EconPapers    
Economics at your fingertips  
 

MLE with datasets from populations having shared parameters

Jun Shao and Xinyan Wang

Statistical Theory and Related Fields, 2023, vol. 7, issue 3, 213-222

Abstract: We consider maximum likelihood estimation with two or more datasets sampled from different populations with shared parameters. Although more datasets with shared parameters can increase statistical accuracy, this paper shows how to handle heterogeneity among different populations for correctness of estimation and inference. Asymptotic distributions of maximum likelihood estimators are derived under either regular cases where regularity conditions are satisfied or some non-regular situations. A bootstrap variance estimator for assessing performance of estimators and/or making large sample inference is also introduced and evaluated in a simulation study.

Date: 2023
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/24754269.2023.2180185 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tstfxx:v:7:y:2023:i:3:p:213-222

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tstf20

DOI: 10.1080/24754269.2023.2180185

Access Statistics for this article

Statistical Theory and Related Fields is currently edited by Zhao Wei

More articles in Statistical Theory and Related Fields from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tstfxx:v:7:y:2023:i:3:p:213-222