EconPapers    
Economics at your fingertips  
 

Independent Additive Weighted Bias Distributions and Associated Goodness-of-Fit Tests

Bruno Ebner () and Yvik Swan ()
Additional contact information
Bruno Ebner: Karlsruhe Institute of Technology (KIT), Institute of Stochastics
Yvik Swan: Université libre de Bruxelles, Département de Mathématique

A chapter in Recent Advances in Econometrics and Statistics, 2024, pp 511-532 from Springer

Abstract: Abstract We use a Stein identity to define a new class of distributions which we call “independent additive weighted bias distributions.” We investigate related L 2 $$L^2$$ -type discrepancy measures, empirical versions of which not only encompass traditional ODE-based procedures but also offer novel methods for conducting goodness-of-fit tests in composite hypothesis testing problems. We determine critical values for these new procedures using a parametric bootstrap approach and evaluate their power through Monte Carlo simulations. As an illustration, we apply these procedures to examine the compatibility of two real datasets with a compound Poisson gamma distribution.

Date: 2024
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:spr:sprchp:978-3-031-61853-6_26

Ordering information: This item can be ordered from
http://www.springer.com/9783031618536

DOI: 10.1007/978-3-031-61853-6_26

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-06-01
Handle: RePEc:spr:sprchp:978-3-031-61853-6_26