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Non-Standard Parametric Statistical Inference | Oxford Scholarship Online
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Non-Standard Parametric Statistical Inference

Russell Cheng

Abstract

This book discusses the fitting of parametric statistical models to data samples. Emphasis is placed on (i) how to recognize situations where the problem is non-standard, when parameter estimates behave unusually, and (ii) the use of parametric bootstrap resampling methods in analysing such problems. Simple and practical model building is an underlying theme. A frequentist viewpoint based on likelihood is adopted, for which there is a well-established and very practical theory. The standard situation is where certain widely applicable regularity conditions hold. However, there are many apparen ... More

Keywords: bootstrap, likelihood, parametric models, regularity conditions, resampling

Bibliographic Information

Print publication date: 2017 Print ISBN-13: 9780198505044
Published to Oxford Scholarship Online: September 2017 DOI:10.1093/oso/9780198505044.001.0001

Authors

Affiliations are at time of print publication.

Russell Cheng, author
University of Southampton