Please use this identifier to cite or link to this item:
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.
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
ISSN: 15205045
DOI: 10.1021/ie401990x
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Mar 21, 2019


checked on Mar 11, 2019

Page view(s)

checked on Mar 23, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.