In this Note, we introduce an extension of the k-nearest neighbor estimator in continuous time, the -occupation time estimator, and we give sufficient conditions for its existence. Then, we show the almost sure convergence for α-mixing and bounded processes in two cases, the superoptimal case (when parametric rates are reached) and the optimal case (when i.i.d. rates of density estimation are reached).
Dans cette Note, nous introduisons une extension de l'estimateur des k-plus proches voisins en temps continu, l'estimateur du -temps d'occupation, puis nous donnons des conditions d'existence de cet estimateur. Nous établissons également la convergence presque sûre pour des processus bornés α-mélangeants dans deux cas, le cas suroptimal (où la vitesse paramétrique est atteinte) et le cas optimal (où la vitesse i.i.d. de l'estimation de la densité est atteinte).
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Boris Labrador 1
@article{CRMATH_2006__343_10_665_0, author = {Boris Labrador}, title = {Almost sure convergence of the $ {k}_{T}$-occupation time density estimator}, journal = {Comptes Rendus. Math\'ematique}, pages = {665--669}, publisher = {Elsevier}, volume = {343}, number = {10}, year = {2006}, doi = {10.1016/j.crma.2006.10.015}, language = {en}, }
Boris Labrador. Almost sure convergence of the $ {k}_{T}$-occupation time density estimator. Comptes Rendus. Mathématique, Volume 343 (2006) no. 10, pp. 665-669. doi : 10.1016/j.crma.2006.10.015. https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.1016/j.crma.2006.10.015/
[1] Strong order of convergence and asymptotic distribution of nearest neighbor density estimates from dependent observations, Sankhyā Ser. A, Volume 53 (1991) no. 2, pp. 194-205
[2] Nonparametric Statistics for Stochastic Processes. Estimation and Prediction, Lecture Notes in Statist., vol. 110, Springer-Verlag, New York, 1998
[3] On smoothed probability density estimation for stationary processes, Stochastic Process. Appl., Volume 21 (1986), pp. 179-193
[4] Convergence rates of nearest neighbor density estimates, Sci. Sinica Ser. A, Volume 25 (1982) no. 5, pp. 455-467
[5] Functional laws of the iterated logarithm for the increments of empirical and quantile processes, Ann. Probab., Volume 20 (1992) no. 3, pp. 1248-1287
[6] The strong uniform convergence of multivariate variable kernel estimates, Canad. J. Statist., Volume 14 (1986) no. 3, pp. 211-219
[7] The strong uniform consistency of nearest neighbor density estimates, Ann. Statist., Volume 5 (1977) no. 3, pp. 536-540
[8] Mixing. Properties and Examples, Lecture Notes in Statist., vol. 85, Springer-Verlag, New York, 1994
[9] E. Fix, J.L. Hodges Jr., Discriminatory analysis, nonparametric discrimination: consistency properties, Report No 4, project No 21-49-004, USAF School of Aviation Medicine, Randolph Field, TX
[10] Occupation densities, Ann. Probab., Volume 8 (1980) no. 1, pp. 1-67
[11] Statistical Inference for Ergodic Diffusion Processes, Springer Ser. Statist., Springer, 2003
[12] A nonparametric estimate of a multivariate density function, Ann. Math. Statist., Volume 36 (1965), pp. 1049-1051
[13] Rate of strong uniform convergence of k-NN density estimates, J. Statist. Plann. Inference, Volume 8 (1983) no. 2, pp. 185-192
[14] Uniform consistency of some estimates of a density function, Ann. Math. Statist., Volume 40 (1969), pp. 1499-1502
[15] Consistency properties of nearest neighbor density function estimators, Ann. Statist., Volume 5 (1977) no. 1, pp. 143-154
[16] The law of the iterated logarithm for the multivariate nearest neighbor density estimators, J. Multivariate Anal., Volume 53 (1995) no. 1, pp. 159-179
[17] S. Levallois, PhD Thesis, University of Montpellier II, 1998
[18] On multivariate variable-kernel density estimates for time series, Canad. J. Statist., Volume 19 (1991) no. 4, pp. 371-387
[19] Strong consistency of nonparametric estimate of a density function, IEEE Trans. Systems Man Cybernet., Volume 3 (1973), pp. 289-290
[20] Rates of strong uniform convergence of nearest neighbor density estimates on any compact set, Appl. Math. Mech., Volume 11 (1990) no. 4, pp. 385-393 (English ed.)
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