Premium
Correspondence estimation of the source profiles in receptor modeling
Author(s) -
Gajewski Byron J.,
Spiegelman Clifford H.
Publication year - 2004
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.654
Subject(s) - estimator , consistency (knowledge bases) , least squares function approximation , statistics , efficiency , contrast (vision) , mathematics , asymptotic distribution , mixture model , econometrics , computer science , mathematical optimization , artificial intelligence
This article considers the estimation of source profiles from pollution data collected at one receptor site. At this receptor site, varying metrological conditions can cause errors that are possibly a mixture of distributions. A standard estimator utilizes a least squares approach because of its optimal properties under normally distributed errors and consistency under many other distributions. In contrast, we study the behavior of least squares relative to our new approach, which is better suited for dealing with errors having a mixture of distributions. The estimator loses efficiency under normal errors, but in turn gains efficiency while in the presence of a mixture of distributions. The new alternative has a tuning constant that determines the level of efficiency, which we show using asymptotic theory for large samples and simulation for small samples. An example from Houston, TX, U.S.A. is considered. Copyright © 2004 John Wiley & Sons, Ltd.