Asymptotic Statistical Inference (PDF)
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Numerous illustrative examples of differing difficulty level are incorporated to clarify the concepts. For better assimilation of the notions, various exercises are included in each chapter. Solutions to almost all the exercises are given in the last chapter, to motivate students towards solving these exercises and to enable digestion of the underlying concepts.
The concepts from asymptotic inference are crucial in modern statistics, but are difficult to grasp in view of their abstract nature. To overcome this difficulty, keeping up with the recent trend of using R software for statistical computations, the book uses it extensively, for illustrating the concepts, verifying the properties of estimators and carrying out various test procedures. The last section of the chapters presents R codes to reveal and visually demonstrate the hidden aspects of different concepts and procedures. Augmenting the theory with R software is a novel and a unique feature of the book.The book is designed primarily to serve as a text book for a one semester introductory course in asymptotic statistical inference, in a post-graduate program, such as Statistics, Bio-statistics or Econometrics. It will also provide sufficient background information for studying inference in stochastic processes. The book will cater to the need of a concise but clear and student-friendly book introducing, conceptually and computationally, basics of asymptotic inference.
Shailaja Deshmukh is a visiting faculty at the Department of Statistics, Savitribai Phule Pune University (formerly known as University of Pune). She was earlier a Professor of Statistics and also Head of the Department of Statistics, before her retirement from the university in November 2015 after thirty eight years of service. She has taught around twenty ¿ve di¿erent theoretical and applied courses. She worked as a visiting professor at the Department of Statistics, University of Michigan, Ann Arbor, Michigan during 2009-10 academic year. Her areas of interest are inference in stochastic processes, applied probability, actuarial statistics and analysis of microarray data. She has a number of research publications in various peer-reviewed journals, such as Biometrika, Communication in Statistics (Theory and Methods), Journal of Multivariate Analysis, J. R. Statist. Soc. Australian Journal of Statistics, Biometrical Journal, Statistics and Probability Letters, Journal of Applied Statistics, Australian and New
- Autoren: Shailaja Deshmukh , Madhuri Kulkarni
- 2021, 1st ed. 2021, 529 Seiten, Englisch
- Verlag: Springer Nature Singapore
- ISBN-10: 9811590036
- ISBN-13: 9789811590030
- Erscheinungsdatum: 05.07.2021
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