Accession Number:

ADA210757

Title:

Boundary Kernel Estimation of the Two Sample Comparison Density Function

Descriptive Note:

Technical rept.

Corporate Author:

TEXAS A AND M UNIV COLLEGE STATION DEPT OF STATISTICS

Personal Author(s):

• Alexander, William P.

Report Date:

1989-05-01

Pagination or Media Count:

252.0

Abstract:

The focus of this work is to derive functional and grap hical statistical techniques for the two sample problem suitable for implementation in modern computing environments. In the two sample problem, it is desired to test the null hypothesis that two independent random samples have a common distribution function. Assuming certain conditions on the distribution functions, a procedure is proposed which has strong graphical elements, a sound theoretical foundation, and estimates the relation of the two distributions if the null hypothesis is rejected. The proposed procedure has as its motivation the estimation of the comparison density and inference concerning its uniformity.

Descriptors:

• *KERNEL FUNCTIONS
• *PROBABILITY DENSITY FUNCTIONS
• COMPARISON
• THESES
• ESTIMATES
• NONPARAMETRIC STATISTICS
• BOUNDARIES
• SAMPLING
• GRAPHICS
• NULLS(AMPLITUDE)
• HYPOTHESES
• MOTIVATION
• STATISTICAL PROCESSES
• DISTRIBUTION FUNCTIONS
• DATA PROCESSING
• STATISTICAL TESTS

Subject Categories:

• Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE