Mon Apr 12 10:38:07 EDT 2004
ABSTRACTS IN ECONOMIC HISTORY
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Name: Brian A'Hearn
Email: bahearn at fandm.edu
Institution: Department of Economics, Franklin & Marshall College
Co-author: none
Title: A restricted maximum likelihood estimator for truncated height samples
Internet Address of abstracted work:
http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B73DX-4BRTF0S-1&_user=10&_handle=B-WA-A-A-AB-MsSAYWA-UUA-AUYBWAVEYE-AUYUDECDYE-BBUDCWZWZ-AB-U&_fmt=full&_coverDate=03%2F31%2F2004&_rdoc=2&_orig=browse&_srch=%23toc%2311482%232004%23999979998%23483967!&_cdi=11482&view=c&_acct=C000050221&_version=1&_urlVersion=0&_userid=10&md5=ba8299e03572d19e5ceece518abc627b
By mail:
Department of Economics
Franklin & Marshall College
Box 3003
Lancaster, PA 17604-3003
USA
Language: English
Abstract:
A restricted maximum likelihood (ML) estimator is presented and evaluated
for use with truncated height samples. In the common situation of a small
sample truncated at a point not far below the mean, the ordinary ML
estimator suffers from high sampling variability. The restricted estimator
imposes an a priori value on the standard deviation and freely estimates
the mean, exploiting the known empirical stability of the former to obtain
less variable estimates of the latter. Simulation results validate the
conjecture that restricted ML behaves like restricted ordinary least
squares (OLS), whose properties are well established on theoretical
grounds. Both estimators display smaller sampling variability when
constrained, whether the restrictions are correct or not. The bias induced
by incorrect restrictions sets up a decision problem involving a
bias-precision tradeoff, which can be evaluated using the mean squared
error (MSE) criterion. Simulated MSEs suggest that restricted ML estimation
offers important advantages when samples are small and truncation points
are high, so long as the true standard deviation is within roughly 0.5 cm
of the chosen value.
Bibliography: A'Hearn, Brian. "A restricted maximum likelihood estimator for truncated height samples." Economics & Human Biology, Volume 2, Issue 1, March 2004, Pages 5-19.
Subject: C
Geographical Area: 0
Country/Region:
Time Period: 0
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