Finite Form Representations for Meijer G and Fox H Functions Finite Form Representations for Meijer G and Fox H Functions
Lecture Notes in Statistics

Finite Form Representations for Meijer G and Fox H Functions

Applied to Multivariate Likelihood Ratio Tests Using Mathematica®, MAXIMA and R

    • €87.99
    • €87.99

Publisher Description

This book depicts a wide range of situations in which there exist finite form representations for the Meijer G and the Fox H functions. Accordingly, it will be of interest to researchers and graduate students who, when implementing likelihood ratio tests in multivariate analysis, would like to know if there exists an explicit manageable finite form for the distribution of the test statistics. In these cases, both the exact quantiles and the exact p-values of the likelihood ratio tests can be computed quickly and efficiently.

The test statistics in question range from common ones, such as those used to test e.g. the equality of means or the independence of blocks of variables in real or complex normally distributed random vectors; to far more elaborate tests on the structure of covariance matrices and equality of mean vectors. The book also provides computational modules in Mathematica®, MAXIMA and R, which allow readers to easily implement, plot and compute the distributions of any of these statistics, or any other statistics that fit into the general paradigm described here.

GENRE
Science & Nature
RELEASED
2019
13 December
LANGUAGE
EN
English
LENGTH
533
Pages
PUBLISHER
Springer International Publishing
PROVIDER INFO
Springer Science & Business Media LLC
SIZE
63.1
MB
Methodology and Applications of Statistics Methodology and Applications of Statistics
2022
Statistical Inference, Econometric Analysis and Matrix Algebra Statistical Inference, Econometric Analysis and Matrix Algebra
2008
Advanced Linear Modeling Advanced Linear Modeling
2019
Advances on Theoretical and Methodological Aspects of Probability and Statistics Advances on Theoretical and Methodological Aspects of Probability and Statistics
2019
Advances in Directional and Linear Statistics Advances in Directional and Linear Statistics
2010
Advances in Modeling and Simulation Advances in Modeling and Simulation
2022
Time Series Models Time Series Models
2022
Multivariate Reduced-Rank Regression Multivariate Reduced-Rank Regression
2022
Optimal Experimental Design Optimal Experimental Design
2023
Statistical Machine Learning for Engineering with Applications Statistical Machine Learning for Engineering with Applications
2024
Linear Dimensionality Reduction Linear Dimensionality Reduction
2025
Optimal Mixture Experiments Optimal Mixture Experiments
2014