The reproducing kernel Hilbert space approach in nonparametric regression problems with correlated observations-Reference-Cited by-同舟云学术

The reproducing kernel Hilbert space approach in nonparametric regression problems with correlated observations

Published:2019-10-01 Issue:6 Volume:72 Page:1479-1500
ISSN:0020-3157
Container-title:Annals of the Institute of Statistical Mathematics
language:en
Short-container-title:Ann Inst Stat Math

Author:

Benelmadani D.,Benhenni K.,Louhichi S.

Publisher

Springer Science and Business Media LLC

Subject

Statistics and Probability

Link

http://link.springer.com/content/pdf/10.1007/s10463-019-00733-3.pdf

Reference29 articles.

1. Altman, N. S. (1990). Kernel smoothing of data with correlated errors. American Statistical Association, 85, 749–759.

2. Azzalini, A. (1984). Estimation and hypothesis testing for collections of autoregressive time series. Biometrika, 71, 85–90.

3. Belouni, M., Benhenni, K. (2015). Optimal and robust designs for estimating the concentration curve and the AUC. Scandinavian Journal of Statistics: Theory and Application, 42, 453–470.

4. Benedetti, J. (1977). On the nonparametric estimation of the regression function. Journal of the Royal Statistical Society, 39, 248–253.

5. Benelmadani, D. (2019a). Contribution à la Régression non Paramétrique avec un Processus Erreur d’Autocovariance Générale et Application en Pharmacocinétique, Ph.D. 2019, Grenoble Alpes University, France.

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