Please use this identifier to cite or link to this item: https://doi.org/10.1021/ie401990x
Title: Filtering of the ARMAX process with generalized t -distribution noise: The influence function approach
Authors: Ho, W.K. 
Ling, K.V.
Vu, H.D.
Wang, X.
Issue Date: 30-Apr-2014
Citation: Ho, W.K., Ling, K.V., Vu, H.D., Wang, X. (2014-04-30). Filtering of the ARMAX process with generalized t -distribution noise: The influence function approach. Industrial and Engineering Chemistry Research 53 (17) : 7019-7028. ScholarBank@NUS Repository. https://doi.org/10.1021/ie401990x
Abstract: The commonly made assumption of Gaussian noise is an approximation to reality. In this paper, influence function, an analysis tool in robust statistics, is used to formulate a recursive solution for the filtering of the ARMAX process with generalized t-distribution noise. By being a superset encompassing Gaussian, uniform, t, and double exponential distributions, generalized t-distribution has the flexibility of characterizing noise with Gaussian or non-Gaussian statistical properties. The filter is formulated as a maximum likelihood problem, but instead of solving the optimization problem numerically, influence function approximation is used to obtain a recursive solution to reduce the computational load and facilitate real-time implementation. The influence function equations derived are also useful in determining the variance of the filter and the impact of outliers. © 2014 American Chemical Society.
Source Title: Industrial and Engineering Chemistry Research
URI: http://scholarbank.nus.edu.sg/handle/10635/82362
ISSN: 15205045
DOI: 10.1021/ie401990x
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