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- W2801103670 abstract "In this paper we develop monitoring schemes for detecting structural changes in nonlinear autoregressive models. We approximate the regression function by asingle layer feedforward neural network. We show that CUSUM-type tests basedon cumulative sums of estimated residuals, that have been intensively studiedfor linear regression in both an offline as well as online setting, can be extendedto this model. The proposed monitoring schemes reject (asymptotically) the nullhypothesis only with a given probability but will detect a large class of alternativeswith probability one. In order to construct these sequential size tests the limitdistribution under the null hypothesis is obtained." @default.
- W2801103670 created "2018-05-17" @default.
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- W2801103670 date "2011-01-01" @default.
- W2801103670 modified "2023-09-26" @default.
- W2801103670 title "An online approach to detecting changes in nonlinear autoregressive models" @default.
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- W2801103670 hasPublicationYear "2011" @default.
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