Page 18 - Computational Statistics Handbook with MATLAB
P. 18

Chapter 1: Introduction                                           3



                                  T
                                  T
                                A B T T A B  E L E L LE L E  1.1  1.1
                                   AB
                                        1.1
                                        1.1
                                   AB
                                  Comparison Between Traditional Statistics and Computational Statistics
                                  [Wegman, 1988]. Reprinted with permission from the Journal of the
                                  Washington Academy of Sciences.
                                        Traditional Statistics      Computational Statistics
                                  Small to moderate sample size  Large to very large sample size
                                  Independent, identically distributed   Nonhomogeneous data sets
                                   data sets
                                  One or low dimensional       High dimensional
                                  Manually computational       Computationally intensive

                                  Mathematically tractable     Numerically tractable
                                  Well focused questions       Imprecise questions

                                  Strong unverifiable assumptions:  Weak or no assumptions:
                                    Relationships (linearity, additivity)  Relationships (nonlinearity)
                                    Error structures (normality)  Error structures (distribution free)

                                  Statistical inference        Structural inference
                                  Predominantly closed form    Iterative algorithms possible
                                   algorithms
                                  Statistical optimality       Statistical robustness




                             include a section containing references that explain the theoretical concepts
                             associated with the methods covered in that chapter.




                             Wh
                             Wh  a t t a  Cover CovereCovere  e I Issd d  Covere
                             WhWh
                                          I
                                          Issdd
                                aatt
                             In this book, we cover some of the most commonly used techniques in com-
                             putational statistics. While we cannot include all methods that might be a
                             part of computational statistics, we try to present those that have been in use
                             for several years.
                              Since the focus of this book is on the implementation of the methods, we
                             include algorithmic descriptions of the procedures. We also provide exam-
                             ples that illustrate the use of the algorithms in data analysis. It is our hope
                             that seeing how the techniques are implemented will help the reader under-
                             stand the concepts and facilitate their use in data analysis.
                              Some background information is given in Chapters 2, 3, and 4 for those
                             who might need a refresher in probability and statistics. In Chapter 2, we dis-
                             cuss some of the general concepts of probability theory, focusing on how they



                             © 2002 by Chapman & Hall/CRC
   13   14   15   16   17   18   19   20   21   22   23