Results 31 to 40 of about 137,667 (314)
Model Selection in Historical Research Using Approximate Bayesian Computation. [PDF]
PLoS ONE, 2016 FORMAL MODELS AND HISTORY:Computational models are increasingly being used to study historical dynamics. This new trend, which could be named Model-Based History, makes use of recently published datasets and innovative quantitative methods to improve our
Xavier Rubio-Campillo
doaj +1 more source
Approximate Bayesian Computation of Bézier Simplices
CoRR, 2021 Bézier simplex fitting algorithms have been recently proposed to approximate the Pareto set/front of multi-objective continuous optimization problems. These new methods have shown to be successful at approximating various shapes of Pareto sets/fronts when sample points exactly lie on the Pareto set/front. However, if the sample points scatter away from
Akinori Tanaka +3 more
openaire +2 more sources
Epidemics, 2023 Assessing the factors responsible for differences in outbreak severity for the same pathogen is a challenging task, since outbreak data are often incomplete and may vary in type across outbreaks (e.g., daily case counts, serology, cases per household ...
Alexander D. Meyer +5 more
doaj +1 more source
Frontiers in Microbiology, 2018 To estimate and predict the transmission dynamics of respiratory viruses, the estimation of the basic reproduction number, R0, is essential. Recently, approximate Bayesian computation methods have been used as likelihood free methods to estimate ...
Heidi L. Tessmer +3 more
doaj +1 more source
Approximation Bayesian computation [PDF]
OA Genetics, 2013 Approximation Bayesian computation [ABC] is an analysis approach that has arisen in response to the recent trend to collect data that is of a magnitude far higher than has been historically the case. This has led to many existing methods become intractable because of difficulties in calculating the likelihood function.
openaire +2 more sources
Approximate Bayesian Computation with Path Signatures
, 2021 42 pages, 8 ...
Dyer, J, Cannon, P, Schmon, SM
openaire +4 more sources
Approximate Bayesian computation methods [PDF]
Statistics and Computing, 2012 Occasionally, Statistics and Computing is publishing Special Issues on topics of potential interests. The most recent published Special Issues were concerned with “Adaptive Methods in Bayesian Computation”, Guest Editor Paul Fearnhead, Volume 18 Issue 4 (2008), “Regularisation Methods in Classification and Regression”, Guest Editor Gerhard Tutz, Volume
openaire +2 more sources
Computation of Kullback–Leibler Divergence in Bayesian Networks
Entropy, 2021 Kullback–Leibler divergence KL(p,q) is the standard measure of error when we have a true probability distribution p which is approximate with probability distribution q.
Serafín Moral +2 more
doaj +1 more source
Exact Inference with Approximate Computation for Differentially Private Data via Perturbations
The Journal of Privacy and Confidentiality, 2022 This paper discusses how two classes of approximate computation algorithms can be adapted, in a modular fashion, to achieve exact statistical inference from differentially private data products.
Ruobin Gong
doaj
Approximate Bayesian computation with functional statistics [PDF]
Statistical Applications in Genetics and Molecular Biology, 2013 Functional statistics are commonly used to characterize spatial patterns in general and spatial genetic structures in population genetics in particular. Such functional statistics also enable the estimation of parameters of spatially explicit (and genetic) models.
Soubeyrand, Samuel +3 more
openaire +5 more sources