1st Edition

Elements of Statistical Computing NUMERICAL COMPUTATION

By R. A. Thisted Copyright 1988
    448 Pages
    by Chapman & Hall

    Statistics and computing share many close relationships. Computing now permeates every aspect of statistics, from pure description to the development of statistical theory. At the same time, the computational methods used in statistical work span much of computer science. Elements of Statistical Computing covers the broad usage of computing in statistics. It provides a comprehensive account of the most important computational statistics. Included are discussions of numerical analysis, numerical integration, and smoothing.

    The author give special attention to floating point standards and numerical analysis; iterative methods for both linear and nonlinear equation, such as Gauss-Seidel method and successive over-relaxation; and computational methods for missing data, such as the EM algorithm. Also covered are new areas of interest, such as the Kalman filter, projection-pursuit methods, density estimation, and other computer-intensive techniques.

    Preface, Chapter 1: Introduction to Statistical Computing, Chapter 2: Basic Numerical Methods, Chapter 3: Numerical Linear Algebra, Chapter 4: Nonlinear Statistical Methods, Chapter 5: Numerical Integration and Approximation, Chapter 6: Smoothing and Density Estimation, Answers to Selected Exercises, References, Index

    Biography

    R.A. Thisted

    "Very readable...This is an authoritative and well-written book which is also of considerable practical use...It is highly recommended."
    eadable...This is an authoritative and well-written book which is also of considerable practical use...It is highly recommended."