Automated Biosurveillance Data from England and Wales, 1991–2011

Autor: Doyo G. Enki, Angela Noufaily, Paul H. Garthwaite, Nick J. Andrews, André Charlett, Chris Lane, C. Paddy Farrington

Publikováno v: Emerging Infectious Diseases, Vol 19, Iss 1, Pp 35-42 (2013)

Outbreak detection systems for use with very large multiple surveillance databases must be suited both to the data available and to the requirements of full automation. To inform the development of more effective outbreak detection algorithms, we ana

Externí odkaz: https://doaj.org/article/370e91e4a1964075acad8ebac00b0474

Bayesian analysis of misclassified binomial data: double-sampling and the zero-numerator problem

Autor: Paul H. Garthwaite, Noriah M. Al-Kandari

Publikováno v: Communications in Statistics - Simulation and Computation. 52:334-348

This article examines the zero numerator problem. This problem occurs when the misclassification rates are so low that both forms of misclassification may not both be present in the validation data. For this problem, the article compares two Bayesian

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b03e5ea7cde59224a4d9701a34122a06
https://doi.org/10.1080/03610918.2020.1855448

On Quantifying Expert Opinion about Multinomial Models that Contain Covariates

Autor: Fadlalla G. Elfadaly, Paul H. Garthwaite

Publikováno v: Journal of the Royal Statistical Society Series A: Statistics in Society. 183:959-981

Summary The paper addresses the task of forming a prior distribution to represent expert opinion about a multinomial model that contains covariates. The task has not previously been addressed. We suppose that the sampling model is a multinomial logis

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f0dd65c7564fb5cd312e5fcc8cad687
https://doi.org/10.1111/rssa.12546

Recent Advances in the Elicitation of Uncertainty Distributions from Experts for Multinomial Probabilities

Autor: Fadlalla G. Elfadaly, Jeremy E. Oakley, Kevin J. Wilson, Paul H. Garthwaite

Publikováno v: International Series in Operations Research & Management Science ISBN: 9783030464738

In this chapter, we consider the problem of the elicitation and specification of an uncertainty distribution based on expert judgements, which may be a subjective prior distribution in a Bayesian analysis, for a set of probabilities which are constra

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::53dfda16281737de3f3cd20290cf5fe9
https://doi.org/10.1007/978-3-030-46474-5_2

Producing Policy-relevant Science by Enhancing Robustness and Model Integration for the Assessment of Global Environmental Change

Autor: P. Slavin, Kevin M. Hiscock, Rachel Warren, Oluwole Oyebamiji, Jan Philipp Dietrich, Graham Riley, Philip B. Holden, Matthew Hyde, Jeff Price, Marian Leimbach, Dieter Gerten, Philomena M. Bacon, Craig Wallace, Alain Haurie, Rupert W. Ford, Sudipta Goswami, Frédéric Louis François Babonneau, Sibyll Schaphoff, Santosh Ram Joshi, Barbara Pizzileo, Neil R. Edwards, Amit Kanudia, Maryse Labriet, Alexander Popp, Paul H. Garthwaite, Marc Vielle, Timothy J. Osborn

Publikováno v: Warren, R F, Edwards, N R, Babonneau, F, Bacon, P M, Dietrich, J P, Ford, R W, Garthwaite, P, Gerten, D, Goswami, S, Haurie, A, Hiscock, K, Holden, P B, Hyde, M R, Joshi, S R, Kanudia, A, Labriet, M, Leimbach, M, Oyebamiji, O K, Osborn, T, Pizzileo, B, Popp, A, Price, J, Riley, G D, Schaphoff, S, Slavin, P, Vielle, M & Wallace, C 2019, ' Producing Policy-relevant Science by Enhancing Robustness and Model Integration for the Assessment of Global Environmental Change ', Environmental Modelling and Software, vol. 111, pp. 248-258 . https://doi.org/10.1016/j.envsoft.2018.05.010

We use the flexible model coupling technology known as the bespoke framework generator to link established existing modules representing dynamics in the global economy (GEMINI-E3), the energy system (TIAM-WORLD), the global and regional climate syste

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb21c93ac570f07c45bc802c62d32ea6
https://doi.org/10.1016/j.envsoft.2018.05.010