Identifiability Analysis Using Data Cloning

Identifiability Analysis Using Data Cloning

Lack of identifiability in statistical models may hinder unique inferential conclusions. Therefore, the search for parametric constraints that ensure identifiability is of utmost importance in statistics. However, for complex modeling strategies, even acquiring the knowledge that the model is unide...

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Bibliographic Details
Main Authors: José Augusto Sartori Junior, Márcia D’Elia Branco
Format: Article
Language:English
Published: Instituto Nacional de Estatística | Statistics Portugal 2024-02-01
Series:Revstat Statistical Journal
Subjects:
identifiability
data cloning
dynamic models
MCMC algorithms
Online Access:https://revstat.ine.pt/index.php/REVSTAT/article/view/457

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