Results 31 to 40 of about 164,931 (293)

Introduction to Bayesian Statistics [PDF]

, 2020
In this brief introductory chapter, we sought to inform readers new to Bayesian statistics about the fundamental concepts in Bayesian analyses. The most important take-home messages to remember are that in Bayesian statistics, the analysis starts with an
Miočević, M., Levy, R., van de Schoot, R.   +2 more
core   +3 more sources

A Bayesian Statistics Course for Undergraduates: Bayesian Thinking, Computing, and Research

Journal of Statistics Education, 2020
We propose a semester-long Bayesian statistics course for undergraduate students with calculus and probability background. We cultivate students’ Bayesian thinking with Bayesian methods applied to real data problems. We leverage modern Bayesian computing
Jingchen Hu
doaj   +1 more source

Using stacking to average bayesian predictive distributions (with discussion) [PDF]

, 2018
Bayesian model averaging is flawed in the M-open setting in which the true data-generating process is not one of the candidate models being fit. We take the idea of stacking from the point estimation literature and generalize to the combination of ...
Grunwald, Peter, Castro-Camilo, Daniela, Li, Meng, Shin, Minsuk, Grushka-Cockayne, Yael, Gelman, Andrew, Lichtendahl, Kenneth C., Iacopini, Matteo, Dawid, A. Philip, van Dijk, Herman K., Lichtendahl, Kenneth C, Yao, Yuling, Zhou, Tianjian, Winkler, Robert L, Aastveit, Knut Are, Dawid, A Philip, Yoo, William Weimin, Pericchi, Luis, Clarke, Bertrand, Bakka, Haakon C, Freni-Sterrantino, Anna, Franck, Christopher T., Hoogerheide, Lennart, Tonellato, Stefano, Winkler, Robert L., Simpson, Daniel, Ferreira, Marco A. R., Franco-Villoria, Maria, Belitser, Eduard, Bakka, Haakon C., van Dijk, Herman K, Ferreira, Marco AR, de Heide, Rianne, Nurushev, Nurzhan, Jose, Victor Richmond R., Vehtari, Aki, Clyde, Merlise, McAlinn, Kenichiro, West, Mike, Rue, Havard, Huser, Raphael, Opitz, Thomas, Jose, Victor Richmond R, Franck, Christopher T   +43 more
core   +1 more source

Reporting Standards for Bayesian Network Modelling

Entropy
Reproducibility is a key measure of the veracity of a modelling result or finding. In other research areas, notably in medicine, reproducibility is supported by mandating the inclusion of an agreed set of details into every research publication ...
Martine J. Barons, Anca M. Hanea, Steven Mascaro, Owen Woodberry   +3 more
doaj   +1 more source

A Web Simulator to Assist in the Teaching of Bayes’ Theorem

Journal of Statistics Education, 2019
Teaching some concepts in statistics greatly benefits from individual practice with immediate feedback. In order to provide such practice to a large number of students we have written a simulator based on an historical event: the loss in May 22, 1968 ...
M. J. Bárcena, M. A. Garín, A. Martín, F. Tusell, A. Unzueta   +4 more
doaj   +1 more source

Improving Transparency and Replication in Bayesian Statistics: The WAMBS-Checklist [PDF]

, 2017
Bayesian statistical methods are slowly creeping into all fields of science and are becoming ever more popular in applied research. Although it is very attractive to use Bayesian statistics, our personal experience has led us to believe that naively ...
Methodology and statistics for the behavioural and social sciences, van de Schoot, Rens, Depaoli, Sarah, Leerstoel Hoijtink   +3 more
core   +1 more source

Bayesian Computing in the Undergraduate Statistics Curriculum

Journal of Statistics Education, 2020
Bayesian statistics has gained great momentum since the computational developments of the 1990s. Gradually, advances in Bayesian methodology and software have made Bayesian techniques much more accessible to applied statisticians and, in turn, have ...
Jim Albert, Jingchen Hu
doaj   +1 more source

Statistical Recovery of 21 cm Visibilities and Their Power Spectra with Gaussian-constrained Realizations and Gibbs Sampling

The Astrophysical Journal Supplement Series, 2023
Radio interferometers designed to probe the 21 cm signal from Cosmic Dawn and the Epoch of Reionization must contend with systematic effects that make it difficult to achieve sufficient dynamic range to separate the 21 cm signal from foreground emission ...
Fraser Kennedy, Philip Bull, Michael J. Wilensky, Jacob Burba, Samir Choudhuri   +4 more
doaj   +1 more source

Using Bayesian Statistics in Enterprise Demography

Zeszyty Naukowe Uniwersytetu Ekonomicznego w Krakowie, 2016
Tytuł artykułu: Zastosowanie metod statystyki bayesowskiej w demografii przedsiębiorstw Znajomość liczby przedsiębiorstw różnego typu, których utworzenie jest planowane w najbliższym roku, stanowi istotną informację, która może zostać wykorzystana w ...
Eva Kotlebová, Ivan Láska
doaj   +1 more source

Bayesian statistics and Monte Carlo methods

Journal of Geodetic Science, 2018
The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is defined as a measure of the plausibility of statements or propositions. Three rules are sufficient to obtain the laws of probability.
Koch K. R.
doaj   +1 more source