Numerical Computing and Graphics for the Power Method Transformation Using Mathematica

This paper provides the requisite information and description of software that perform numerical computations and graphics for the power method polynomial transformation. The software developed is written in the Mathematica 5.2 package PowerMethod.m and is associated with fifth-order polynomials tha...

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Main Authors: Todd C. Headrick, Yanyan Sheng, Flaviu-Adrian Hodis
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2007-04-01
Series:Journal of Statistical Software
Subjects:
Online Access:http://www.jstatsoft.org/v19/i03/paper
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spelling doaj-536b563913414a699e9b870fe5ed13782020-11-24T21:22:32ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602007-04-01193Numerical Computing and Graphics for the Power Method Transformation Using MathematicaTodd C. HeadrickYanyan ShengFlaviu-Adrian HodisThis paper provides the requisite information and description of software that perform numerical computations and graphics for the power method polynomial transformation. The software developed is written in the Mathematica 5.2 package PowerMethod.m and is associated with fifth-order polynomials that are used for simulating univariate and multivariate non-normal distributions. The package is flexible enough to allow a user the choice to model theoretical pdfs, empirical data, or a user’s own selected distribution(s). The primary functions perform the following (a) compute standardized cumulants and polynomial coefficients, (b) ensure that polynomial transformations yield valid pdfs, and (c) graph power method pdfs and cdfs. Other functions compute cumulative probabilities, modes, trimmed means, intermediate correlations, or perform the graphics associated with fitting power method pdfs to either empirical or theoretical distributions. Numerical examples and Monte Carlo results are provided to demonstrate and validate the use of the software package. The notebook Demo.nb is also provided as a guide for user of the power method.http://www.jstatsoft.org/v19/i03/papercumulantsMathematicaMonte Carlonon-normalpolynomialsimulation
collection DOAJ
language English
format Article
sources DOAJ
author Todd C. Headrick
Yanyan Sheng
Flaviu-Adrian Hodis
spellingShingle Todd C. Headrick
Yanyan Sheng
Flaviu-Adrian Hodis
Numerical Computing and Graphics for the Power Method Transformation Using Mathematica
Journal of Statistical Software
cumulants
Mathematica
Monte Carlo
non-normal
polynomial
simulation
author_facet Todd C. Headrick
Yanyan Sheng
Flaviu-Adrian Hodis
author_sort Todd C. Headrick
title Numerical Computing and Graphics for the Power Method Transformation Using Mathematica
title_short Numerical Computing and Graphics for the Power Method Transformation Using Mathematica
title_full Numerical Computing and Graphics for the Power Method Transformation Using Mathematica
title_fullStr Numerical Computing and Graphics for the Power Method Transformation Using Mathematica
title_full_unstemmed Numerical Computing and Graphics for the Power Method Transformation Using Mathematica
title_sort numerical computing and graphics for the power method transformation using mathematica
publisher Foundation for Open Access Statistics
series Journal of Statistical Software
issn 1548-7660
publishDate 2007-04-01
description This paper provides the requisite information and description of software that perform numerical computations and graphics for the power method polynomial transformation. The software developed is written in the Mathematica 5.2 package PowerMethod.m and is associated with fifth-order polynomials that are used for simulating univariate and multivariate non-normal distributions. The package is flexible enough to allow a user the choice to model theoretical pdfs, empirical data, or a user’s own selected distribution(s). The primary functions perform the following (a) compute standardized cumulants and polynomial coefficients, (b) ensure that polynomial transformations yield valid pdfs, and (c) graph power method pdfs and cdfs. Other functions compute cumulative probabilities, modes, trimmed means, intermediate correlations, or perform the graphics associated with fitting power method pdfs to either empirical or theoretical distributions. Numerical examples and Monte Carlo results are provided to demonstrate and validate the use of the software package. The notebook Demo.nb is also provided as a guide for user of the power method.
topic cumulants
Mathematica
Monte Carlo
non-normal
polynomial
simulation
url http://www.jstatsoft.org/v19/i03/paper
work_keys_str_mv AT toddcheadrick numericalcomputingandgraphicsforthepowermethodtransformationusingmathematica
AT yanyansheng numericalcomputingandgraphicsforthepowermethodtransformationusingmathematica
AT flaviuadrianhodis numericalcomputingandgraphicsforthepowermethodtransformationusingmathematica
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