Estimation of the marginal location under a partially linear model with missing responses

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In this paper, we consider a semiparametric partially linear regression model where there are missing data in the response. We propose robust Fisher-consistent estimators for the regression parameter, for the regression function and for the marginal location parameter of the response variable. A rob...

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Detalles Bibliográficos
Autor principal: Bianco, A.
Otros Autores: Boente, G., González-Manteiga, W., Pérez-González, A.
Formato: Capítulo de libro
Lenguaje:Inglés
Publicado: 2010
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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030 |a CSDAD 
100 1 |a Bianco, A. 
245 1 0 |a Estimation of the marginal location under a partially linear model with missing responses 
260 |c 2010 
270 1 0 |m Boente, G.; Facultad de Ciencias Exactas y Naturales, Universidad de Buenos AiresArgentina; email: gboente@dm.uba.ar 
506 |2 openaire  |e Política editorial 
504 |a Aerts, M., Claeskens, G., Hens, N., Molenberghs, G., Local multiple imputation (2002) Biometrika, 89 (2), pp. 375-388 
504 |a Bianco, A., Boente, G., Robust estimators in semiparametric partly linear regression models (2004) J. Statist. Plann. Inference, 122, pp. 229-252 
504 |a Bianco, A., Boente, G., Robust estimators under a semiparametric partly linear autoregression model: Asymptotic behavior and bandwidth selection (2007) J. Time Ser. Anal., 28, pp. 274-306 
504 |a Bianco, A., Boente, G., González-Manteiga, W., Pérez-González, A., (2009) Estimation of the marginal location under a partially linear model with missing responses, , http://www.ic.fcen.uba.ar/preprints/biaboegonper.pdf, Available at 
504 |a Bianco, A., Boente, G., Martínez, E., Robust tests in semiparametric partly linear models (2006) Scandinavian J. Statist., 33, pp. 435-450 
504 |a Boente, G., González-Manteiga, W., Pérez-González, A., Robust nonparametric estimation with missing data (2009) J. Statist. Plann. Inference, 139, pp. 571-592 
504 |a Cantoni, E., Ronchetti, E., Resistant selection of the smoothing parameter for smoothing splines (2001) Statist. Comput., 11, pp. 141-146 
504 |a Chen, J., Fan, J., Li, K., Zhou, H., Local quasi-likelihood estimation with data missing at random (2006) Statist. Sinica, 16, pp. 1071-1100 
504 |a Chen, J., Shao, J., Nearest neighbor imputation for survey data (2000) J. Official Statist., 16, pp. 113-131 
504 |a Cheng, P.E., Nonparametric estimation of mean functionals with data missing at random (1994) J. Amer. Statist. Assoc., 89, pp. 81-87 
504 |a Chu, C.K., Cheng, P.E., Nonparametric regression estimation with missing data (1995) J. Statist. Plann. Inference, 48, pp. 85-99 
504 |a Croux, C., Haesbroeck, G., Implementing the Bianco and Yohai estimator for logistic regression (2003) Comput. Statist. Data Anal., 44, pp. 273-295 
504 |a Daniel, C., Wood, F., (1980) Fitting Equations to Data: Computer Analysis of Multifactor Data, , Wiley, New York 
504 |a González-Manteiga, W., Aneiros-Pérez, G., Testing in partial linear regression models with dependent errors (2003) J. Nonparametr. Stat., 15, pp. 93-111 
504 |a González-Manteiga, W., Pérez-González, A., Nonparametric mean estimation with missing data (2004) Comm. Statist. Theory Methods, 33, pp. 277-303 
504 |a He, X., Zhu, Z., Fung, W., Estimation in a semiparametric model for longitudinal data with unspecified dependence structure (2002) Biometrika, 89, pp. 579-590 
504 |a Huber, P., (1981) Robust Statistics, , Wiley, New York 
504 |a Maronna, R., Martin, D., Yohai, V., (2006) Robust Statistics: Theory and Methods, , Wiley, New York 
504 |a Meng, X.-L., Missing data: Dial M for ??? (2000) J. Amer. Statist. Assoc., 95 (452), pp. 1325-1330 
504 |a Neyman, J., Contribution to the theory of sampling human populations (1938) J. Amer. Statist. Assoc., 33, pp. 101-116 
504 |a Robins, J., Rotnitzky, A., Zhao, L.P., Estimation of regression coefficients when some regressors are not always observed (1994) J. Amer. Statist. Assoc., 89, pp. 846-866 
504 |a Scharfstein, D., Rotnitzky, A., Robins, J., Adjusting for nonignorable drop out in semiparametric nonresponse models (with discussion) (1999) J. Amer. Statist. Assoc., 94, pp. 1096-1146 
504 |a Wang, C., Wang, S., Gutierrez, R., Carroll, R., Local linear regression for generalized linear models with missing data (1998) Ann. Statist., 26, pp. 1028-1050 
504 |a Wang, C., Wang, S., Zhao, L.P., Ou, S.T., Weighted semiparametric estimation in regression analysis regression with missing covariates data (1997) J. Amer. Statist. Assoc., 92, pp. 512-525 
504 |a Wang, F., Scott, D., The L1 method for robust nonparametric regression (1994) J. Amer. Statist. Assoc., 89, pp. 65-76 
504 |a Wang, Q., Linton, O., Härdle, W., Semiparametric regression analysis with missing response at random (2004) J. Amer. Statist. Assoc., 99 (466), pp. 334-345 
504 |a Wang, Q., Sun, Z., Estimation in partially linear models with missing responses at random (2007) J. Multivariate Anal., 98, pp. 1470-1493 
504 |a Wang, W., Rao, J., Empirical likelihood-based inference under imputation for missing response data (2002) Ann. Statist., 30, pp. 896-924 
504 |a Yates, F., The analysis of replicated experiments when the field results are incomplete (1933) Emporium J. Exp. Agriculture, 1, pp. 129-142 
520 3 |a In this paper, we consider a semiparametric partially linear regression model where there are missing data in the response. We propose robust Fisher-consistent estimators for the regression parameter, for the regression function and for the marginal location parameter of the response variable. A robust cross-validation method is briefly discussed, although, from our numerical results, the marginal estimators seem not to be sensitive to the bandwidth parameter. Finally, a Monte Carlo study is carried out to compare the performance of the robust proposed estimators among themselves and also with the classical ones, for normal and contaminated samples, under different missing data models. An example based on a real data set is also discussed. © 2009 Elsevier B.V. All rights reserved.  |l eng 
593 |a Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Argentina 
593 |a CONICET, Argentina 
593 |a Universidad de Santiago de Compostela, Spain 
593 |a Universidad de Vigo, Spain 
690 1 0 |a BANDWIDTH PARAMETERS 
690 1 0 |a CONSISTENT ESTIMATORS 
690 1 0 |a CROSS-VALIDATION METHODS 
690 1 0 |a DATA SETS 
690 1 0 |a EXAMPLE BASED 
690 1 0 |a LINEAR REGRESSION MODELS 
690 1 0 |a LOCATION PARAMETERS 
690 1 0 |a MISSING DATA 
690 1 0 |a MISSING RESPONSE 
690 1 0 |a MONTE CARLO STUDY 
690 1 0 |a NUMERICAL RESULTS 
690 1 0 |a PARTIALLY LINEAR MODELS 
690 1 0 |a REGRESSION FUNCTION 
690 1 0 |a REGRESSION PARAMETERS 
690 1 0 |a SEMIPARAMETRIC 
690 1 0 |a LINEAR REGRESSION 
690 1 0 |a PARAMETER ESTIMATION 
700 1 |a Boente, G. 
700 1 |a González-Manteiga, W. 
700 1 |a Pérez-González, A. 
773 0 |d 2010  |g v. 54  |h pp. 546-564  |k n. 2  |p Comput. Stat. Data Anal.  |x 01679473  |w (AR-BaUEN)CENRE-4276  |t Computational Statistics and Data Analysis 
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856 4 0 |u https://doi.org/10.1016/j.csda.2009.09.028  |y DOI 
856 4 0 |u https://hdl.handle.net/20.500.12110/paper_01679473_v54_n2_p546_Bianco  |y Handle 
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