This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 413
Type: Contributed
Date/Time: Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
Sponsor: Section for Statistical Programmers and Analysts
Abstract - #306666
Title: Making Inference for Inequality-Constrained Regression Problems
Author(s): Jinde Wang*+
Companies: Nanjing University
Address: Dept. of Mathematics, Nanjing, 210093, China
Keywords: Inequality constraints, ; confidence intervals ; confidence region
Abstract:

Inequality constrained statistical models have been found useful and necessary in more and more application areas.. For estimation topics, a very fundamental problem of how to make statistical inference has not been well solved. Unlike the unconstrained statistical problems, having distribution of the estimators, it is still not clear how to make inference. The purpose of this paper is to solve this problem. General principles of constructing confidence intervals and confidence regions are given. It can be seen that the approaches required , the forms of the confidence intervals and the shapes of the confidence regions for inequality constrained problems are quite different from the corresponding ones for unconstrained problems. The main principles and the methods proposed here should be applicable to inequality-constrained maximum likelihood estimation problems.


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