Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/247558 
Authors: 
Year of Publication: 
2020
Citation: 
[Journal:] Econometrics [ISSN:] 2225-1146 [Volume:] 8 [Issue:] 1 [Publisher:] MDPI [Place:] Basel [Year:] 2020 [Pages:] 1-11
Publisher: 
MDPI, Basel
Abstract: 
A factor model based covariance matrix is used to build a new form of Mahalanobis distance. The distribution and relative properties of the new Mahalanobis distances are derived. A new type of Mahalanobis distance based on the separated part of the factor model is defined. Contamination effects of outliers detected by the new defined Mahalanobis distances are also investigated. An empirical example indicates that the new proposed separated type of Mahalanobis distances predominate the original sample Mahalanobis distance.
Subjects: 
covariance matrix estimation
dimension reduction
multivariate analysis
outlier detection
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.