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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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 |
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1725995447186620416 |