A necessary Bayesian nonparametric test for assessing multivariate normality

DOI10.3103/S1066530721030029zbMath1490.62130OpenAlexW4285420823MaRDI QIDQ2670674

Luai Al-Labadi, Zahra Saberi, Forough Fazeli Asl

Publication date: 1 June 2022

Published in: Mathematical Methods of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.3103/s1066530721030029

zbMATH Keywords

Dirichlet processmultivariate hypothesis testingrelative belief inferencesAnderson-Darling distancesquared radii

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Hypothesis testing in multivariate analysis (62H15) Bayesian inference (62F15)

Related Items (1)

On robustness of the relative belief ratio and the strength of its evidence with respect to the geometric contamination prior

Uses Software

• energy
• mvShapiroTest

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A Generalization of Shapiro–Wilk's Test for Multivariate Normality
• Energy statistics: a class of statistics based on distances
• On a rapid simulation of the Dirichlet process
• A graphical method for assessing multivariate normality
• Conditional probability integral transformations and goodness-of-fit tests for multivariate normal distributions
• Exploring multivariate data with the forward search.
• A robustified Jarque-Bera test for multivariate normality
• Goodness of fit for the logistic regression model using relative belief
• Two-sample Kolmogorov-Smirnov test using a Bayesian nonparametric approach
• Optimal robustness results for relative belief inferences and the relationship to prior-data conflict
• Testing for normality in any dimension based on a partial differential equation involving the moment generating function
• Bayesian test of normality versus a Dirichlet process mixture alternative
• Using prior expansions for prior-data conflict checking
• On simulations from the two-parameter Poisson-Dirichlet process and the normalized inverse-Gaussian process
• A Bayesian analysis of some nonparametric problems
• A Bayesian nonparametric goodness of fit test for right censored data based on approximate samples from the beta-Stacy process
• Some Techniques for Assessing Multivarate Normality Based on the Shapiro- Wilk W
• Multivariate extension of chi-squared univariate normality test
• Pushing the Limits of Contemporary Statistics: Contributions in Honor of Jayanta K. Ghosh
• On simulation from infinitely divisible distributions
• A class of invariant consistent tests for multivariate normality
• Plotting squared radii
• Bayesian ikference procedures derived via the concept of relative surprise
• Likelihood ratio tests for multivariate normality
• New tests for multivariate normality based on Small's and Srivastava's graphical methods
• Prior‐based model checking
• A powerful affine invariant test for multivariate normality based on interpoint distances of principal components
• A powerful test for multivariate normality
• A Necessary Power Divergence Type Family Tests of Multivariate Normality
• Goodness-of-fit tests based on the distance between the Dirichlet process and its base measure
• Measures of multivariate skewness and kurtosis with applications
• A Test of Goodness of Fit
• Self-Calibrating Quantile–Quantile Plots
• Checking for prior-data conflict

This page was built for publication: A necessary Bayesian nonparametric test for assessing multivariate normality