Complete Guide to Statistical Theory, Simulation and Probability

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.