Go to  Advanced Search

Globally robust inference for simple linear regression models with repeated median slope estimator

Show full item record

Files in this item

Files Size Format Description   View
ubc_2002-0447.pdf 2.620Mb Adobe Portable Document Format   View/Open
 
Title: Globally robust inference for simple linear regression models with repeated median slope estimator
Author: Khan, Md Jafar Ahmed
Degree Master of Science - MSc
Program Statistics
Copyright Date: 2002
Abstract: Globally robust inference takes into account the potential bias of the point estimates (Adrover, Salibian-Barrera and Zamar, 2002). To construct robust confidence intervals for the simple linear regression slope, the authors selected the generalized median of slopes (GMS) as their point estimate, considering its good bias behavior and asymptotic normality. However, GMS has a breakdown point of only 0.25, its asymptotic normality is established under very restrictive conditions, and its bias bound is known only for symmetric carrier distributions. In this study, we propose the repeated median slope (RMS) estimate as an alternative choice. RMS has a breakdown point of 0.50, its asymptotic normality holds under mild assumptions, and the bias bound for RMS is known for general carrier distributions. The proposed method achieves, more or less, the same observed coverage levels while it constructs intervals of smaller lengths, as compared to the GMS approach.
URI: http://hdl.handle.net/2429/12713
Series/Report no. UBC Retrospective Theses Digitization Project [http://www.library.ubc.ca/archives/retro_theses/]

This item appears in the following Collection(s)

Show full item record

All items in cIRcle are protected by copyright, with all rights reserved.

UBC Library
1961 East Mall
Vancouver, B.C.
Canada V6T 1Z1
Tel: 604-822-6375
Fax: 604-822-3893