Skew-normal median regression model with applications

Autor:	Xingyun Cao, Gege Wang, Liucang Wu
Rok vydání:	2020
Předmět:	History Statistics Skew Median regression Computer Science Applications Education Mathematics
Zdroj:	Journal of Physics: Conference Series. 1616:012079
ISSN:	1742-6596 1742-6588
Popis:	Skewed/asymmetrical data often appear in many research fields such as finance, economy, climate science, environmental science, engineering technology, social sciences and biomedicine. Little research has been carried out to establish median regression model to investigate the influence of some covariates on distributional characteristics. Since the median can capture the “medium” level of the skewed data, the main objective of this paper is to construct the median regression model for the analysis of skew-normal data. We develop an expectation-maximization (EM) algorithm facilitated by Newton-Raphson algorithm to estimate the regression coefficients and parameters. The proposed methods are evaluated by some Monte Carlo simulations and are illustrated by a real data analysis.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5d2b2b9e51464016d6f660daefd3501f https://doi.org/10.1088/1742-6596/1616/1/012079 Zobrazit plný text záznamu