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Academic journal
Bayesian Analysis is an open-access peer-reviewed scientific journal covering theoretical and applied aspects of Bayesian methods. It is published by
Bayesian_Analysis_(journal)
Type of sensitivity analysis
robust Bayesian analysis, also called Bayesian sensitivity analysis, is a type of sensitivity analysis applied to the outcome from Bayesian inference
Robust_Bayesian_analysis
Theory and paradigm of statistics
trials. More concretely, analysis in Bayesian methods codifies prior knowledge in the form of a prior distribution. Bayesian statistical methods use Bayes'
Bayesian_statistics
redirect targets Approximate Bayesian computation – Computational method in Bayesian statistics Bayesian Analysis (journal) Bayesian approaches to brain function –
List of things named after Thomas Bayes
List_of_things_named_after_Thomas_Bayes
Statistical method
Debajyoti; Dey, Dipak K. (September 1997). "Semiparametric Bayesian Analysis of Survival Data". Journal of the American Statistical Association. 92 (439): 1195–1212
Bayesian_survival_analysis
Method of statistical inference
mathematical statistics. Bayesian updating is particularly important in the dynamic analysis of a sequence of data. Bayesian inference has found application
Bayesian_inference
Method of statistical analysis
Bayesian linear regression is a type of conditional modeling in which the mean of one variable is described by a linear combination of other variables
Bayesian_linear_regression
Learned society for Bayesian statistics
The International Society for Bayesian Analysis (ISBA) is a society with the goal of promoting Bayesian analysis for solving problems in the sciences and
International Society for Bayesian Analysis
International_Society_for_Bayesian_Analysis
Interpretation of probability
data analysis using what is now known as Bayesian inference. Mathematician Pierre-Simon Laplace pioneered and popularized what is now called Bayesian probability
Bayesian_probability
Experimental design framework
Bayesian experimental design provides a general probability-theoretical framework from which other theories on experimental design can be derived. It is
Bayesian_experimental_design
Free and open-source statistical program
ANOVA, Regression, Variances) BSTS: Bayesian take on linear Gaussian state space models suitable for time series analysis. Circular Statistics: Basic methods
JASP
Statistical method for molecular phylogenetics
Bayesian inference of phylogeny combines the information in the prior and in the data likelihood to create the so-called posterior probability of trees
Bayesian inference in phylogeny
Bayesian_inference_in_phylogeny
Probabilistic graphical representation of causal relationships
A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents a
Bayesian_network
Sequential model-based optimization of expensive black-box functions
Bayesian optimization is a sequential model-based strategy for global optimization of black-box objective functions whose evaluations are costly. It is
Bayesian_optimization
Statistical technique used for feature selection
Bayesian structural time series (BSTS) model is a statistical technique used for feature selection, time series forecasting, nowcasting, inferring causal
Bayesian structural time series
Bayesian_structural_time_series
Fienberg, (2006) When did Bayesian Inference become "Bayesian"? Archived 2014-09-10 at the Wayback Machine Bayesian Analysis, 1 (1), 1–40. See page 5.
History_of_statistics
Statistical estimation method
In statistics and econometrics, Bayesian vector autoregression (BVAR) uses Bayesian methods to estimate a vector autoregression (VAR) model. BVAR differs
Bayesian vector autoregression
Bayesian_vector_autoregression
Computational method in Bayesian statistics
Approximate Bayesian computation (ABC) constitutes a class of computational methods rooted in Bayesian statistics that can be used to estimate the posterior
Approximate Bayesian computation
Approximate_Bayesian_computation
French statistician (born 1961)
from 2006 to 2009. He was president of the International Society for Bayesian Analysis in 2008. In 2016 he was joint program chair of the AIStats conference
Christian_Robert
first complete analysis of Bayesian Inference for many statistical problems. Importance: Includes a large body of research on Bayesian analysis for outlier
List of publications in statistics
List_of_publications_in_statistics
Breed of sheep
Trends for Milk Production of Blond-Faced Latxa Sheep Using Bayesian Analysis". Journal of Dairy Science. 79 (12): 2268–77. doi:10.3168/jds.S0022-0302(96)76604-3
Latxa
Explaining the brain's abilities through statistical principles
Bayesian approaches to brain function investigate the capacity of the nervous system to operate in situations of uncertainty in a fashion that is close
Bayesian approaches to brain function
Bayesian_approaches_to_brain_function
Italian statistician
editor-in-chief of the academic journal Bayesian Analysis. He was the president of the International Society for Bayesian Analysis in 2021. 2015: Fellow of the
Igor_Prünster
Experimental design that is optimal with respect to some statistical criterion
Design and Analysis of Experiments. Handbook of Statistics. pp. 977–1006. DasGupta, A. "Review of Optimal Bayesian Designs". Design and Analysis of Experiments
Optimal_experimental_design
Python package
ArviZ (/ˈɑːrvɪz/ AR-vees) is a Python package for exploratory analysis of Bayesian models. It is specifically designed to work with the output of probabilistic
ArviZ
Statistical model written in multiple levels
Bayesian hierarchical modelling is a statistical model written in multiple levels (hierarchical form) that estimates the posterior distribution of model
Bayesian hierarchical modeling
Bayesian_hierarchical_modeling
Branch of econometrics
Bayesian econometrics is a branch of econometrics which applies Bayesian principles to economic modelling. Bayesianism is based on a degree-of-belief interpretation
Bayesian_econometrics
Statistical method that summarizes and/or integrates data from multiple sources
been executed using Bayesian methods, mixed linear models and meta-regression approaches. Specifying a Bayesian network meta-analysis model involves writing
Meta-analysis
Criterion for model selection
In statistics, the Bayesian information criterion (BIC) or Schwarz information criterion (also SIC, SBC, SBIC) is a criterion for model selection among
Bayesian information criterion
Bayesian_information_criterion
Probabilistic theory of knowledge
Bayesian epistemology is a formal approach to various topics in epistemology that has its roots in Thomas Bayes' work in the field of probability theory
Bayesian_epistemology
Indian-American statistician
known for his research contributions to Bayesian hierarchical modeling and inference for spatial data analysis. He is Professor of Biostatistics and Senior
Sudipto_Banerjee
Ratio of competing statistical models
Chen, Ming-Hui; Sinha, Debajyoti (2001). "Model Comparison". Bayesian Survival Analysis. Springer Series in Statistics. New York: Springer. pp. 246–254
Bayes_factor
Collection of statistical models
Analysis of variance (ANOVA) is a family of statistical methods used to compare the means of two or more groups by analyzing variance. Specifically, ANOVA
Analysis_of_variance
Game theory concept
In game theory, a Bayesian game is a strategic decision-making model which assumes players have incomplete information. Players may hold private information
Bayesian_game
Probability distribution
)} it generalizes the normal distribution and also arises in the Bayesian analysis of data from a normal family as a compound distribution when marginalizing
Student's_t-distribution
Denial of the scientific consensus on climate change
popularity of conspiracy theories of presidential assassination: A Bayesian analysis". Journal of Personality and Social Psychology. 37 (5): 637–644. doi:10
Climate_change_denial
Concept in medicine referring to design of clinical trials
nature of adaptive trials inherently suggests the use of Bayesian statistical analysis. Bayesian statistics inherently address updating information such
Adaptive_design_(medicine)
Statistics and machine learning technique
Andrew (2018). "Using Stacking to Average Bayesian Predictive Distributions (with Discussion)". Bayesian Analysis. 13 (3): 917–1007. arXiv:1704.02030. doi:10
Ensemble_learning
Set of statistical processes for estimating the relationships among variables
accommodating various types of missing data, nonparametric regression, Bayesian methods for regression, regression in which the predictor variables are
Regression_analysis
American statistician
founding Editor-in-Chief of Bayesian Analysis (journal), and Executive Editor (editor-in-chief) of the international review journal Statistical Science. At
Robert_Kass
popularity of conspiracy theories of presidential assassination: A Bayesian analysis". Journal of Personality and Social Psychology. 37 (5): 637–644. doi:10
Psychology of climate change denial
Psychology_of_climate_change_denial
International Journal of Forecasting Journal of Time Series Analysis The following journals are considered open access: Bayesian Analysis Brazilian Journal of Probability
List_of_statistics_journals
Italian statistician
International Society for Bayesian Analysis in 2025. He was the editor-in-chief on the academic journal Bayesian Analysis from 2019 to 2021, and became
Michele_Guindani
Method of statistical inference
Objective Bayesian Analysis". Bayesian Analysis. 1 (3): 385–402. doi:10.1214/06-ba115. In listing the competing definitions of "objective" Bayesian analysis, "A
Statistical_hypothesis_test
Statistical method
Factor analysis is a statistical method used to describe variability among observed, correlated variables in terms of a potentially lower number of unobserved
Factor_analysis
Richard G. (December 1, 2010). "Galaxy formation: a Bayesian uncertainty analysis". Bayesian Analysis. 5 (4): 619–669. doi:10.1214/10-BA524 – via Project
Bayesian_history_matching
Process of using data analysis for predicting population data from sample data
alia's Statistics. Moore et al. (2015). Gelman A. et al. (2013). Bayesian Data Analysis (Chapman & Hall). Peirce (1877-1878) Peirce (1883) Freedman, Pisani
Statistical_inference
Indian-American statistician
number of problems on Bayesian analysis and authored journal articles for developing theories and methods related to Bayesian modeling and inference
Dipak_K._Dey
Probabilistic problem-solving algorithm
density function analysis of radiative forcing. Monte Carlo methods are used in various fields of computational biology, for example for Bayesian inference in
Monte_Carlo_method
Mathematical rule for inverting probabilities
likelihood of being a carrier for a recessive gene of interest. A Bayesian analysis can be done based on family history or genetic testing to predict
Bayes'_theorem
Type of statistical inference
and type II errors. As a point of reference, the complement to this in Bayesian statistics is the minimum Bayes risk criterion. Because of the reliance
Frequentist_inference
Probabilistic classification algorithm
quite well in many complex real-world situations. In 2004, an analysis of the Bayesian classification problem showed that there are sound theoretical
Naive_Bayes_classifier
BEAST 2 is a cross-platform program for Bayesian analysis of molecular sequences. Using MCMC, it estimates rooted, timed phylogenies using a range of
BEAST_2
American statistician
World 1991–2001 Science Watch President, International Society for Bayesian Analysis, 2006 Recipient, Parzen Prize, 2006 Distinguished Research Medal,
Alan_E._Gelfand
Study of uncertainty in the output of a mathematical model or system
(PDF). Journal of Statistical Software. 33 (6). doi:10.18637/jss.v033.i06. Becker, W.; Worden, K.; Rowson, J. (2013). "Bayesian sensitivity analysis of bifurcating
Sensitivity_analysis
Italian statistician
focusses on Bayesian methods, specifically robustness and stochastic process inference. He has done innovative work on the sensitivity of Bayesian methods
Fabrizio_Ruggeri
Survey-based statistical technique
unsuitable for market segmentation studies. With newer hierarchical Bayesian analysis techniques, individual-level utilities may be estimated that provide
Conjoint_analysis
Bayesian statistics textbook by Richard McElreath
Statistical Rethinking: A Bayesian Course with Examples in R and Stan is an applied Bayesian statistics textbook by Richard McElreath. A second edition
Statistical_Rethinking
Austrian academic statistician
known for her research in Bayesian analysis. In 2020 she was the President of the International Society for Bayesian Analysis. Sylvia Frühwirth-Schnatter
Sylvia_Frühwirth-Schnatter
Type of statistical model
Hyperparameter Mixed-design analysis of variance Multiscale modeling Random effects model Nonlinear mixed-effects model Bayesian hierarchical modeling Restricted
Multilevel_model
Sequence of data points over time
Nonlinear mixed-effects modeling Dynamic time warping Dynamic Bayesian network Time-frequency analysis techniques: Fast Fourier transform Continuous wavelet transform
Time_series
Use of statistical measurement systems to study human behavior in a social environment
theory Bayesian statistics Stochastic process Latent class model Cluster analysis Multidimensional scaling Classification analysis Cohort analysis Social
Social_statistics
Extinct genus of Early Miocene ape from Egypt
secondary bayesian analysis tree based on craniodental and DNA data is given below: A simplified version of the standard non-clock bayesian analysis tree is
Masripithecus
American statistician
frequentist properties. He is also recognized for his analysis of the opposition between Bayesian and frequentist visions on testing statistical hypotheses
James_O._Berger
In Bayesian probability theory
likelihood function that has been integrated over the parameter space. In Bayesian statistics, it represents the probability of generating the observed sample
Marginal_likelihood
pp. 361–371. Benson, Noah C; Winawer, Jonathan (December 2018). "Bayesian analysis of retinotopic maps". eLife. 7 e40224. doi:10.7554/elife.40224. PMC 6340702
Data_analysis
Method of data analysis
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data
Principal_component_analysis
Science of characterizing uncertainties
(2009-03-01). "Modularization in Bayesian analysis, with emphasis on analysis of computer models". Bayesian Analysis. 4 (1). Institute of Mathematical
Uncertainty_quantification
Type of heuristic technique
bounds established for UCB algorithms to Bayesian regret bounds for Thompson sampling or unify regret analysis across both these algorithms and many classes
Thompson_sampling
Grouping a set of objects by similarity
Cluster analysis, or clustering, is a data analysis technique aimed at partitioning a set of objects into groups such that objects within the same group
Cluster_analysis
Branch of statistics focusing on spatial data sets
calculate its posterior. High-dimensional Bayesian geostatistics refers to Bayesian modeling and analysis for geostatistical data when the number of
Geostatistics
American statistician
Hal S.; Dunson, David B.; Vehtari, Aki; Rubin, Donald B. (2013). Bayesian Data Analysis, Third Edition. New York, New York: Chapman and Hall. doi:10.1201/b16018
David_Dunson
Formal information theory restatement of Occam's Razor
Minimum message length (MML) is a Bayesian information-theoretic method for statistical model comparison and selection. It provides a formal information
Minimum_message_length
Task of selecting a statistical model from a set of candidate models
the Akaike information criterion and (ii) the Bayes factor and/or the Bayesian information criterion (which to some extent approximates the Bayes factor)
Model_selection
Concept in statistical science
(2013). Bayesian Data Analysis (Third ed.). Chapman and Hall/CRC. ISBN 978-1-4398-4095-5. Watanabe, Sumio (2013). "A Widely Applicable Bayesian Information
Widely applicable information criterion
Widely_applicable_information_criterion
Distribution of an uncertain quantity
dominates the information contained in the data being analyzed. The Bayesian analysis combines the information contained in the prior with that extracted
Prior_probability
Interpretation of probability
(15 May 2017). "Explicit Bayesian analysis for process tracing: Guidelines, opportunities, and caveats". Political Analysis. 25 (3): 363–380. doi:10.1017/pan
Frequentist_probability
Machine learning and applied statistics
Girolami, M. (2019). "A Bayesian conjugate gradient method". Bayesian Analysis. 14 (3). International Society for Bayesian Analysis: 937–1012. doi:10.1214/19-BA1145
Probabilistic_numerics
British statistician and geneticist (1919–2000)
American Statistical Association. Biography portal Cornwall portal Analysis of variance Bayesian experimental design Biostatistics ("Biometry" or "Biometrics")
Oscar_Kempthorne
Interval bounded by an upper and a lower limit statistics
confidence intervals (a frequentist method) and credible intervals (a Bayesian method). Less common forms include likelihood intervals, fiducial intervals
Interval_estimation
Method in statistics
the class of probabilistic numerical methods. Bayesian quadrature views numerical integration as a Bayesian inference task, where function evaluations are
Bayesian_quadrature
Concepts underlying statistical methods
on the analysis and interpretation of data, and some of these contrasts have been subject to centuries of debate. Examples include the Bayesian inference
Foundations_of_statistics
Method used in statistics, pattern recognition, and other fields
Linear discriminant analysis (LDA), normal discriminant analysis (NDA), canonical variates analysis (CVA), or discriminant function analysis is a generalization
Linear_discriminant_analysis
Function related to statistics and probability theory
B. Carlin, H. S. Stern, D. B. Dunson, A. Vehtari, D. B. Rubin: Bayesian Data Analysis (3rd ed., Chapman & Hall/CRC 2014), §1.3 Sox, H. C.; Higgins, M
Likelihood_function
Use of statistics in psychology
include psychometrics, factor analysis, experimental designs, and Bayesian statistics. The article also discusses journals in the same field. Psychometrics
Psychological_statistics
Class of statistical tests
tested against the null hypothesis that it is normally distributed. In Bayesian statistics, one does not "test normality" per se, but rather computes the
Normality_test
Approach to optimizing robustness to failure
it is convenient to view it as an instance of Bayesian analysis. The essence of the Bayesian analysis is applying probabilities for different possible
Info-gap_decision_theory
Statistical model
2013.04.029. Banerjee, Sudipto (2017). "High-dimensional Bayesian Geostatistics". Bayesian Analysis. 12 (2): 583–614. doi:10.1214/17-BA1056R. PMC 5790125
Gaussian_process
Genus of ornithischian dinosaurs
analysis recovered Doolysaurus in an unresolved position within the family, while the 50% majority-rule consensus parsimony analysis and the Bayesian
Doolysaurus
Python package
Elicitation: The Past, Present, and Future". Bayesian Analysis. 19 (4). International Society for Bayesian Analysis: 1–33. arXiv:2112.01380. doi:10.1214/23-BA1381
Bambi_(software)
exercise, as well as consult on computational genetics analysis. Other work includes Bayesian hierarchical models, Markov chain Monte Carlo theory, bureaucratic
Jeff_Gill_(academic)
Application of statistical methods to marketing processes
In marketing, Bayesian inference allows for decision making and market research evaluation under uncertainty and with limited data. The communication between
Bayesian inference in marketing
Bayesian_inference_in_marketing
Feature of artificial neural networks
to the infinite width limit of Bayesian neural networks, and to the distribution over functions realized by non-Bayesian neural networks after random initialization
Large width limits of neural networks
Large_width_limits_of_neural_networks
Branch of applied probability theory
theory and Bayesian Analysis (2nd ed.). New York: Springer-Verlag. ISBN 978-0-387-96098-2. MR 0804611. Bernardo JM, Smith AF (1994). Bayesian Theory. Wiley
Decision_theory
Problem in statistical estimation
numbers. The problem can be approached using either frequentist inference or Bayesian inference, leading to different results. Estimating the population maximum
German_tank_problem
teams is a predictor of length of a procedure: A retrospective Bayesian analysis". Journal of Vascular Surgery. 71 (3): 959–966. doi:10.1016/j.jvs.2019
Predictive methods for surgery duration
Predictive_methods_for_surgery_duration
American Statistician
Bayesian Analysis in 2020 and of the Institute of Mathematical Statistics in 2021. He served as President of the International Society for Bayesian Analysis
Steve_MacEachern
British statistician and author (1948–2023)
Bayesian Analysis, alongside Arnold Zellner and Gordon Kaufman. Leonard's books include A Course in Categorical Data Analysis and Bayesian Methods: An
Thomas_H._Leonard
Mathematical relation assigning a probability event to a cost
EMS Press Berger, James O. (1985). Statistical decision theory and Bayesian Analysis (2nd ed.). New York: Springer-Verlag. Bibcode:1985sdtb.book.....B
Loss_function
Quantitative analysis of law
the legal system, as a way to bridge quantitative analysis, and equitable judicial processes. Bayesian inference Causal inference Instrumental variables
Jurimetrics
BAYESIAN ANALYSIS-JOURNAL
BAYESIAN ANALYSIS-JOURNAL
BAYESIAN ANALYSIS-JOURNAL
BAYESIAN ANALYSIS-JOURNAL
BAYESIAN ANALYSIS-JOURNAL
BAYESIAN ANALYSIS-JOURNAL
BAYESIAN ANALYSIS-JOURNAL
BAYESIAN ANALYSIS-JOURNAL
BAYESIAN ANALYSIS-JOURNAL