A method of simulating multivariate nonnormal distributions by the Pearson distribution system and estimation

DOI10.1016/j.csda.2003.10.008zbMath1429.62029OpenAlexW2044072034MaRDI QIDQ956985

Yuichi Nagahara

Publication date: 26 November 2008

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2003.10.008

zbMATH Keywords

skewness and kurtosisPearson distribution systemgenerator of random numbersmultivariate nonnormal distributionsthird- and fourth-order moment matrix

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Random number generation in numerical analysis (65C10)

Related Items (6)

A method of calculating the downside risk by multivariate nonnormal distributions ⋮ The generalized Pearson family of distributions and explicit representation of the associated density functions ⋮ Generating correlated, non-normally distributed data using a non-linear structural model ⋮ Higher-order approximations to the distributions of fit indexes under fixed alternatives in structural equation models ⋮ Higher Order Asymptotic Cumulants of Studentized Estimators in Covariance Structures ⋮ Comparison of the alternative parameter estimators of Pearson distributions by robustness criteria

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A method for simulating non-normal distributions
• Inferences based on multiple skipped correlations
• Simulating multivariate nonnormal distributions
• On an integrated approach to member selection and parameter estimation for Pearson distributions
• On simulating non-normal distributions
• On asymptotic distributions of normal theory MLE in covariance structure analysis under some nonnormal distributions
• The PDF and CF of Pearson type IV distributions and the ML estimation of the parameters
• A test of normality with high uniform power.
• Fast fifth-order polynomial transforms for generating univariate and multivariate nonnormal distributions.
• Numerically stable cointegration analysis
• Inferences on correlation coefficients in some classes of nonnormal distributions
• A simple algorithm for generating random variates with a log-concave density
• Mersenne twister
• The multivariate skew-normal distribution
• Probability for Statisticians
• Non‐Gaussian Filter and Smoother Based on the Pearson Distribution System
• Some problems arising in approximating to probability distributions, using moments
• Systems of Frequency Curves

This page was built for publication: A method of simulating multivariate nonnormal distributions by the Pearson distribution system and estimation