Robust kernel estimators for additive models with dependent observations

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Robust nonparametric estimators for additive regression or autoregression models under an α-mixing condition are proposed. They are based on local M-estimators or local medians with kernel weights, and their asymptotic behaviour is studied. Moreover, these local M-estimators achieve the same univari...

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Detalles Bibliográficos
Autor principal: Bianco, A.
Otros Autores: Boente, G.
Formato: Capítulo de libro
Lenguaje:Inglés
Publicado: Statistical Society of Canada 1998
Acceso en línea:Registro en Scopus
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Biblioteca Central Dr. Luis F. Leloir (FCEN) de Universidad de Buenos Aires
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100 1 |a Bianco, A. 
245 1 0 |a Robust kernel estimators for additive models with dependent observations 
260 |b Statistical Society of Canada  |c 1998 
270 1 0 |m Bianco, A.; Instituto de Cálculo, Fac. Ciencias Exactas y Nat., Pabellón No. 2, Buenos Aires, 1428, Argentina; email: abianco@mate.dm.uba.ar 
506 |2 openaire  |e Política editorial 
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504 |a Bianco, A.M., Boente, G., (1993) Robust Nonparametric Generalized Regression Estimation, , Unpublished manuscript 
504 |a Boente, G., Fraiman, R., Robust nonparametric regression estimation for dependent observations (1989) Ann. Statist., 17, pp. 1242-1256 
504 |a Boente, G., Fraiman, R., Asymptotic distribution of robust estimators for nonparametric models from mixing processes (1990) Ann. Statist., 18, pp. 891-906 
504 |a Boente, G., Fraiman, R., Asymptotic distribution of smoothers based on local means and local medians under dependence (1995) J. Multivariate Anal., 53, pp. 77-90 
504 |a Boente, G., Fraiman, R., Meloche, J., Robust plug-in bandwidth estimators in nonparametric regression (1997) J. Statist. Plann. Inference, 57, pp. 109-142 
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504 |a Györfi, L., Masry, E., The L1 and L2 strong consistency of recursive kernel density estimation from dependent samples (1990) IEEE Trans. Inform. Theory, 36, pp. 531-539 
504 |a Hall, P., Lahiri, S.N., Truong, Y.K., On bandwidth choice for density estimation with dependent data (1995) Ann. Statist., 23, pp. 2241-2263 
504 |a Härdle, W., Applied nonparametric regression (1990) Econometric Soc. Monogr., p. 19. , Cambridge Univ. Press, Cambridge 
504 |a Härdle, W., Tsybakov, A.B., (1990) How Many Terms Should Be Added into an Additive Model?, , Core Discussion paper N9068, Center for Operations Research & Econometrics, Université Catholique de Louvain, Louvain-la-Neuve, Belgium 
504 |a Härdle, W., Tsybakov, A.B., Additive nonparametric regression in principal components (1995) J. Nonparametric Statist., 5, pp. 157-184 
504 |a Härdle, W., Vieu, P., Kernel regression smoothing of time series (1992) J. Time Ser. Anal., 13, pp. 209-232 
504 |a Hart, J.D., Some automated methods of smoothing time-dependent data (1996) J. Nonparametric Statist., 6, pp. 115-142 
504 |a Hart, J.D., Vieu, P., Data-driven bandwidth choice for density estimation based on dependent data (1990) Ann. Statist., 18, pp. 873-890 
504 |a Hart, J.D., Wehrly, T.E., Kernel regression estimation using repeated measurements data (1986) J. Amer. Statist. Assoc., 81, pp. 1080-1088 
504 |a Hastie, T.J., Tibshirani, R.J., Generalized additive models (1990) Monogr. Statist. Appl. Probab., p. 43. , Chapman and Hall, London 
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504 |a Robinson, P.M., Nonparametric estimators for time series (1983) J. Time Ser. Anal., 4, pp. 185-206 
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504 |a Roussas, G., Nonparametric regression estimation under mixing conditions (1990) J. Time Ser. Anal., 4, pp. 85-208 
504 |a Stone, C.J., Additive regression and other nonparametric models (1985) Ann. Statist., 13, pp. 689-705 
504 |a Stone, C.J., The dimensionality reduction principle for generalized additive models (1986) Ann. Statist., 14, pp. 590-606 
504 |a Tran, L., Nonparametric function estimation for time series by local average estimators (1993) Ann. Statist., 21, pp. 1040-1057 
504 |a Truong, Y., Robust nonparametric regression in time series (1992) J. Multivariate Anal., 41, pp. 163-177 
504 |a Truong, Y., Stone, C., Nonparametric function estimation involving time series (1992) Ann. Statist., 20, pp. 77-97 
504 |a Truong, Y., Stone, C., Semiparametric time series regression (1994) J. Time Ser. Anal., 15, pp. 405-428 
504 |a Wang, F., Scott, D., The L1 method for robust nonparametric regression (1994) J. Amer. Statist. Assoc., 89, pp. 65-76 
504 |a Yakowitz, S., Nonparametric density estimation, prediction and regression for Markov sequences (1985) J. Amer. Statist. Assoc., 80, pp. 215-221 
504 |a Yakowitz, S., Nonparametric density and regression estimation for Markov sequences without mixing assumptions (1989) J. Multivariate Anal., 30, pp. 124-136 
520 3 |a Robust nonparametric estimators for additive regression or autoregression models under an α-mixing condition are proposed. They are based on local M-estimators or local medians with kernel weights, and their asymptotic behaviour is studied. Moreover, these local M-estimators achieve the same univariate rate of convergence as their linear relatives.  |l eng 
593 |a Instituto de Cálculo, Fac. Ciencias Exactas y Nat., Pabellón No. 2, Buenos Aires, 1428, Argentina 
593 |a Departamento de Matemáticas, Fac. Ciencias Exactas y Nat., Pabellón No. 1, Buenos Aires, 1428, Argentina 
690 1 0 |a ADDITIVE MODEL 
690 1 0 |a KERNEL ESTIMATION 
690 1 0 |a NONPARAMETRIC REGRESSION 
690 1 0 |a ROBUST ESTIMATION 
690 1 0 |a Α-MIXING CONDITIONS 
700 1 |a Boente, G. 
773 0 |d Statistical Society of Canada, 1998  |g v. 26  |h pp. 239-255  |k n. 2  |p Can. J. Stat.  |x 03195724  |t Canadian Journal of Statistics 
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856 4 0 |u https://doi.org/10.2307/3315508  |y DOI 
856 4 0 |u https://hdl.handle.net/20.500.12110/paper_03195724_v26_n2_p239_Bianco  |y Handle 
856 4 0 |u https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_03195724_v26_n2_p239_Bianco  |y Registro en la Biblioteca Digital 
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962 |a info:eu-repo/semantics/article  |a info:ar-repo/semantics/artículo  |b info:eu-repo/semantics/publishedVersion 
999 |c 63880 

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