Zobrazeno 1 - 10
of 147
pro vyhledávání: '"Saleh, A. K. Md. Ehsanes"'
This paper analyzes a popular loss function used in machine learning called the log-cosh loss function. A number of papers have been published using this loss function but, to date, no statistical analysis has been presented in the literature. In thi
Externí odkaz:
http://arxiv.org/abs/2208.04564
This paper proposes a new method to address the long-standing problem of lack of monotonicity in estimation of the conditional and structural quantile function, also known as quantile crossing problem. Quantile regression is a very powerful tool in d
Externí odkaz:
http://arxiv.org/abs/2111.04805
In the context of multiple regression model, suppose that the vector parameter of interest \beta is subjected to lie in the subspace hypothesis H\beta = h, where this restriction is based on either additional information or prior knowledge. Then, the
Externí odkaz:
http://arxiv.org/abs/1505.02913
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, SCA
Externí odkaz:
http://arxiv.org/abs/1503.06910
We propose an improved LASSO estimation technique based on Stein-rule. We shrink classical LASSO estimator using preliminary test, shrinkage, and positive-rule shrinkage principle. Simulation results have been carried out for various configurations o
Externí odkaz:
http://arxiv.org/abs/1503.05160
Publikováno v:
The Canadian Journal of Statistics / La Revue Canadienne de Statistique, 2018 Dec 01. 46(4), 690-704.
Externí odkaz:
https://www.jstor.org/stable/48744754
