The Annals of Statistics

Minimaxity of the Method of Regularization of Stochastic Processes

Ker-Chau Li

Full-text: Open access

Abstract

The idea of smoothing-spline interpolation is generalized to propose an estimator for the mean function of a stochastic process. A minimax property of the proposed estimator is then demonstrated under the usual squared loss function.

Article information

Source
Ann. Statist., Volume 10, Number 3 (1982), 937-942.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176345883

Digital Object Identifier
doi:10.1214/aos/1176345883

Mathematical Reviews number (MathSciNet)
MR663444

Zentralblatt MATH identifier
0497.62078

JSTOR
links.jstor.org

Subjects
Primary: 60G35: Signal detection and filtering [See also 62M20, 93E10, 93E11, 94Axx]
Secondary: 62M10: Time series, auto-correlation, regression, etc. [See also 91B84] 62G35: Robustness 62J05: Linear regression

Keywords
Autoregressive processes minimaxity method of regularization robustness smoothing splines spectrum

Citation

Li, Ker-Chau. Minimaxity of the Method of Regularization of Stochastic Processes. Ann. Statist. 10 (1982), no. 3, 937--942. doi:10.1214/aos/1176345883. https://projecteuclid.org/euclid.aos/1176345883


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