Results 51 to 60 of about 135,519 (174)

Modeling of Flowering Time in Vigna radiata with Approximate Bayesian Computation

Agronomy, 2021
Flowering time is an important target for breeders in developing new varieties adapted to changing conditions. A new approach is proposed that uses Approximate Bayesian Computation with Differential Evolution to construct a pool of models for flowering ...
Andrey Ageev, Cheng-Ruei Lee, Chau-Ti Ting, Roland Schafleitner, Eric Bishop-von Wettberg, Sergey V. Nuzhdin, Maria Samsonova, Konstantin Kozlov   +7 more
doaj   +1 more source

Cellular connectomes as arbiters of local circuit models in the cerebral cortex

Nature Communications, 2021
Large-scale connectomes from the mammalian brain are becoming available, but it remains unclear how informative these are for the distinction of circuit models.
Emmanuel Klinger, Alessandro Motta, Carsten Marr, Fabian J. Theis, Moritz Helmstaedter   +4 more
doaj   +1 more source

Cophylogeny Reconstruction via an Approximate Bayesian Computation [PDF]

Systematic Biology, 2014
Despite an increasingly vast literature on cophylogenetic reconstructions for studying host-parasite associations, understanding the common evolutionary history of such systems remains a problem that is far from being solved. Most algorithms for host-parasite reconciliation use an event-based model, where the events include in general (a subset of ...
Baudet, C., DONATI, BEATRICE, Sinaimeri, B., CRESCENZI, PIERLUIGI, Gautier, C., Matias, C., Sagot, M. F.   +6 more
openaire   +4 more sources

Approximate Bayesian Computation for infectious disease modelling [PDF]

Epidemics, 2019
Approximate Bayesian Computation (ABC) techniques are a suite of model fitting methods which can be implemented without a using likelihood function. In order to use ABC in a time-efficient manner users must make several design decisions including how to code the ABC algorithm and the type of ABC algorithm to use.
Minter, Amanda, Retkute, Renata
openaire   +3 more sources

Approximate Bayesian Computation of radiocarbon and paleoenvironmental record shows population resilience on Rapa Nui (Easter Island)

Nature Communications, 2021
Summed probability distributions of radiocarbon dates can be used to estimate past demography, but methods to test for associations with environmental change are lacking. Here, DiNapoli et al.
Robert J. DiNapoli, Enrico R. Crema, Carl P. Lipo, Timothy M. Rieth, Terry L. Hunt   +4 more
doaj   +1 more source

Quick and energy-efficient Bayesian computing of binocular disparity using stochastic digital signals [PDF]

, 2016
Reconstruction of the tridimensional geometry of a visual scene using the binocular disparity information is an important issue in computer vision and mobile robotics, which can be formulated as a Bayesian inference problem.
Bessière, Pierre, Coninx, Alexandre, Droulez, Jacques   +2 more
core   +3 more sources

Regression approaches for Approximate Bayesian Computation [PDF]

, 2017
This book chapter introduces regression approaches and regression adjustment for Approximate Bayesian Computation (ABC). Regression adjustment adjusts parameter values after rejection sampling in order to account for the imperfect match between ...
Blum, Michael GB
core   +1 more source

Non-linear regression models for Approximate Bayesian Computation

, 2009
Approximate Bayesian inference on the basis of summary statistics is well-suited to complex problems for which the likelihood is either mathematically or computationally intractable.
A. Butler, A. Gelman, B. Schölkopf, B.D. Ripley, C. Gourieroux, C.M. Bishop, C.P. Robert, D.A. Nix, D.E. Reich, E.A. Nadaraya, G. Weiss, G.E.P. Box, G.S. Watson, I.J. Wilson, J. Fan, J. Hey, J.H. Friedman, J.K. Pritchard, J.K. Pritchard, J.P. King, J.S. Liu, K. Heggland, L.A. Zhivotovsky, L.A. Zhivotovsky, M. Stephens, M. Tanaka, M.A. Beaumont, M.D. Shriver, M.K. Kuhner, N.J.R. Fagundes, O. Ratmann, P. Bortot, P. Marjoram, P. Marjoram, P.J. Diggle, S. Tavaré, S. Tavaré, S.A. Sisson, T. Ohta, T. Toni, V.N. Vapnik, W. Härdle, Y.-X. Fu, Y.-X. Fu   +43 more
core   +1 more source

A Comparative Review of Dimension Reduction Methods in Approximate Bayesian Computation [PDF]

, 2013
Approximate Bayesian computation (ABC) methods make use of comparisons between simulated and observed summary statistics to overcome the problem of computationally intractable likelihood functions.
Blum, M. G. B., Nunes, M. A., Prangle, D., Sisson, S. A.   +3 more
core   +4 more sources

Approximate Bayesian Computation: A Nonparametric Perspective [PDF]

Journal of the American Statistical Association, 2010
Approximate Bayesian Computation is a family of likelihood-free inference techniques that are well-suited to models defined in terms of a stochastic generating mechanism. In a nutshell, Approximate Bayesian Computation proceeds by computing summary statistics s_obs from the data and simulating summary statistics for different values of the parameter ...
openaire   +4 more sources