Explores limit theorems for various types of observational data.
The book is divided into 16 chapters, with the first ten including case studies to demonstrate real-world utility. Key Topics: Large Sample Techniques for Statistics (Springe...
A foundational course in calculus and mathematical statistics is required. Why It Matters Explores limit theorems for various types of observational
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 Why It Matters Large-sample techniques are essential because
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.