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Asymptotic expansion of the risk of maximum likelihood estimator with respect to -divergence
Sheena, Yo
This is an Accepted Manuscript of an article published by Taylor & Francis in Communications in Statistics - Theory and Methods on 2018 available online: http://www.tandfonline.com/10.1080/03610926.2017.1380828 .
Alpha divergence
connection
Fisher information metric
maximum likelihood estimator
Riemannian curvature
Published online: 13 Nov 2017
For a given parametric probability model, we consider the risk of the maximum likelihood estimator with respect to -divergence, which includes the special cases of Kullback-Leibler divergence, the Hellinger distance, and essentially (2)-divergence. The asymptotic expansion of the risk is given with respect to sample sizes up to order n(- 2). Each term in the expansion is expressed with the geometrical properties of the Riemannian manifold formed by the parametric probability model.
Article
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS. 47(16):4059-4087 (2018)
TAYLOR & FRANCIS INC
2018
eng
journal article
AM
http://hdl.handle.net/10091/00021643
https://soar-ir.repo.nii.ac.jp/records/20886
https://doi.org/10.1080/03610926.2017.1380828
10.1080/03610926.2017.1380828
0361-0926
AA10512682
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
47
16
4059
4087
https://soar-ir.repo.nii.ac.jp/record/20886/files/divergence_expansion_ver3.pdf
application/pdf
342.3 kB
2019-09-17