Bootstrapping Not Independent and Not Identically Distributed Data

Bootstrapping Not Independent and Not Identically Distributed Data

Classical normal asymptotics could bring serious pitfalls in statistical inference, because some parameters appearing in the limit distributions are unknown and, moreover, complicated to estimated (from a theoretical as well as computational point of view). Due to this, plenty of stochastic approach...

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Bibliographic Details
Main Authors: Martin Hrba, Matúš Maciak, Barbora Peštová, Michal Pešta
Format: Article
Language:English
Published: MDPI AG 2022-12-01
Series:Mathematics
Subjects:
bootstrap
statistical inference
asymptotic normality
weakly dependent data
not identically distributed data
moving block bootstrap
Online Access:https://www.mdpi.com/2227-7390/10/24/4671

Internet

https://www.mdpi.com/2227-7390/10/24/4671

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