Large Sample Techniques For Statistics (springe... Here

Large-sample techniques are essential because they provide solutions for complex problems where exact distributions are intractable. As noted by Jiming Jiang in the preface, these techniques simplify and justify statistical solutions while guiding researchers toward better methods, though he warns that misuse can lead to serious errors, such as misinterpreting the asymptotic null distribution of a likelihood ratio test. Hardcover: ISBN 978-3-030-91694-7 Paperback: ISBN 978-3-030-91697-8 eBook: ISBN 978-3-030-91695-4

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Explores limit theorems for various types of observational data. Large Sample Techniques for Statistics (Springe...

It is designed for a broad academic range, from senior undergraduates to doctoral researchers.

The 2nd edition (2022) of this comprehensive guide bridges the gap between formal theory and practical application. Unlike many texts that focus solely on rigorous proofs, this book emphasizes developing analytical thinking skills and intuition for asymptotic arguments. Explores limit theorems for various types of observational

Reviews basic tools like epsilon-delta arguments, Taylor expansion, types of convergence, and inequalities.

The second edition includes a new chapter on random matrix theory and expanded sections on mixed effects models. Unlike many texts that focus solely on rigorous

This post provides an overview of , authored by Jiming Jiang and published as part of the Springer Texts in Statistics series. Book Overview