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Author Arvanitis, Matthew A., author.

Title Small-sample solution to the two-sample problem for quantiles using melded random confidence intervals / Matthew A. Arvanitis.

Publication Info. [Madison, Wis.] : United States Department of Agriculture, Forest Service, Forest Products Laboratory, 2022.

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Description 1 online resource (15 pages) : illustrations.
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Series Research paper FPL-RP ; 713
Research paper FPL-RP ; 713.
Note "March 2022."
In scope of the U.S. Government Publishing Office Cataloging and Indexing Program (C&I) and Federal Depository Library Program (FDLP).
Bibliography Includes bibliographical references (pages 14-15).
Summary "A new nonparametric solution to the two-sample problem for quantiles is proposed. This solution is applicable to small samples and/or extreme quantiles, and it prioritizes limiting Type I error to the indicated level of significance over optimizing power or confidence interval width. Aside from continuity, no assumptions about the distributions are made. In this approach, nonparametric random confidence intervals obtained from the samples are "melded," resulting in a nonparametric confidence interval for the difference between the two population quantiles with a specified confidence level. Simulations and an application to lumber strength characteristics are exhibited."
Note Description based on online resource; title from PDF cover (USFS, viewed Jan. 5, 2023).
Subject Confidence intervals.
Random data (Statistics)
Statistics.
Nonparametric statistics.
Lumber.
Confidence Intervals
Statistics, Nonparametric
Intervalles de confiance.
Données aléatoires (Statistique)
Statistique non paramétrique.
Bois d'industrie.
Statistique.
lumber.
statistics.
Confidence intervals
Lumber
Nonparametric statistics
Random data (Statistics)
Statistics
Added Author Forest Products Laboratory (U.S.), issuing body.
Gpo Item No. 0083-B (online)
Sudoc No. A 13.78:FPL-RP-713

 
    
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