Results 41 to 50 of about 4,352 (182)

Jeffreys’ prior is the Hausdorff measure for the Hellinger and Kullback-Leibler distances [PDF]

Studia Scientiarum Mathematicarum Hungarica, 2000
Let \((\Omega, {\mathcal A}, F = \{ P_\vartheta\} _{\vartheta \in \Theta})\) be a dominated statistical experiment with \( \Theta \subset \mathbb R ^ k\) such that \( P_\vartheta \not= P_{\vartheta'} \) for \( \vartheta \neq \vartheta'\). Let \(\{ f_\vartheta \} _{\vartheta \in \Theta} \) be the corresponding family of \(\mu\)-densities.
openaire   +3 more sources

Correcting automatically generated closed captions for online learning materials does not improve student learning outcomes (although students believe it does)

British Journal of Educational Technology, EarlyView.
Abstract Lecture capture is ubiquitous in higher education. Lecture capture recordings are typically accompanied by automatically generated closed captions that are sometimes corrected by humans. Students self‐report that they benefit from captions, and particularly human‐corrected captions.
Peter J. Allen, Polly Barr, Kristopher G. Magee, Imogen van Jaarsveldt, Andy Wakefield   +4 more
wiley   +1 more source

Bertrand’s Paradox Resolution and Its Implications for the Bing–Fisher Problem

Mathematics, 2023
Bertrand’s paradox is a problem in geometric probability that has resisted resolution for more than one hundred years. Bertrand provided three seemingly reasonable solutions to his problem — hence the paradox. Bertrand’s paradox has also been influential
Richard A. Chechile
doaj   +1 more source

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, Jan‐Willem Simons, Haiyan Liu   +2 more
wiley   +1 more source

Bayes, Jeffreys, Prior Distributions and the Philosophy of Statistics

Statistical Science, 2009
I actually own a copy of Harold Jeffreys's Theory of Probability but have only read small bits of it, most recently over a decade ago to confirm that, indeed, Jeffreys was not too proud to use a classical chi-squared p-value when he wanted to check the misfit of a model to data (Gelman, Meng and Stern, 2006). I do, however, feel that it is important to
openaire   +5 more sources

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
wiley   +1 more source

The Prior Can Often Only Be Understood in the Context of the Likelihood

Entropy, 2017
A key sticking point of Bayesian analysis is the choice of prior distribution, and there is a vast literature on potential defaults including uniform priors, Jeffreys’ priors, reference priors, maximum entropy priors, and weakly informative priors. These
Andrew Gelman, Daniel Simpson, Michael Betancourt   +2 more
doaj   +1 more source

LLM‐based prior elicitation for Bayesian graphical modeling

British Journal of Mathematical and Statistical Psychology, EarlyView.
ABSTRACT In the Bayesian graphical modeling framework, priors on network structure encode theoretical assumptions and uncertainty about the topology of psychological constructs under study. For instance, the Bernoulli prior specifies the probability of each pairwise interaction, the Beta–Bernoulli prior governs expected network density, and the ...
Nikola Sekulovski, Meike Waaijers, Giuseppe Arena   +2 more
wiley   +1 more source

On estimation for accelerated failure time models with small or rare event survival data

BMC Medical Research Methodology, 2022
Background Separation or monotone likelihood may exist in fitting process of the accelerated failure time (AFT) model using maximum likelihood approach when sample size is small and/or rate of censoring is high (rare event) or there is at least one ...
Tasneem Fatima Alam, M. Shafiqur Rahman, Wasimul Bari   +2 more
doaj   +1 more source

To vary or not to vary: A flexible empirical Bayes factor for testing variance components

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Random effects are the gold standard for capturing structural heterogeneity, such as individual differences or temporal dependence. Yet testing their presence is difficult because variance components are constrained to be non‐negative, creating a boundary problem. This paper introduces a flexible empirical Bayes factor (EBF) for testing random
Fabio Vieira, Hongwei Zhao, Joris Mulder
wiley   +1 more source