Advances in Multivariate Statistical Models: Approaches and Applications for Continuous Data
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D1: Probability and Statistics".
Deadline for manuscript submissions: 31 March 2027 | Viewed by 769
Editors
Interests: probability and statistics; model with errors in variables; elliptical and skew-elliptical distribution; estimation; diagnosis; asymptotic distribution and estimation of maximum likelihood; lifetime models; Birnbaum–Saunders distribution
Special Issue Information
Dear Colleagues,
Nowadays, multi-dimensional data are increasingly common, raising the need to fit data to multivariate models and justifying the use of multivariate methods. Therefore, we invite original research articles and reviews that address statistical models with multivariate continuous responses (symmetric or asymmetric), with applications to real datasets. Contributions involving their application to high-dimensional data will be especially welcome. Potential contributions can cover a wide range of topics, including parameter estimation and hypothesis testing, multivariate data adjustment techniques, residuals, and diagnostic analysis. The goal in this Special Issue is to bring together the most recent research and practical applications in these areas.
In other words, this Special Issue aims to promote the development of new approaches and fundamental research topics, with applications in various scientific areas, seeking to improve the practices of researchers and practitioners in statistics and related areas by offering more robust and accurate solutions for the analysis of complex data.
Dr. Filidor Edilfonso Vilca-Labra
Dr. Camila Zeller
Guest Editors
Manuscript Submission Information
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Keywords
- estimation
- asymptotic properties
- goodness of fit
- multivariate data analysis
- kurtosis
- maximum likelihood
- regression model
- diagnostic analysis
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