Regression analysis constitutes an important tool for investigating the effect of explanatory
variables on response variables. When outliers and bias errors are present, the weighted …

Radio frequency interference (RFI) mitigation for pulsar signals is a long perplexing issue in
astrophysical measurements. Linear mitigation methods are often criticized for limited RFI …

The OLS model is built on the assumption of normality in the distribution of error terms.
However, this assumption can be easily violated, especially when there are outliers in the …

To yield well-suited image segmentation results, conventional clustering algorithms depend
on customized hand-crafted features as well as an appropriate initialization process. This …

This paper provides an analysis of the combining effect of novel activation function and loss
function based on M‐estimation in application to extreme learning machine (ELM), a feed …

In this article, a new robust ratio type estimator using the Uk's redescending M-estimator is
proposed for the estimation of the finite population mean in the simple random sampling …

In real-life situations, we have to analyze the data that contains the atypical observations,
and the presence of outliers has adverse effects on the performance of ordinary least square …

Removal of salt and pepper noise has been one of the most interesting researches in the
field of image preprocessing tasks; it has two simultaneous stringent demands: the …

The methods of two‐parameter ridge and ordinary ridge regression are very sensitive to the
presence of the joint problem of multicollinearity and outliers in the y‐direction. To overcome …

In the linear regression problem, redescending M-estimators are used as an alternative
method to the ordinary least square method when there are outliers in the data. Using the …