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Please use this identifier to cite or link to this item: https://elib.bsu.by/handle/123456789/51941
Title: Scalability properties of a new forward search algorithm
Authors: Perrotta, D.
Riani, M.
Cerioli, A.
Torti, F.
Issue Date: 2013
Publisher: Minsk : Publ. center of BSU
Citation: Computer Data Analysis and Modeling: Theoretical and Applied Stochastics : Proc. of the Tenth Intern. Conf., Minsk, Sept. 10–14, 2013. Vol 1. — Minsk, 2013. — P. 87-88
Abstract: We propose some computational improvements for a robust method for the identification of atypical observations known as forward search, which is based on the idea of monitoring quantities of interest, such as parameter estimates and test statistics, as the model is fitted to data subsets of increasing size. We provide a recursive implementation of the procedure which exploits the information of the previous step and we demonstrate the computational advantages of the new approach using both synthetic and real data.
URI: http://elib.bsu.by/handle/123456789/51941
Appears in Collections:2013. Computer Data Analysis and Modeling. Vol 1
Vol. 1

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