Robust inference in partially linear models with missing responses

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We consider robust testing on the regression parameter of a partially linear regression model, where missing responses are allowed. We derive the asymptotic behavior of the proposed test statistic under the null and contiguous alternatives. A numerical study is performed. © 2014 Elsevier B.V.

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Detalles Bibliográficos
Autor principal: Bianco, A.M
Otros Autores: Boente, G., González-Manteiga, W., Pérez-González, A.
Formato: Capítulo de libro
Lenguaje:Inglés
Publicado: Elsevier 2015
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.M. 
245 1 0 |a Robust inference in partially linear models with missing responses 
260 |b Elsevier  |c 2015 
270 1 0 |m Bianco, A.M.; Instituto de Cálculo, FCEyN, UBA, Ciudad Universitaria, Pabellón 2, Argentina 
506 |2 openaire  |e Política editorial 
504 |a Bhattacharya, P.K., Zhao, P.L., Semiparametric inference in a partial linear model (1997) Ann. Statist., 25, pp. 244-262 
504 |a Bianco, A., Boente, G., On the asymptotic behavior of one-step estimates in heteroscedastic regression models (2002) Statist. Probab. Lett., 60, pp. 33-47 
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., González-Manteiga, W., Pérez-González, A., Estimation of the marginal location under a partially linear model with missing responses (2010) Comput. Statist. Data Anal., 54, pp. 546-564 
504 |a Bianco, A., Boente, G., González-Manteiga, W., Pérez-González, A., Asymptotic behavior of robust estimators in partially linear models with missing responses: The effect of estimating the missing probability on the simplified marginal estimators (2011) TEST, 20, pp. 524-548 
504 |a Bianco, A., Boente, G., Martínez, E., Robust tests in semiparametric partly linear models (2006) Scand. 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 Gao, J., Adaptive parametric test in a semiparametric regression model (1997) Comm. Statist. Theory Methods, 26, pp. 787-800 
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., Crujeiras, R., An updated review of goodness-of-fit tests for regression models (2013) TEST, 22, pp. 361-447 
504 |a Härdle, W., Liang, H., Gao, J., (2000) Partially Linear Models, , Springer-Verlag 
504 |a Härdle, W., Müller, M., Sperlich, S., Werwatz, A., (2004) Nonparametric and Semiparametric Models, , Springer 
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 Koul, H.L., Müller, U., Schick, A., The transfer principle: a tool for complete case analysis (2012) Ann. Statist., 40, pp. 3031-3049 
504 |a Maronna, R., Martin, D., Yohai, V., (2006) Robust Statistics: Theory and Methods, , Wiley, New York 
504 |a Robinson, P., Root-n-consistent semiparametric regression (1988) Econometrica, 56, pp. 931-954 
504 |a Severini, T., Staniswalis, J., Quasi-likelihood estimation in semiparametric models (1994) J. Amer. Statist. Assoc., 89, pp. 501-511 
504 |a Speckman, P., Kernel smoothing in partial linear models (1988) J. R. Stat. Soc. Ser. B, 50, pp. 413-436 
504 |a Sperlich, S., On the choice of regularization parameters in specification testing: a critical discussion (2014) Empir. Econom., 47, pp. 427-450 
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 
520 3 |a We consider robust testing on the regression parameter of a partially linear regression model, where missing responses are allowed. We derive the asymptotic behavior of the proposed test statistic under the null and contiguous alternatives. A numerical study is performed. © 2014 Elsevier B.V.  |l eng 
593 |a Instituto de Cálculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 2, Buenos Aires, 1428, Argentina 
593 |a CONICET, Av. Rivadavia 1917, Buenos Aires, 1429, Argentina 
593 |a Departamento de Matemáticas, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, Pabellón 1, Buenos Aires, 1428, Argentina 
593 |a IMAS, CONICET, Ciudad Universitaria, Pabellón 1, Buenos Aires, 1428, Argentina 
593 |a Departamento de Estatística e Investigación Operativa, Facultad de Matemáticas, Universidad de Santiago de Compostela, Santiago de Compostela, 15782, Spain 
593 |a Departamento de Estadística e Investigación Operativa, Facultad de Empresariales y Turismo, Universidad de Vigo, Campus de Orense, Orense, 32004, Spain 
690 1 0 |a HYPOTHESIS TESTING 
690 1 0 |a KERNEL WEIGHTS 
690 1 0 |a M-LOCATION FUNCTIONALS 
690 1 0 |a MISSING AT RANDOM 
690 1 0 |a PARTLY LINEAR MODELS 
690 1 0 |a ROBUST ESTIMATION 
700 1 |a Boente, G. 
700 1 |a González-Manteiga, W. 
700 1 |a Pérez-González, A. 
773 0 |d Elsevier, 2015  |g v. 97  |h pp. 88-98  |p Stat. Probab. Lett.  |x 01677152  |w (AR-BaUEN)CENRE-6916  |t Statistics and Probability Letters 
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856 4 0 |u https://doi.org/10.1016/j.spl.2014.11.004  |y DOI 
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