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Biased Sampling, Over-identified Parameter Problems and Beyond

Jing Qin

978-981-10-4856-2

2017
Edition 1
- Provides a comprehensive overview of traditional statistical methods such as likelihood based inference and estimating function theory
- Extensively discusses many different biased sampling problems
- Explicitly addresses the connections between Godambe’s estimating function theory, Hansen’s generalized method of moments, and Qin and Lawless’ empirical likelihood approach for over-identified parameter problems
- Makes the general theory of biased sampling accessible to upper undergraduate and graduate students
- Includes supplementary material: sn.pub/extras
- Includes supplementary material: sn.pub/extras
€340 €306
10% OFF

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