On minimax rates of convergence in image models under sequential design

Alexander Korostelev

Statistics & Probability Letters, 1999, vol. 43, issue 4, 369-375

Abstract: A binary image model is studied with a Lipschitz edge function. The indicator function of the image is observed in random noise at n design points that can be chosen sequentially. The asymptotically minimax rate as n-->[infinity] is found in estimating the edge function, and an asymptotically optimal algorithm is described.

Keywords: Image; model; Minimax; rates; Asymptotics; Sequential; design (search for similar items in EconPapers)
Date: 1999
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Citations: View citations in EconPapers (1)

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