Abstract #300713

This is the preliminary program for the 2003 Joint Statistical Meetings in San Francisco, California. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 2-5, 2003); 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.

Back to main JSM 2003 Program page
JSM 2003 Abstract #300713
Activity Number: 124
Type: Contributed
Date/Time: Monday, August 4, 2003 : 10:30 AM to 12:20 PM
Sponsor: SSC
Abstract - #300713
Title: On Estimation of Population Total Using Generalized Regression Predictor
Author(s): Raghunath Arnab*+ and Sarjinder Singh
Companies: University of Durban, Westville and St. Cloud State University
Address: Department of Statistics, Durban, , 4000, Southwest Africa
Keywords: generalized regression predictor ; auxiliary information ; esimation of total/variance ; optimality
Abstract:

The generalized regression predictor (greg) is used for the estimation of a finite population total when the study variable is well-related to the auxiliary variable. Chaudhuri and Roy (1997) provided the lower bound of the mean square error (mse) of variance estimators belonging to a class of nonhomogeneous quadratic unbiased estimators. They also found the optimum variance estimator whose mean square error attains the lower bound. We have shown that the derivation of the lower bound in Chaudhuri and Roy's (1997) paper is incorrect and their proposed optimal estimator does not attain the lower bound as originally claimed. An example is also provided to contradict the results of Chaudhri and Roy (1997). Model-assisted higher-order calibration approach to estimate the variance of regression predictor has also been investigated.

  • 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 2003 program

JSM 2003 For information, contact meetings@amstat.org or phone (703) 684-1221. If you have questions about the Continuing Education program, please contact the Education Department.
Revised March 2003