Modal regression based robust empirical likelihood and variable selection for partial linear models with longitudinal data

Xiaofei Sun; Kangning Wang; Shaomin Li; Lin Lu

doi:10.1360/ssm-2019-0230

ScienceGate Book Chapters

JOURNAL ARTICLE

Modal regression based robust empirical likelihood and variable selection for partial linear models with longitudinal data

Xiaofei Sun Kangning Wang Shaomin Li Lin Lu

Year: 2020 Journal: Scientia Sinica Mathematica Vol: 52 (4)Pages: 447-447 Publisher: Science China Press

DOI: 10.1360/ssm-2019-0230

Get Full-Text PDF Get Analytical Report

Keywords:

Linear regression Statistics Feature selection Longitudinal data Econometrics Regression analysis Mathematics Modal Regression Computer science Data mining Artificial intelligence

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.24

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Modal regression based robust empirical likelihood and variable selection for partial linear models with longitudinal data

Metrics

Citation History

Topics

Related Documents

Robust empirical likelihood inference for generalized partial linear models with longitudinal data

Modal regression statistical inference for longitudinal data semivarying coefficient models: Generalized estimating equations, empirical likelihood and variable selection

Variable selection in robust regression models for longitudinal data

Empirical Likelihood Diagnosis of Modal Linear Regression Models

Penalized Empirical Likelihood based Variable Selection for Partially Linear Quantile Regression Models with Missing Responses