Focusing on both univariate and multivariate nonnormal data generation, this book presents techniques for conducting a Monte Carlo simulation study. It shows how to use power method polynomials for simulating univariate and multivariate nonnormal distributions with specified cumulants and correlation matrices. By using the methodology and techniques developed in the text, readers can evaluate different transformations in terms of comparing percentiles, measures of central tendency, goodness-of-fit tests, and more. Along with many numerical examples and results, the book employs Mathematica in a range of procedures and offers the source code for download online.
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