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Partial linear model is very flexible when the relation between the covariates and responses, either parametric and nonparametric. …

The ridge regression estimator is a commonly used procedure to deal with multicollinear data. This paper proposes an estimation …

The proportional hazard Cox regression models play a key role in analyzing censored survival data. We use penalized methods in high …

In this note, we show how to construct the well-known preliminary test estimator to be practical in the high dimensional linear …

A statistician may face with a dataset that suffers from multicollinearity and outliers, simultaneously. The Huberized ridge (HR) …

Suppose the regression vector-parameter is subjected to lie in a subspace hypothesis in a linear regression model. In situations where …

In the development of efficient predictive models, the key is to identify suitable predictors to establish a prediction model for a …

Due to the complicated mathematical and nonlinear nature of ridge regression estimator, Liu (Linear-Unified) estimator has been …

In this paper, we consider the estimation problem of the weighted least absolute deviation (WLAD) regression parameter vector when …