Regression-Based, Regression-Free and Model-Free Approaches for Robust Online Scale Estimation

Regression-based, regression-free and model-free approaches for robust online scale estimation

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Regression-Free and Robust Estimation of Scale for Bivariate Data

In this paper we present robust estimators for the dispersion of the errors in simple linear regression. Existing scale estimators are based on the residuals from an estimator of the regression itself. Instead, we propose scale estimators that do not depend on any previous estimate of the regression parameters. For this purpose we consider triangles formed by data points, and deene their vertic...

www.econstor.eu Robust Online Scale Estimation in Time Series: A Regression-Free Approach

Model-Free and Model-Based Active Learning for Regression

Training machine learning models often requires large labelled datasets, which can be both expensive and time-consuming to obtain. Active learning aims to selectively choose which data is labelled in order to minimize the total number of labels required to train an effective model. This paper compares model-free and model-based approaches to active learning for regression, finding that model-fr...

Shrinkage Inverse Regression Estimation for Model Free Variable Selection

The family of inverse regression estimators recently proposed by Cook and Ni (2005) have proven effective in dimension reduction by transforming the highdimensional predictor vector to its low-dimensional projections. In this article, we propose a general shrinkage estimation strategy for the entire inverse regression estimation family that is capable of simultaneous dimension reduction and var...