Comparing the mean vectors of two independent multivariate log-normal distributions

DOI10.1080/02664763.2013.838669OpenAlexW1988534423MaRDI QIDQ5128577

No author found.

Publication date: 28 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2013.838669

zbMATH Keywords

heteroscedasticitycoverage probabilitygeneralized pivotal quantitytype I errorsgeneralized test variablemultivariate log-normal

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (2)

Bootstrap inference on the Behrens–Fisher-type problem for the skew-normal population under dependent samples ⋮ Inferences on correlation coefficients of bivariate log-normal distributions

Uses Software

• heplots

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Visualizing hypothesis tests in multivariate linear models: the \texttt{heplots} package for R
• Statistical inference for the common mean of two log-normal distributions and some applications in reliability
• Inferences on the means of lognormal distributions using generalized \(p\)-values and generalized confidence intervals.
• Generalized \(p\)-values and generalized confidence regions for the multivariate Behrens-Fisher problem and MANOVA.
• Generalized inferences on the common mean vector of several multivariate normal populations
• The generalized P-value in one-sided testing in two sample multivariate normal populations
• Likelihood Analysis for the Ratio of Means of Two Independent Log-Normal Distributions
• Generalized Confidence Intervals
• Inferences on a linear combination of K multivariate normal mean vectors
• Some Techniques for Assessing Multivarate Normality Based on the Shapiro- Wilk W
• Methods for Comparing the Means of Two Independent Log-Normal Samples

This page was built for publication: Comparing the mean vectors of two independent multivariate log-normal distributions