Arbitrary Precision Mathematica Functions to Evaluate the One-Sided One Sample K-S Cumulative Sampling Distribution

Efficient rational arithmetic methods that can exactly evaluate the cumulative sampling distribution of the one-sided one sample Kolmogorov-Smirnov (K-S) test have been developed by Brown and Harvey (2007) for sample sizes n up to fifty thousand. This paper implements in arbitrary precision the same...

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Main Authors: J. Randall Brown, Milton E. Harvey
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2008-04-01
Series:Journal of Statistical Software
Subjects:
Online Access:http://www.jstatsoft.org/v26/i03/paper
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author J. Randall Brown
Milton E. Harvey
author_facet J. Randall Brown
Milton E. Harvey
author_sort J. Randall Brown
collection DOAJ
description Efficient rational arithmetic methods that can exactly evaluate the cumulative sampling distribution of the one-sided one sample Kolmogorov-Smirnov (K-S) test have been developed by Brown and Harvey (2007) for sample sizes n up to fifty thousand. This paper implements in arbitrary precision the same 13 formulae to evaluate the one-sided one sample K-S cumulative sampling distribution. Computational experience identifies the fastest implementation which is then used to calculate confidence interval bandwidths and p values for sample sizes up to ten million.
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spelling doaj.art-f6818ca8a1a14b13a5927beb9b75cb6a2022-12-22T03:46:09ZengFoundation for Open Access StatisticsJournal of Statistical Software1548-76602008-04-01263Arbitrary Precision Mathematica Functions to Evaluate the One-Sided One Sample K-S Cumulative Sampling DistributionJ. Randall BrownMilton E. HarveyEfficient rational arithmetic methods that can exactly evaluate the cumulative sampling distribution of the one-sided one sample Kolmogorov-Smirnov (K-S) test have been developed by Brown and Harvey (2007) for sample sizes n up to fifty thousand. This paper implements in arbitrary precision the same 13 formulae to evaluate the one-sided one sample K-S cumulative sampling distribution. Computational experience identifies the fastest implementation which is then used to calculate confidence interval bandwidths and p values for sample sizes up to ten million.http://www.jstatsoft.org/v26/i03/paperK-S cumulative sampling distributionsK-S one-sided one sample probabilitiesK-S confidence bandsarbitrary precision arithmetic
spellingShingle J. Randall Brown
Milton E. Harvey
Arbitrary Precision Mathematica Functions to Evaluate the One-Sided One Sample K-S Cumulative Sampling Distribution
Journal of Statistical Software
K-S cumulative sampling distributions
K-S one-sided one sample probabilities
K-S confidence bands
arbitrary precision arithmetic
title Arbitrary Precision Mathematica Functions to Evaluate the One-Sided One Sample K-S Cumulative Sampling Distribution
title_full Arbitrary Precision Mathematica Functions to Evaluate the One-Sided One Sample K-S Cumulative Sampling Distribution
title_fullStr Arbitrary Precision Mathematica Functions to Evaluate the One-Sided One Sample K-S Cumulative Sampling Distribution
title_full_unstemmed Arbitrary Precision Mathematica Functions to Evaluate the One-Sided One Sample K-S Cumulative Sampling Distribution
title_short Arbitrary Precision Mathematica Functions to Evaluate the One-Sided One Sample K-S Cumulative Sampling Distribution
title_sort arbitrary precision mathematica functions to evaluate the one sided one sample k s cumulative sampling distribution
topic K-S cumulative sampling distributions
K-S one-sided one sample probabilities
K-S confidence bands
arbitrary precision arithmetic
url http://www.jstatsoft.org/v26/i03/paper
work_keys_str_mv AT jrandallbrown arbitraryprecisionmathematicafunctionstoevaluatetheonesidedonesamplekscumulativesamplingdistribution
AT miltoneharvey arbitraryprecisionmathematicafunctionstoevaluatetheonesidedonesamplekscumulativesamplingdistribution