2026-06-28T10:32:54Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/502192023-08-26T10:37:04Zcom_20.500.14352_14col_20.500.14352_15
Docta Complutense
author
Menéndez Calleja, María Luisa
author
Pardo Llorente, Julio Ángel
author
Pardo Llorente, Leandro
2023-06-20T09:42:24Z
2023-06-20T09:42:24Z
2008
0361-0926
10.1080/03610920701669710
https://hdl.handle.net/20.500.14352/50219
http://www.tandfonline.com/doi/pdf/10.1080/03610920701669710
http://www.tandfonline.com/
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.
eng
Phi-divergence statistics for testing linear hypotheses in logistic regression models
journal article
URL
https://docta.ucm.es/bitstreams/285f89b3-7fea-4a42-990c-45f451e3beb9/download
File
MD5
5faa100335484eb8450d7e0d7d1f04a0
143157
application/pdf
PardoJulio04.pdf