984 research outputs found
Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems
Approximate Bayesian computation methods can be used to evaluate posterior
distributions without having to calculate likelihoods. In this paper we discuss
and apply an approximate Bayesian computation (ABC) method based on sequential
Monte Carlo (SMC) to estimate parameters of dynamical models. We show that ABC
SMC gives information about the inferability of parameters and model
sensitivity to changes in parameters, and tends to perform better than other
ABC approaches. The algorithm is applied to several well known biological
systems, for which parameters and their credible intervals are inferred.
Moreover, we develop ABC SMC as a tool for model selection; given a range of
different mathematical descriptions, ABC SMC is able to choose the best model
using the standard Bayesian model selection apparatus.Comment: 26 pages, 9 figure
Bayesian Analysis for Food-Safety Risk Assessment: Evaluation of Dose-Response Functions within WinBUGS
Bayesian methods are becoming increasingly popular in the field of food-safety risk assessment. Risk assessment models often require the integration of a dose-response function over the distribution of all possible doses of a pathogen ingested with a specific food. This requires the evaluation of an integral for every sample for a Markov chain Monte Carlo analysis of a model. While many statistical software packages have functions that allow for the evaluation of the integral, this functionality is lacking in WinBUGS. A probabilistic model, that incorporates a novel numerical integration technique, is presented to facilitate the use of WinBUGS for food-safety risk assessments. The numerical integration technique is described in the context of a typical food-saftey risk assesment, some theoretical results are given, and a snippet of WinBUGS code is provided
Honor Farm
My artwork work focuses upon byproducts; byproducts of humans and byproducts as subject. My imagery picks up on the byproducts of society's organization of human life, such as prison architecture and security devices. Honor Farm is a metaphor for the human environment, space, and location that creates containment. Through the exploration of containment facilities, prisons, and barriers Honor Farm emerges as the subject matter. Desire for the barrier obstructs the balance among mind, body, and spirit. My art embraces the living environment as a link between the physical and the cerebral. The communication between material and image drives my process. Material informs the paint and the paint informs the imagery. In the last two years as an artist, my language evolved in relation to materials, images, and concepts
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