Results 101 to 110 of about 4,362,963 (201)

Robust Forecasting of Non-Stationary Time Series [PDF]

This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency.
Mahieu, K., Gijbels, I., Fried, R., Croux, C.   +3 more
core  

Efficient Robust Estimation of Regression Models (Revision of DP 2006-08) [PDF]

This paper introduces a new class of robust regression estimators. The proposed twostep least weighted squares (2S-LWS) estimator employs data-adaptive weights determined from the empirical distribution, quantile, or density functions of regression ...
Cizek, P.
core  

Regression depth and support vector machine [PDF]

The regression depth method (RDM) proposed by Rousseeuw and Hubert [RH99] plays an important role in the area of robust regression for a continuous response variable.
Christmann, Andreas
core  

A review of robust regression in biomedical science research. [PDF]

Arch Med Sci, 2020
Varin S, Panagiotakos DB.
europepmc   +1 more source

General Trimmed Estimation: Robust Approach to Nonlinear and Limited Dependent Variable Models (Replaces DP 2007-1) [PDF]

High breakdown-point regression estimators protect against large errors and data con- tamination. We generalize the concept of trimming used by many of these robust estima- tors, such as the least trimmed squares and maximum trimmed likelihood, and ...
Cizek, P.
core  

Robust Regression with Density Power Divergence: Theory, Comparisons, and Data Analysis. [PDF]

Entropy (Basel), 2020
Riani M, Atkinson AC, Corbellini A, Perrotta D.   +3 more
europepmc   +1 more source

Scalable and robust regression models for continuous proportional data. [PDF]

J Am Stat Assoc
Lee CJ, Dahl BK, Ovaskainen O, Dunson DB.   +3 more
europepmc   +1 more source

Robust Estimators are Hard to Compute [PDF]

In modern statistics, the robust estimation of parameters of a regression hyperplane is a central problem. Robustness means that the estimation is not or only slightly affected by outliers in the data. In this paper, it is shown that the following robust
Bernholt, Thorsten
core  

Novel class of population mean estimators based on robust regression methods. [PDF]

Sci Rep
Kumar A, Kumari R, Alomair AM, Alomair MA.   +3 more
europepmc   +1 more source

Use of robust regression methods to detect outliers and estimate parameters for Length-Weight relationships in fishes. [PDF]

Sci Rep
Orenti A, Neat FC, Zolin A, Marubini E, Cesana BM.   +4 more
europepmc   +1 more source