Asymptotic Optimality for $C_p, C_L$, Cross-Validation and Generalized Cross-Validation: Discrete Index Set

Asymptotic optimality of likelihood-based cross-validation.

Likelihood-based cross-validation is a statistical tool for selecting a density estimate based on n i.i.d. observations from the true density among a collection of candidate density estimators. General examples are the selection of a model indexing a maximum likelihood estimator, and the selection of a bandwidth indexing a nonparametric (e.g. kernel) density estimator. In this article, we estab...

Customer Validation in Cross-Dock

Considering the importance of validation of customers in the cross-dock and since this is one of the problems of implementing cross-dock system in Iran, this study attempted to extract customer validation criteria. The purpose of the research is to eliminate the distrust of distributors in receiving the funds of the sent items and the statistical sample of this research is the experts of the sy...

The generalized cross validation filter

Generalized cross validation (GCV) is one of the most important approaches used to estimate parameters in the context of inverse problems and regularization techniques. A notable example is the determination of the smoothness parameter in splines. When the data are generated by a state space model, like in the spline case, efficient algorithms are available to evaluate the GCV score with comple...

Generalized Correlated Cross-Validation (GCCV)

Generalized cross validation for wavelet thresholding

Noisy data are often fitted using a smoothing parameter, controling the importance of two objectives that are opposite to a certain extent. One of these two is smoothness and the other is closeness to the input data. The optimal value of this paramater minimizes the error of the result (as compared to the unknown, exact data), usually expressed in the L2 norm. This optimum cannot be found exact...