Learning the smoothness of noisy curves with application to online curve estimation-Reference-Cited by-同舟云学术

Learning the smoothness of noisy curves with application to online curve estimation

Published:2022-01-01 Issue:1 Volume:16 Page:
ISSN:1935-7524
Container-title:Electronic Journal of Statistics
language:
Short-container-title:Electron. J. Statist.

Author:

Golovkine Steven¹,Klutchnikoff Nicolas²,Patilea Valentin³

Affiliation:

1. Groupe Renault & CREST - UMR 9194, Rennes, France

2. Univ Rennes, IRMAR - UMR 6625, France

3. Ensai, CREST - UMR 9194, Rennes, France

Publisher

Institute of Mathematical Statistics

Subject

Statistics and Probability,Statistics, Probability and Uncertainty

Reference41 articles.

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3. Scrucca, L., Fop, M., Murphy, T. B. and Raftery, A. E. (2016). mclust 5: clustering, classification and density estimation using Gaussian finite mixture models. The R Journal 8 289–317.

4. CARPENTIER, A. (2015). Testing the regularity of a smooth signal. Bernoulli 21 465–488.

5. BELLONI, A., CHERNOZHUKOV, V., CHETVERIKOV, D. and KATO, K. (2015). Some new asymptotic theory for least squares series: Pointwise and uniform results. Journal of Econometrics 186 345 – 366.

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