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  • Search: subject:"R-estimator"
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Year of publication
Subject
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R-estimator 8 M-estimator 4 Additive model 2 Kernel estimator 2 L-estimator 2 Marginal integration 2 Robustness 2 S-estimator 2 Tyler's M-estimator 2 Von-mises statistical functional generalized Delta-theorem 2 influence function 2 local asymptotic normality 2 nonparametric regression 2 robust covariance matrix estimator 2 robustness 2 scale-invariant function 2 shape matrix 2 Asymptotic relative efficiency 1 Autoregression quantile 1 Measurement error 1 Regression quantile 1 Regression rank scores 1 Two-step regression quantile 1
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Online availability
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Free 6 Undetermined 2
Type of publication
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Book / Working Paper 6 Article 2
Type of publication (narrower categories)
All
Working Paper 3
Language
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English 4 Undetermined 4
Author
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Tamine, Julien 4 Frahm, Gabriel 2 Härdle, Wolfgang 2 Picek, Jan 2 Yang, Lijian 2 Jurečková, Jana 1 Kalina, Jan 1 Saleh, A. 1
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Institution
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Sonderforschungsbereich 373, Quantifikation und Simulation ökonomischer Prozesse, Wirtschaftswissenschaftliche Fakultät 2 Seminar für Wirtschafts- und Sozialstatistik, Wirtschafts- und Sozialwissenschaftliche Fakultät 1
Published in...
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SFB 373 Discussion Paper 2 SFB 373 Discussion Papers 2 Discussion Papers in Econometrics and Statistics 1 Discussion Papers in Statistics and Econometrics 1 Metrika 1 Statistics & Probability Letters 1
Source
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RePEc 5 EconStor 3
Showing 1 - 8 of 8
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Asymptotic distributions of robust shape matrices and scales
Frahm, Gabriel - 2008
It has been frequently observed in the literature that many multivariate statistical methods require the covariance or dispersion matrix ∑ of an elliptical distribution only up to some scaling constant. If the topic of interest is not the scale but only the shape of the elliptical...
Persistent link: https://www.econbiz.de/10010304418
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Asymptotic distributions of robust shape matrices and scales
Frahm, Gabriel - Seminar für Wirtschafts- und Sozialstatistik, … - 2008
It has been frequently observed in the literature that many multivariate statistical methods require the covariance or dispersion matrix ∑ of an elliptical distribution only up to some scaling constant. If the topic of interest is not the scale but only the shape of the elliptical...
Persistent link: https://www.econbiz.de/10009019658
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R-estimation of the parameters of a multiple regression model with measurement errors
Saleh, A.; Picek, Jan; Kalina, Jan - In: Metrika 75 (2012) 3, pp. 311-328
Persistent link: https://www.econbiz.de/10010846094
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Regression quantiles and their two-step modifications
Jurečková, Jana; Picek, Jan - In: Statistics & Probability Letters 82 (2012) 6, pp. 1111-1115
Regression quantiles and their two-step modifications based on R-estimation of slope components of regression parameter are asymptotically equivalent and are very close numerically even for small sample sizes; their extreme versions even exactly coincide. Regarding that, we study their relations...
Persistent link: https://www.econbiz.de/10011040002
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R robustified additive nonparametric regression
Tamine, Julien; Härdle, Wolfgang; Yang, Lijian - 2002
Additive modelling is known to be useful for multivariate nonparametric regression as it reduces the complexity of problem to the level of univariate regression. This usefulness could be compromised if the data set was contaminated by outliers whose detection and removal are particularly...
Persistent link: https://www.econbiz.de/10010310510
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R robustified additive nonparametric regression
Tamine, Julien; Härdle, Wolfgang; Yang, Lijian - Sonderforschungsbereich 373, Quantifikation und … - 2002
Additive modelling is known to be useful for multivariate nonparametric regression as it reduces the complexity of problem to the level of univariate regression. This usefulness could be compromised if the data set was contaminated by outliers whose detection and removal are particularly...
Persistent link: https://www.econbiz.de/10010983510
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Smoothed influence function: Another view at robust nonparametric regression
Tamine, Julien - 2001
In this work, we introduce a smoothed influence function that constitute a theoretical tool for studying the outliers robustness properties of a large class of nonparametric estimators. With this tool, we first show the nonrobustness of the Nadaraya-Watson estimator of regression. Then we show...
Persistent link: https://www.econbiz.de/10010310591
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Smoothed influence function: Another view at robust nonparametric regression
Tamine, Julien - Sonderforschungsbereich 373, Quantifikation und … - 2001
In this work, we introduce a smoothed influence function that constitute a theoretical tool for studying the outliers robustness properties of a large class of nonparametric estimators. With this tool, we first show the nonrobustness of the Nadaraya-Watson estimator of regression. Then we show...
Persistent link: https://www.econbiz.de/10010956562
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