Robust Multiple Regression
As modern data analysis pushes the boundaries of classical statistics, it is timely to reexamine alternate approaches to dealing with outliers in multiple regression. As sample sizes and the number of predictors increase, interactive methodology becomes less effective. Likewise, with limited underst...
Main Authors: | David W. Scott, Zhipeng Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-01-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/23/1/88 |
Similar Items
-
Improving the Efficiency of Robust Estimators for the Generalized Linear Model
by: Alfio Marazzi
Published: (2021-02-01) -
R Package distrMod: S4 Classes and Methods for Probability Models
by: Matthias Kohl, et al.
Published: (2010-10-01) -
Commentary on S. Kumar and P. Chhaparwal, 2016. A robust unbiased dual to product estimator for population mean through Modified Maximum Likelihood in simple random sampling, Cogent Mathematics, 3:1168070
by: Evrim Oral, et al.
Published: (2019-01-01) -
Transmuted Generalized Gompertz distribution with application
by: Muhammad Shuaib Khan, et al.
Published: (2017-02-01) -
Estimation of the Parameters of a Bivariate Geometric Distribution
by: U.J. Dixit, et al.
Published: (2015-08-01)