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Statistical Properties of the log-cosh Loss Function Used in Machine Learning
In this paper, we present the distribution function from which the log-cosh loss arises.
Solution to the Non-Monotonicity and Crossing Problems in Quantile Regression
From this perspective, we also utilize the flexible check function to provide insights into the root causes of the crossing problem.
Penalty, Shrinkage, and Preliminary Test Estimators under Full Model Hypothesis
This paper considers a multiple regression model and compares, under full model hypothesis, analytically as well as by simulation, the performance characteristics of some popular penalty estimators such as ridge regression, LASSO, adaptive LASSO, SCAD, and elastic net versus Least Squares Estimator, restricted estimator, preliminary test estimator, and Stein-type estimators when the dimension of the parameter space is smaller than the sample space dimension.
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