Preface
I Methods of Computational Statistics
Introduction to Part I
1 Preliminaries
2 Monte Carlo Methods for Statistical Inference
3 Randomization and Data Partitioning
4 Bootstrap Methods
5 Tools for Identification of Structure in Data
6 Estimation of Functions
7 Graphical Methods in Computational Statistics
II Exploring Data Density and Structure
Introduction to Part II
8 Estimation of Probability Density Functions Using Parametric Models
9 Nonparametric Estimation of Probability Density Functions
10 Structure in data
11 Statistical Models of Dependencies
Appendices
A Monte Carlo Studies in Statistics
B Software for Randon Number Generation
C Notation and Definitions
D Solutions and Hints for Selected Exercises
Bibliography
Author Index
Subject Index