Zobrazeno 1 - 10
of 247
pro vyhledávání: '"Yohai, Victor"'
We propose a new class of robust and Fisher-consistent estimators for mixture models. These estimators can be used to construct robust model-based clustering procedures. We study in detail the case of multivariate normal mixtures and propose a proced
Externí odkaz:
http://arxiv.org/abs/2102.06851
Autor:
Maronna, Ricardo A., Yohai, Victor J.
Let F_{{\theta}} be a family of distributions with support on the set of nonnegative integers Z_0. In this paper we derive the M-estimators with smallest gross error sensitivity (GES). We start by defining the uniform median of a distribution F with
Externí odkaz:
http://arxiv.org/abs/1911.03982
K means is a popular non-parametric clustering procedure introduced by Steinhaus (1956) and further developed by MacQueen (1967). It is known, however, that K means does not perform well in the presence of outliers. Cuesta-Albertos et al (1997) intro
Externí odkaz:
http://arxiv.org/abs/1906.08198
Generalized Linear Models are routinely used in data analysis. The classical procedures for estimation are based on Maximum Likelihood and it is well known that the presence of outliers can have a large impact on this estimator. Robust procedures are
Externí odkaz:
http://arxiv.org/abs/1709.10261
We define one-sided dynamic principal components (ODPC) for time series as linear combinations of the present and past values of the series that minimize the reconstruction mean squared error. Previous definitions of dynamic principal components depe
Externí odkaz:
http://arxiv.org/abs/1708.04705
Doubly protected estimators are widely used for estimating the population mean of an outcome Y from a sample where the response is missing in some individuals. To compensate for the missing responses, a vector X of covariates is observed at each indi
Externí odkaz:
http://arxiv.org/abs/1707.01951
Highly robust and efficient estimators for the generalized linear model with a dispersion parameter are proposed. The estimators are based on three steps. In the first step the maximum rank correlation estimator is used to consistently estimate the s
Externí odkaz:
http://arxiv.org/abs/1703.09626
Publikováno v:
In International Journal of Forecasting October-December 2021 37(4):1498-1508
We consider the problem of multivariate location and scatter matrix estimation when the data contain cellwise and casewise outliers. Agostinelli et al. (2015) propose a two-step approach to deal with this problem: first, apply a univariate filter to
Externí odkaz:
http://arxiv.org/abs/1609.00402