The power method transformation: its probability density function, distribution function, and its further use for fitting data

DOI10.1080/10629360600605065zbMath1113.62011OpenAlexW2078562120MaRDI QIDQ3446970

Rhonda K. Kowalchuk, Todd C. Headrick

Publication date: 27 June 2007

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/10629360600605065

zbMATH Keywords

momentssimulationcumulantsMonte Carlonon-normalitydistribution fitting

Mathematics Subject Classification ID

Related Items (6)

A characterization of power method transformations through the method of percentiles ⋮ The t-transformed power method distributions for simulating univariate and multivariate non-normal distributions ⋮ Concurrent generation of binary and nonnormal continuous data through fifth-order power polynomials ⋮ Generating correlated, non-normally distributed data using a non-linear structural model ⋮ Simulating Controlled Variate and Rank Correlations Based on the Power Method Transformation ⋮ A Method for Simulating Multivariate Non Normal Distributions with Specified Standardized Cumulants and Intraclass Correlation Coefficients

Uses Software

• Mathematica

Cites Work

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• An empirical study of the type I error rate and power for some selected normal-theory and nonparametric tests of the independence of two sets of variables
• A Method for Simulating Multivariate Non Normal Distributions with Specified Standardized Cumulants and Intraclass Correlation Coefficients
• A Method for Simulating Correlated Non-Normal Systems of Linear Statistical Equations
• Properties of the rank transformation in factorial analysis of covariance
• An investigation of the rank transformation in multiple regression.

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