/10.1007/s11222-017-9789-8
https://doi.org/10.1007/s11222-017-9789-8
Publikováno v:
Journal of Computational and Graphical Statistics. 26:434-444
When conducting Bayesian inference, delayed acceptance (DA) Metropolis-Hastings (MH) algorithms and DA pseudo-marginal MH algorithms can be applied when it is computationally expensive to calculate the true posterior or an unbiased estimate thereof,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1a894999c2504f305b4e4ce1e4c51760
https://doi.org/10.1080/10618600.2016.1231064
https://doi.org/10.1080/10618600.2016.1231064