Titlebook: Data Segmentation and Model Selection for Computer Vision; A Statistical Approa Alireza Bab-Hadiashar,David Suter Book 2000 Springer Scienc

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https://doi.org/10.1007/978-3-663-09498-2tti and Staudte. Then we propose a new method for robustly finding acceptable submodels using weights of evidence for hypotheses regarding the noncentrality parameter of the Wald test statistic. The theory is illustrated with applications to linear and logistic regression, and to finding the order of time series.

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Gian Paolo Cimellaro Ph.D., P.E.,Marta Piquéproperties of the most important robust methods for regression..The second part is devoted to robust model selection. We present robust versions of parametric model selection criteria as well as nonparametric techniques based on cross-validation.

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Robust Regression Methods and Model Selectionproperties of the most important robust methods for regression..The second part is devoted to robust model selection. We present robust versions of parametric model selection criteria as well as nonparametric techniques based on cross-validation.

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