Theory and Methods of Statistics
(Sprache: Englisch)
Theory and Methods of Statistics covers essential topics for advanced graduate students and professional research statisticians. This comprehensive resource covers many important areas in one manageable volume, including core subjects such as probability...
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Theory and Methods of Statistics covers essential topics for advanced graduate students and professional research statisticians. This comprehensive resource covers many important areas in one manageable volume, including core subjects such as probability theory, mathematical statistics, and linear models, and various special topics, including nonparametrics, curve estimation, multivariate analysis, time series, and resampling. The book presents subjects such as "maximum likelihood and sufficiency," and is written with an intuitive, heuristic approach to build reader comprehension. It also includes many probability inequalities that are not only useful in the context of this text, but also as a resource for investigating convergence of statistical procedures. - Codifies foundational information in many core areas of statistics into a comprehensive and definitive resource
- Serves as an excellent text for select master's and PhD programs, as well as a professional reference
- Integrates numerous examples to illustrate advanced concepts
- Includes many probability inequalities useful for investigating convergence of statistical procedures
Inhaltsverzeichnis zu „Theory and Methods of Statistics “
1. Probability Theory 2. Some Common Probability Distributions 3. Infinite Sequence of Random Variables and Their Convergence Properties 4. Basic Concepts of Statistical Inference and a Decision Theoretic Approach 5. Point Estimation in Parametric Models 6. Hypotheses Testing in Parametric Models 7. Asymptotic Properties of Likelihood Based Methods 8. Ranks, Empirical Distribution Functions and Quantiles 9. Nonparametric Curve Estimation 10. Statistical Functionals 11. Inference in Linear Models 12. Multivariate Analysis 13. Resampling: Jackknife and Bootstrap 14. Time Series Appendix A. Some Results from Advanced Calculus B. Some Inequalities C. Stieltjes Integration D. Convergence in Law E. Contiguity F. Weak Convergence
Autoren-Porträt von P.K. Bhattacharya, Prabir Burman
P.K. Bhattacharya has more than 30 years of experience teaching a broad spectrum of undergraduate and graduate courses in Statistics at Indian Statistical Institute, the University of Arizona, the University of California, Davis, and as a visiting professor at the University of Minnesota and MIT. He has supervised PhD students and has done professional consulting. He has authored more than 40 scientific papers in various areas of Statistics in leading statistical journals and has served on the editorial boards of Annals of Statistics and Sankhya. Prabir Burman has more than 30 years of teaching experience at University of California, Davis, Rutgers University, and Singapore National University. He has taught a wide variety of courses in Statistics courses at undergraduate and graduate levels, and he supervises PhD students in Statistics. He has also performed professional consulting. The author of more than 40 scientific publications in statistics and scientific journals, he is currently on the editorial board of the Journal of Multivariate Analysis, Statistics and Probability Letters, and ISRN Journal of Probability and Statistics.
Bibliographische Angaben
- Autoren: P.K. Bhattacharya , Prabir Burman
- 2016, 544 Seiten, Maße: 19,1 x 23,5 cm, Kartoniert (TB), Englisch
- Verlag: Academic Press
- ISBN-10: 0128024402
- ISBN-13: 9780128024409
- Erscheinungsdatum: 01.06.2016
Sprache:
Englisch
Pressezitat
"There will always be a need for a small number of mathematical statisticians, and this book would be a viable choice for training those people...In addition to its use as a textbook, this volume would make a good reference on the theory behind many standard methods."--MAA Reviews
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