Results 31 to 40 of about 1,249,090 (302)
Lévy Walk in Swarm Models Based on Bayesian and Inverse Bayesian Inference
Computational and Structural Biotechnology Journal, 2021 While swarming behavior is regarded as a critical phenomenon in phase transition and frequently shows the properties of a critical state such as Lévy walk, a general mechanism to explain the critical property in swarming behavior has not yet been found ...
Yukio-Pegio Gunji +5 more
doaj +1 more source
Bayesian inference for dynamical systems
Infectious Disease Modelling, 2020 Bayesian inference is a common method for conducting parameter estimation for dynamical systems. Despite the prevalent use of Bayesian inference for performing parameter estimation for dynamical systems, there is a need for a formalized and detailed ...
Weston C. Roda
doaj +1 more source
Bayesian inference for psychology. Part II: Example applications with JASP
Psychonomic Bulletin & Review, 2017 Bayesian hypothesis testing presents an attractive alternative to p value hypothesis testing. Part I of this series outlined several advantages of Bayesian hypothesis testing, including the ability to quantify evidence and the ability to monitor and ...
E. Wagenmakers +25 more
semanticscholar +1 more source
Stats, 2022 In this study, the estimation methods of bias-corrected maximum likelihood (BCML), bootstrap BCML (B-BCML) and Bayesian using Jeffrey’s prior distribution were proposed for the inverse Gaussian distribution with small sample cases to obtain the ML and ...
Tzong-Ru Tsai +3 more
doaj +1 more source
Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects (with Discussion) [PDF]
, 2020 Congratulations to Hahn, Murray and Carvalho on a nice contribution. The authors propose the Bayesian causal forest (BCF) model. It reduces the bias and improves frequentist coverage of Bayesian credible intervals of treatment effect estimates in the ...
Liangyuan Hu
semanticscholar +1 more source
Efficient Bayesian hierarchical functional data analysis with basis function approximations using Gaussian-Wishart processes [PDF]
, 2016 Functional data are defined as realizations of random functions (mostly smooth functions) varying over a continuum, which are usually collected with measurement errors on discretized grids.
Bonferroni C. E. +8 more
core +1 more source
Enhanced off-grid DOA estimation by corrected power Bayesian inference using difference coarray
The Journal of Engineering, 2019 Sparse Bayesian inference for on-grid direction-of-arrival (DOA) estimation using difference coarray was investigated in the authors’ previous work to estimate more signal sources than the number of physical antenna elements. Sparse Bayesian inference is
Yanan Ma, Xianbin Cao, Xiangrong Wang
doaj +1 more source
Bayesian parameter inference and model selection by population annealing in systems biology. [PDF]
PLoS ONE, 2014 Parameter inference and model selection are very important for mathematical modeling in systems biology. Bayesian statistics can be used to conduct both parameter inference and model selection.
Yohei Murakami
doaj +1 more source
Journal of Statistical Software, 2022 Consider a Bayesian inference problem where a variable of interest does not take values in a Euclidean space. These "non-standard" data structures are in reality fairly common. They are frequently used in problems involving latent discrete factor models,
Alexandre Bouchard-Côté +7 more
doaj +1 more source
Variational Inference for Nonlinear Structural Identification [PDF]
Journal of Applied and Computational Mechanics, 2021 Research interest in predictive modeling within the structural engineering community has recently been focused on Bayesian inference methods, with particular emphasis on analytical and sampling approaches. In this study, we explore variational inference,
Alana Lund +2 more
doaj +1 more source