RT Journal Article
T1 Phi-divergence statistics for testing linear hypotheses in logistic regression models
A1 Menéndez Calleja, María Luisa
A1 Pardo Llorente, Julio Ángel
A1 Pardo Llorente, Leandro
AB In this paper we introduce and study two new families of statistics for the problem of testing linear combinations of the parameters in logistic regression models. These families are based on the phi-divergence measures. One of them includes the classical likelihood ratio statistic and the other the classical Pearson's statistic for this problem. It is interesting to note that the vector of unknown parameters, in the two new families of phi-divergence statistics considered in this paper, is estimated using the minimum phi-divergence estimator instead of the maximum likelihood estimator. Minimum phi-divergence estimators are a natural extension of the maximum likelihood estimator.
PB Taylor & Francis
SN 0361-0926
YR 2008
FD 2008
LK https://hdl.handle.net/20.500.14352/50219
UL https://hdl.handle.net/20.500.14352/50219
LA eng
DS Docta Complutense
RD 15 abr 2026