IJPAM: Volume 36, No. 3 (2007)
VIA GENERALIZED LINEAR MODELS



Faculty of Arts and Sciences
University of Marmara
Göztepe-Kadiköy, Istanbul, 34722, TURKEY


Abstract.In the studies done till now, situations, where mixture experiments have a
response with a normal distribution, have been taken into account. In case
of having a response with a normal distribution, it would be sufficient to
use Scheffé canonical polynomials and other mixture model forms for the
analysis of the mixture experiments. However, as in many applications, there
are situations when mixture experiments do not have a response with a normal
distribution. In this paper, Generalized Linear Models (GLMs), which with a
help of a link function takes advantage of natural distribution of the
response, were used for the analysis of mixture experiments with a Gamma
distribution. As a linear predictor, not only Scheffé models without a
constant term were used but also mixture models with inverse terms were
taken into account. The best subset models were obtained by using Gamma
distribution together with canonical and non-canonical link functions. Then
the proposed approach was examined on one example in literature.
Received: February 2, 2007
AMS Subject Classification: 62K99, 62J12
Key Words and Phrases: mixture experiments, generalized linear models, nonnormal response, Scheffé canonical polynomials, inverse terms in mixture models
Source: International Journal of Pure and Applied Mathematics
ISSN: 1311-8080
Year: 2007
Volume: 36
Issue: 3