The problem of minimax estimation of a parameter θ when θ is restricted to a finite interval [θ₀,θ₀+m] is studied. The case of a convex loss function is considered. Sufficient conditions for existence of a minimax estimator which is a Bayes estimator with respect to a prior concentrated in two points θ₀ and θ₀+m are obtained. An example is presented.
@article{bwmeta1.element.bwnjournal-article-doi-10_4064-am32-2-3,
author = {Agata Boraty\'nska},
title = {Two-point priors and minimax estimation of a bounded parameter under convex loss},
journal = {Applicationes Mathematicae},
volume = {32},
year = {2005},
pages = {145-153},
zbl = {1062.62009},
language = {en},
url = {http://dml.mathdoc.fr/item/bwmeta1.element.bwnjournal-article-doi-10_4064-am32-2-3}
}
Agata Boratyńska. Two-point priors and minimax estimation of a bounded parameter under convex loss. Applicationes Mathematicae, Tome 32 (2005) pp. 145-153. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-doi-10_4064-am32-2-3/