Thumbnail
Access Restriction
Subscribed

Author Moore, T.J. ♦ Sadler, B.M.
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©2010
Language English
Subject Domain (in DDC) Technology ♦ Engineering & allied operations ♦ Applied physics
Subject Keyword Maximum likelihood estimation ♦ Testing ♦ Jacobian matrices ♦ Signal to noise ratio ♦ Biological system modeling ♦ Training ♦ Mathematical model ♦ asymptotic analysis ♦ Hypothesis testing ♦ constrained Cramér-Rao bound
Abstract The classical Wald and Rao test statistics are asymptotically equivalent to the generalized likelihood ratio test statistics, while not requiring parameter estimation under both hypotheses, and so they provide lower complexity test statistics. In this paper we develop corresponding variations of the Wald and Rao test for nested hypothesis testing under parameter constraints. The resulting tests incorporate the constrained Cramér-Rao bound formulation from Stoica and Ng, and unify some asymptotic hypothesis testing results. Examples will illustrate key ideas and test performance.
Description Author affiliation: Army Research Laboratory, Adelphi, MD 20783 USA (Moore, T.J.; Sadler, B.M.)
ISBN 9781424489787
ISSN 2151870X
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research ♦ Reading
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2010-10-04
Publisher Place Israel
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
e-ISBN 9781424489770
Size (in Bytes) 258.48 kB
Page Count 4
Starting Page 113
Ending Page 116


Source: IEEE Xplore Digital Library