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

Format:

Book

Government document

Author/Creator:

Arvanitis, Matthew A., author.

Contributor:

Forest Products Laboratory (U.S.), issuing body.

Series:

Research paper FPL-RP ; 713.

Research paper FPL-RP ; 713

Language:

English

Subjects (All):

Confidence intervals.

Random data (Statistics).

Statistics.

Nonparametric statistics.

Lumber.

Confidence Intervals.

Statistics, Nonparametric.

lumber.

statistics.

Medical Subjects:

Confidence Intervals.

Statistics, Nonparametric.

Physical Description:

1 online resource (15 pages) : illustrations.

Place of Publication:

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

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."

Notes:

"March 2022."

In scope of the U.S. Government Publishing Office Cataloging and Indexing Program (C&I) and Federal Depository Library Program (FDLP).

Includes bibliographical references (pages 14-15).

Description based on online resource; title from PDF cover (USFS, viewed Jan. 5, 2023).

OCLC:

1308415873