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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…mehr

Produktbeschreibung
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.

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Autorenporträt
Todd C. Headrick is an associate professor and coordinator of the Educational Statistics & Measurement program at Southern Illinois University Carbondale.