Abstract
In Chapter 1 we found the convergence rates of some estimators in nonparametric regression and in the change-point problem. The purpose of this chapter is to show that these rates of convergence cannot be improved by any other estimators. We would like to study the bounds on the accuracy of estimators in these two statistical problems in parallel, though it may seem they have few common features. To realize this plan we embed them into a more general framework. Consider these particular models as examples of the general statistical model.
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© 1993 Springer-Verlag New York, Inc.
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Korostelev, A.P., Tsybakov, A.B. (1993). Minimax Lower Bounds. In: Minimax Theory of Image Reconstruction. Lecture Notes in Statistics, vol 82. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2712-0_2
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DOI: https://doi.org/10.1007/978-1-4612-2712-0_2
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-94028-1
Online ISBN: 978-1-4612-2712-0
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