The Complete Guide to Statistical Theory, Simulation and Probability

A Bridge to the Future Volume 1

Anirban Dasgupta (Autor)

Buch | Hardcover

810 Seiten

2026
Springer-Verlag New York Inc.
978-1-0716-5181-0 (ISBN)

Noch nicht erschienen - erscheint am 04.03.2026
Versandkostenfrei
Auch auf Rechnung

Artikel merken

This book is a unique compendium of core topics in the Statistics Ph.D. program, as well as covering the latest statistical theory, graduate probability and simulation techniques. The Complete Guide to Statistical Theory, Simulation and Probability: A Bridge to the Future gives an elaborate treatment of standard statistics topics such as parametric inference, basic theory of linear models, large sample theory, as well as more advanced topics such as robust estimation, density estimation, bootstrap, multiple testing, and the latest breakthrough developments such as the LASSO and thresholding and regularization. It also gives self-contained treatments of standard graduate probability and major Monte Carlo techniques, including MCMC. As such, this book can be used as an all-purpose text in the statistics Ph.D. programs, as well as a unique research reference.

The book provides 918 exercises, and an additional 98 exercises at the end of the book. The book also has a complete and comprehensive synopsis of real analysis, calculus, linear algebra and matrix theory as an invaluable source of consultation for students, instructors, and researchers.

Anirban DasGupta is Professor of Statistics, at Purdue University. He is currently a member of the IMS Memorial Committee and is the current Chief Editor of The IMS Student Problem Corner. He has been an Editor of the Annals of Statistics, Journal of American Statistical Association, Bernoulli, Sankhya, Journal of Statistical Planning and Inference, Statistics Surveys, International Statistics Review, the IMS Lecture Notes and Monographs Series and Metrika. He is a Fellow of the Institute of Mathematical Statistics and has published over 120 research articles, monographs, and books.

Preface.- Chapter 1 Graduate Probability.- Chapter 2 Writing Models for Data.- Chapter 3 Exponential Families as a Unifier in Inference.- Chapter 4 The Problems of Inference: A Nontechnical First Glimpse.- Chapter 5 Decision Theory: Basic Concepts.- Chapter 6 Decision Theory: Basic Concepts.- Chapter 7 Bayes, Empirical Bayes and Shrinkage Estimates.- Chapter 8 Testing of Hypotheses and Confidence Regions.- Chapter 9 Asymptotic Approximations and Practical Asymptotic Tools.- Chapter 10 Least Squares Theory and Linear Models.- Chapter 11 Chi-square Tests.- Chapter 12 Empirical Processes and the Kolmogorov-Smirnov Tests.- Chapter 13 Density Estimation.- Chapter 14 Robust Estimates.- Chapter 15 Bootstrap, Jackknife and Permutation Tests.- Chapter 16 Simulation and the EM Algorithm.- Chapter 17 Markov Chain Monte Carlo.- Chapter 18 Epilogue: Metamorphosis of Statistics?.- Chapter 19 Sample Midterms.- Chapter 20 Appendix.- Index.

Erscheint lt. Verlag	15.5.2026
Reihe/Serie	Springer Texts in Statistics
Zusatzinfo	10 Illustrations, color; 56 Illustrations, black and white
Verlagsort	New York
Sprache	englisch
Maße	210 x 279 mm
Themenwelt	Mathematik / Informatik ► Mathematik ► Computerprogramme / Computeralgebra
	Mathematik / Informatik ► Mathematik ► Statistik
	Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
Schlagworte	Data Analysis • Frequentist Modeling • Probability • Statistical Inference • stochastic models
ISBN-10	1-0716-5181-1 / 1071651811
ISBN-13	978-1-0716-5181-0 / 9781071651810
Zustand	Neuware