GMM estimation and variable selection of partially linear additive spatial autoregressive model

Fang Lü; Guo‐Liang Tian; Jing Yang

doi:10.1007/s00362-023-01481-6

ScienceGate Book Chapters

JOURNAL ARTICLE

GMM estimation and variable selection of partially linear additive spatial autoregressive model

Fang Lü Guo‐Liang Tian Jing Yang

Year: 2023 Journal: Statistical Papers Vol: 65 (4)Pages: 2253-2288 Publisher: Springer Science+Business Media

DOI: 10.1007/s00362-023-01481-6

Get Full-Text PDF Get Analytical Report

Keywords:

Autoregressive model Generalized method of moments Smoothing STAR model Mathematics Model selection Computation Monte Carlo method Applied mathematics Algorithm Mathematical optimization Computer science Econometrics Statistics Time series Panel data Autoregressive integrated moving average

Metrics

Cited By

4.31

FWCI (Field Weighted Citation Impact)

Refs

0.94

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Spatial and Panel Data Analysis

Social Sciences → Economics, Econometrics and Finance → Economics and Econometrics

Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Statistical Methods and Bayesian Inference

Physical Sciences → Mathematics → Statistics and Probability

GMM estimation and variable selection of partially linear additive spatial autoregressive model

Metrics

Citation History

Topics

Related Documents

GMM estimation of partially linear additive spatial autoregressive model

Variable selection of partially linear varying coefficient spatial autoregressive model

Two-stage Walsh-average-based robust estimation and variable selection for partially linear additive spatial autoregressive models

Estimation in functional partially linear spatial autoregressive model

Orthogonality based penalized GMM estimation for variable selection in partially linear spatial autoregressive models