Literature DB >> 19358745

Simulating multivariate g-and-h distributions.

Rhonda K Kowalchuk1, Todd C Headrick.   

Abstract

The Tukey family of g-and-h distributions is often used to model univariate real-world data. There is a paucity of research demonstrating appropriate multivariate data generation using the g-and-h family of distributions with specified correlations. Therefore, the methodology and algorithms are presented to extend the g-and-h family from univariate to multivariate data generation. An example is provided along with a Monte Carlo simulation demonstrating the methodology. In addition, algorithms written in Mathematica 7.0 are available from the authors for implementing the procedure.

Mesh:

Year:  2009        PMID: 19358745     DOI: 10.1348/000711009X423067

Source DB:  PubMed          Journal:  Br J Math Stat Psychol        ISSN: 0007-1102            Impact factor:   3.380


  2 in total

1.  A Cautionary Note on the Use of the Vale and Maurelli Method to Generate Multivariate, Nonnormal Data for Simulation Purposes.

Authors:  Oscar L Olvera Astivia; Bruno D Zumbo
Journal:  Educ Psychol Meas       Date:  2014-09-12       Impact factor: 2.821

2.  Some Improvements in Confidence Intervals for Standardized Regression Coefficients.

Authors:  Paul Dudgeon
Journal:  Psychometrika       Date:  2017-03-13       Impact factor: 2.500

  2 in total

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