RT Journal Article
T1 Minimum phi-divergence estimator and phi-divergence statistics in generalized linear models with binary data
A1 Pardo Llorente, Julio Ángel
A1 Pardo Llorente, María del Carmen
AB In this paper, we assume that the data are distributed according to a binomial distribution whose probabilities follow a generalized linear model. To fit the data the minimum phi-divergence estimator is studied as a generalization of the maximum likelihood estimator. We use the minimum phi-divergence estimator, which is the basis of some new statistics, for solving the problems of testing in a generalized linear model with binary data. A wide simulation study is carried out for studying the behavior of the new family of estimators as well as of the new family of test statistics.
PB Springer
SN 1387-5841
YR 2008
FD 2008-09
LK https://hdl.handle.net/20.500.14352/50218
UL https://hdl.handle.net/20.500.14352/50218
LA eng
DS Docta Complutense
RD 10 abr 2025