Results 31 to 40 of about 287 (69)
Robust and efficient estimation of nonparametric generalized linear models. [PDF]
Test (Madr), 2023 Kalogridis I, Claeskens G, Van Aelst S.
europepmc +1 more source
Logistic discrimination using robust estimators: An influence function approach. [PDF]
Discrimination; Estimator; Influence function;
Croux, Christophe +2 more
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ROBUST KERNEL ESTIMATOR FOR DENSITIES OF UNKNOWN [PDF]
Results on nonparametric kernel estimators of density differ according to the assumed degree of density smoothness; it is often assumed that the density function is at least twice differentiable.
Victoria Zinde-Walsh, Yulia Kotlyarova
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Robust fitting of mixtures of GLMs by weighted likelihood. [PDF]
Adv Stat Anal, 2022 Greco L.
europepmc +1 more source
Nonparametric LAD Cointegrating Regression [PDF]
We deal with nonparametric estimation in a nonlinear cointegration model whose regressor and dependent variable can be contemporaneously correlated. The asymptotic properties of the Nadaraya-Watson estimator are already examined in the literature.
Toshio Honda
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High breakdown estimators for principal components: the projection-pursuit approach revisited. [PDF]
Li and Chen (J. Amer. Statist. Assoc. 80 (1985) 759) proposed a method for principal components using projection-pursuit techniques. In classical principal components one searches for directions with maximal variance, and their approach consists of ...
Croux, Christophe, Ruiz-Gazen, A
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A Microeconomic Explanation of the EPK Paradox [PDF]
Supported by several recent investigations the empirical pricing kernel paradox might be considered as a stylized fact. In Chabi-Yo et al. (2008) simulation studies have been presented which suggest that this paradox might be caused by regime switching ...
Rouslan Moro +2 more
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Robust Learning from Bites [PDF]
Many robust statistical procedures have two drawbacks. Firstly, they are computer-intensive such that they can hardly be used for massive data sets. Secondly, robust confidence intervals for the estimated parameters or robust predictions according to the
Christmann, Andreas
core
Influence function and efficiency of the minimum covariance determinant scatter matrix estimator. [PDF]
The minimum covariance determinant (MCD) scatter estimator is a highly robust estimator for the dispersion matrix of a multivariate, elliptically symmetric distribution. It is relatively fast to compute and intuitively appealing.
Croux, Christophe, Haesbroeck, G
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Robust Learning from Bites for Data Mining [PDF]
Some methods from statistical machine learning and from robust statistics have two drawbacks. Firstly, they are computer-intensive such that they can hardly be used for massive data sets, say with millions of data points.
Christmann, Andreas +2 more
core