A tutorial on Bayesian model averaging for exponential random graph models
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract The use of exponential random graph models (ERGMs) is becoming prevalent in psychology due to their ability to explain and predict the formation of edges between vertices in a network. Valid inference with ERGMs requires correctly specifying endogenous and exogenous effects as network statistics, guided by theory, to represent the network ...
Ihnwhi Heo +2 more
wiley +1 more source
Bayesian Estimation of Multicomponent Stress-Strength Model Using Progressively Censored Data from the Inverse Rayleigh Distribution. [PDF]
Entropy (Basel)Yılmaz A.
europepmc +1 more source
A Bayes factor framework for unified parameter estimation and hypothesis testing
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract The Bayes factor, the data‐based updating factor of the prior to posterior odds of two hypotheses, is a natural measure of statistical evidence for one hypothesis over the other. We show how Bayes factors can also be used for parameter estimation.
Samuel Pawel
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Approximating the ideal observer for joint signal detection and estimation tasks by the use of Markov-Chain Monte Carlo with generative adversarial networks. [PDF]
J Med Imaging (Bellingham)Li D, Li K, Zhou W, Anastasio MA.
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This paper is intended to appear as a chapter for the Handbook of Markov Chain Monte Carlo. The goal of this chapter is to unify various problems at the intersection of Markov chain Monte Carlo (MCMC) and machine learning$\unicode{x2014}$which includes black-box variational inference, adaptive MCMC, normalizing flow construction and transport-assisted ...
Bouchard-Côté, Alexandre +3 more
openaire +1 more source
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract In the present study, we extend a stochastic differential equation (SDE) model, the Ornstein–Uhlenbeck (OU) process, to the simultaneous analysis of time series of multiple variables by means of random effects for individuals and variables using a Bayesian framework.
José Ángel Martínez‐Huertas +1 more
wiley +1 more source
The evolution of public health statistical modeling approaches and how to advance their incorporation into modern arboviral surveillance. [PDF]
J Med EntomolMcCarter M +5 more
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Identifiability conditions in cognitive diagnosis: Implications for Q‐matrix estimation algorithms
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract The Q‐matrix of a cognitively diagnostic assessment (CDA), documenting the item‐attribute associations, is a key component of any CDA. However, the true Q‐matrix underlying a CDA is never known and must be estimated—typically by content experts.
Hyunjoo Kim +2 more
wiley +1 more source
Mathematical Modeling of Amoxicillin Synthesis in Batch and Semi-Batch Reactor: Application of Bayesian Statistics and Genetic Algorithm. [PDF]
Biotechnol BioengFormigosa LF +5 more
europepmc +1 more source
Idiographic interrater reliability measures for intensive longitudinal multirater data
British Journal of Mathematical and Statistical Psychology, EarlyView.Abstract Interrater reliability plays a crucial role in various areas of psychology. In this article, we propose a multilevel latent time series model for intensive longitudinal data with structurally different raters (e.g., self‐reports and partner reports).
Tobias Koch +4 more
wiley +1 more source