Distributed debiased estimation of high-dimensional partially linear models with jumps

Yan‐Yong Zhao; Yuchun Zhang; Yuan Liu; Noriszura Ismail

doi:10.1016/j.csda.2023.107857

ScienceGate Book Chapters

JOURNAL ARTICLE

Distributed debiased estimation of high-dimensional partially linear models with jumps

Yan‐Yong Zhao Yuchun Zhang Yuan Liu Noriszura Ismail

Year: 2023 Journal: Computational Statistics & Data Analysis Vol: 191 Pages: 107857-107857 Publisher: Elsevier BV

DOI: 10.1016/j.csda.2023.107857

Get Full-Text PDF Get Analytical Report

Keywords:

Estimator Nonparametric statistics Mathematics Spline (mechanical) Nonparametric regression Lasso (programming language) Linear model Applied mathematics Mathematical optimization Algorithm Statistics Computer science

Metrics

Cited By

0.64

FWCI (Field Weighted Citation Impact)

Refs

0.65

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Financial Risk and Volatility Modeling

Social Sciences → Economics, Econometrics and Finance → Finance

Advanced Statistical Methods and Models

Physical Sciences → Mathematics → Statistics and Probability

Distributed debiased estimation of high-dimensional partially linear models with jumps

Metrics

Citation History

Topics

Related Documents

Heterogeneity-aware debiased machine learning for high-dimensional partially linear models

Distributed Partially Linear Additive Models With a High Dimensional Linear Part

Semi-profiled distributed estimation for high-dimensional partially linear model

Adaptive group bridge estimation for high-dimensional partially linear models

Estimation and inference of high-dimensional partially linear spatial autoregressive models with linear constraints