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Title: Generalized regression estimation for continuous time processes with values in functional spaces (English)
Author: Maillot, Bertrand
Author: Chesneau, Christophe
Language: English
Journal: Commentationes Mathematicae Universitatis Carolinae
ISSN: 0010-2628 (print)
ISSN: 1213-7243 (online)
Volume: 62
Issue: 4
Year: 2021
Pages: 461-481
Summary lang: English
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Category: math
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Summary: We consider two continuous time processes; the first one is valued in a semi-metric space, while the second one is real-valued. In some sense, we extend the results of F. Ferraty and P. Vieu in ``Nonparametric models for functional data, with application in regression, time-series prediction and curve discrimination'' (2004), by establishing the convergence, with rates, of the generalized regression function when a real-valued continuous time response is considered. As corollaries, we deduce the convergence of the conditional distribution function as well as conditional quantiles. Note that a parametric rate of convergence in probability is reached while working with a naive kernel. (English)
Keyword: continuous time process
Keyword: regression function estimation
Keyword: conditional distribution function
MSC: 62C05
MSC: 62E20
MSC: 62G07
idZBL: Zbl 07511574
idMR: MR4405817
DOI: 10.14712/1213-7243.2022.003
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Date available: 2022-02-21T13:28:25Z
Last updated: 2024-01-01
Stable URL: http://hdl.handle.net/10338.dmlcz/149370
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Reference: [1] Bosq D.: Vitesses optimales et superoptimales des estimateurs fonctionnels pour les processus à temps continu.C. R. Acad. Sci. Paris Sér. I Math. 317 (1993), no. 11, 1075–1078 (French). MR 1249792
Reference: [2] Bosq D.: Nonparametric Statistics for Stochastic Processes.Estimation and Prediction, Lecture Notes in Statistics, 110, Springer, New York, 1998. MR 1640691, 10.1007/978-1-4612-1718-3
Reference: [3] Bosq D.: Linear Processes in Function Spaces.Theory and Applications, Lecture Notes in Statistics, 149, Springer, New York, 2000. MR 1783138, 10.1007/978-1-4612-1154-9_8
Reference: [4] Bradley R. C.: Basic properties of strong mixing conditions. A survey and some open questions.Probab. Surv. 2 (2005), 107–144. MR 2178042, 10.1214/154957805100000104
Reference: [5] Cardot H., Ferraty F., Sarda P.: Functional linear model.Statist. Probab. Lett. 45 (1999), no. 1, 11–22. MR 1718346, 10.1016/S0167-7152(99)00036-X
Reference: [6] Cardot H., Ferraty F., Sarda P.: Spline estimators for the functional linear model.Statist. Sinica 13 (2003), no. 3, 571–591. MR 1997162
Reference: [7] Castellana J. V., Leadbetter M. R.: On smoothed probability density estimation for stationary processes.Stochastic Process. Appl. 21 (1986), no. 2, 179–193. MR 0833950
Reference: [8] Collomb G., Härdle W.: Strong uniform convergence rates in robust nonparametric time series analysis and prediction: kernel regression estimation from dependent observations.Stochastic Process. Appl. 23 (1986), no. 1, 77–89. MR 0866288
Reference: [9] Dabo-Niang S.: Density estimation in a separable metric space.Ann. I.S.U.P. 47 (2003), no. 1–2, 3–21. MR 2002884
Reference: [10] Dabo-Niang S.: Density estimation by orthogonal series in an infinite dimensional space: application to processes of diffusion type I.The International Conf. on Recent Trends and Directions in Nonparametric Statistics, J. Nonparametr. Stat. 16 (2004), no. 1–2, 171–186. MR 2053068, 10.1080/10485250310001624837
Reference: [11] Demongeot J., Laksaci A., Madani F., Rachdi M.: A fast functional locally modeled conditional density and mode for functional time-series.Recent Advances in Functional Data Analysis and Related Topics, Contrib. Statist., Physica Verlag, Springer, Heidelberg, 2011, 85–90. MR 2815565
Reference: [12] Ferraty F., Goia A., Vieu P.: Functional nonparametric model for time series: a fractal approach for dimension reduction.Test 11 (2002), no. 2, 317–344. MR 1947601, 10.1007/BF02595710
Reference: [13] Ferraty F., Laksaci A., Tadj A., Vieu P.: Kernel regression with functional response.Electron. J. Stat. 5 (2011), 159–171. MR 2786486, 10.1214/11-EJS600
Reference: [14] Ferraty F., Rabhi A., Vieu P: Conditional quantiles for dependent functional data with application to the climatic El Niño phenomenon.Sankhyā 67 (2005), no. 2, 378–398. MR 2208895
Reference: [15] Ferraty F., Vieu P.: Nonparametric models for functional data, with application in regression, time-series prediction and curve discrimination.The International Conf. on Recent Trends and Directions in Nonparametric Statistics, J. Nonparametr. Stat. 16 (2004), no. 1–2, 111–125. MR 2053065, 10.1080/10485250310001622686
Reference: [16] Ferraty F., Vieu P.: Nonparametric Functional Data Analysis.Theory and Practice, Springer Series in Statistics, Springer, New York, 2006. MR 2229687
Reference: [17] Frank I. E., Friedman J. H.: A statistical view of some chemometric regression tools.Technometrics 35 (1993), no. 2, 109–135. 10.1080/00401706.1993.10485033
Reference: [18] Grunig R.: Probabilités conditionnelles régulières sur des tribus de type non dénombrable.Ann. Inst. H. Poincaré Sect. B (N.S.) 2 (1965/1966), no. 3, 227–229 (French). MR 0196799
Reference: [19] Jiřina M.: Conditional probabilities on strictly separable $\sigma$-algebras.Czechoslovak. Math. J. 4(79) (1954), 372–380. MR 0069416, 10.21136/CMJ.1954.100124
Reference: [20] Jiřina M.: On regular conditional probabilities.Czechoslovak. Math. J. 9(84) (1959), 445–451. MR 0115202, 10.21136/CMJ.1959.100368
Reference: [21] Krzy.zak A., Pawlak M.: The pointwise rate of convergence of the kernel regression estimate.J. Statist. Plann. Inference 16 (1987), no. 2, 159–166. MR 0895756, 10.1016/0378-3758(87)90065-6
Reference: [22] Masry E.: Nonparametric regression estimation for dependent functional data: asymptotic normality.Stochastic Process. Appl. 115 (2005), no. 1, 155–177. MR 2105373, 10.1016/j.spa.2004.07.006
Reference: [23] Ramsay J. O., Silverman B. W.: Functional Data Analysis.Springer Series in Statistics, Springer, New York, 2005. MR 2168993
Reference: [24] Rio E.: Théorie asymptotique des processus aléatoires faiblement dépendants.Mathématiques & Applications, 31, Springer, Berlin, 2000 (French). MR 2117923
Reference: [25] Rosenblatt M.: Conditional probability density and regression estimators.in Multivariate Analysis II, Proc. Second Internat. Sympos., Dayton, Ohio, 1968, Academic Press, New York, 1969, pages 25–31. MR 0254987
Reference: [26] Roussas G. G.: Nonparametric regression estimation under mixing conditions.Stochastic Process. Appl. 36 (1990), no. 1, 107–116. Zbl 0699.62038, MR 1075604, 10.1016/0304-4149(90)90045-T
Reference: [27] Stone C. J.: Optimal global rates of convergence for nonparametric regression.Ann. Statist. 10 (1982), no. 4, 1040–1053. MR 0673642, 10.1214/aos/1176345969
Reference: [28] Watson G. S.: Smooth regression analysis.Sankhyā Ser. A 26 (1964), 359–372. MR 0185765
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