JSM 2005 Online Program

Abstract #304433

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

To View the Program:
You may choose to view all activities of the program or just parts of it at any one time. All activities are arranged by date and time.

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

The Program has labeled the meeting rooms with "letters" preceding the name of the room, designating in which facility the room is located:

Minneapolis Convention Center = “MCC” Hilton Minneapolis Hotel = “H” Hyatt Regency Minneapolis = “HY”

Back to main JSM 2005 Program page

Legend:

= Applied Session,

= Theme Session,

= Presenter

Activity Number:	270
Type:	Contributed
Date/Time:	Tuesday, August 9, 2005 : 10:30 AM to 12:20 PM
Sponsor:	General Methodology
Abstract - #304433
Title:	A Self-building System for Ranked Set Sampling
Author(s):	Tao Yu*+ and Ran He and Marepalli Rao
Companies:	University of Cincinnati and University of Cincinnati and University of Cincinnati
Address:	Department of Environmental Health, Cincinnati, OH, 45267-0056, United States
Keywords:	order statistics ; ranked set sampling ; nonparametric ; stratification ; variance reduction ; sample size
Abstract:	Ranked Set Sampling (RSS) has been proved an economical estimation under certain conditions. Various procedures based on RSS have been developed since the 80s to improve its precision. However, problems still exist. Little improvement has been made for nonparametric estimation. Decisions of sample sizes and necessary optimal designs of RSS in practice could be complicated, time-consuming, and unsuccessful after all. Imperfect ranking with potential subjective misjudgment or ranking with more than two characteristics also may hurt the efficiencies over other sampling methods. In this paper, we introduce an objective, self-building system or procedure for RSS to better solve the above problems. This system has been showed much better than other RSS-related procedures under most conditions for both nonparametric and parametric cases. In some situations, it is even closed to the precision of measuring all the hundreds of samples with only several actual measurements necessary.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2005 program