Determining the number of factors in approximate factor models by twice K-fold cross validation
type: Item
instance of: scholarly article
title: Determining the number of factors in approximate factor models by twice K-fold cross validation
zbMATH Open document ID: 1443.62163
author: Jie Wei
author: Hui Chen
published in: Economics Letters
publication date: 2020-07-07T00:00:00Z
Mathematics Subject Classification ID: 62H12
Mathematics Subject Classification ID: 62H25
Mathematics Subject Classification ID: 62D20
Mathematics Subject Classification ID: 62P20
zbMATH DE Number: 7218459
zbMATH Keywords: approximate factor models
zbMATH Keywords: K-fold cross validation
zbMATH Keywords: consistency
zbMATH Keywords: finite sample performance
MaRDI profile type: Publication
full work available at URL: j.econlet.2020.109149
OpenAlex ID: W3015301926
Wikidata QID: Q112880962
cites work: Determining the Number of Factors in Approximate Factor Models
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cites work: A Testing Procedure for Determining the Number of Factors in Approximate Factor Models With Large Datasets
cites work: Stability Selection
cites work: Eigenvalue ratio test for the number of factors
cites work: Linear Model Selection by Cross-Validation
cites work: Consistency of cross validation for comparing regression procedures
cites work: Cross-validation for selecting a model selection procedure
DOI: 10.1016/J.ECONLET.2020.109149
description: scientific article; zbMATH DE number 7218459