Advances in structural modeling robust to outliers in explanatory and response variables
Details
Serval ID
serval:BIB_6211BBB35D6A
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
Advances in structural modeling robust to outliers in explanatory and response variables
Title of the conference
The 2010 International Joint Conference on Neural Networks (IJCNN)
Publisher
IEEE
Address
Barcelona, Spain
ISBN
978-1-4244-6916-1
Publication state
Published
Issued date
07/2010
Peer-reviewed
Oui
Language
english
Abstract
The robust regression analysis works on data affected by deviations from a general assumption of normality. Currently the field of robust linear regression analysis is well developed and there are number of stable and verified by time methods. In contrast the robust structural modeling and high-order model parameter estimation are still under active development.
Keywords
Robustness, Polynomials, Mathematical model, Estimation, Artificial neural networks, Input variables, Generators
Create date
04/08/2017 12:32
Last modification date
20/08/2019 15:19
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