Teaching plan for programming in S-Plus

1. Becker, R.A., Chambers J.M. and Wilks A.R. (1988) The new S Language, A Programming Environment For Data Analysis and Graphics, Wadsworth and Brooks/Cole Computer Science Series.
2. Chambers J. M., Hastie, T. (1992) Statistical Models in S Wadsworth and brooks/cole Computer Science Series.
3. Chambers J. M. (1998) Programming with data: A guide to the S language New York: Springer-Verlag. See the homepage of the book here.
4. Venables W.N. , Ripley B.D. (1999) Modern Applied Statistics with S-PLUS Vol 1: Data Analysis Springer-Verlag. See the homepage of the book here.
5. Venables W.N. , Ripley B.D. (2000) S Programming Springer-Verlag. See the homepage of the book here.

Lecture 1

Contents:
Review of S and S-Plus. Introduction to objects types and attributes in S-Plus including vectors, matrices, data frames, arrays, time series, factors and lists.

Lecture 2

Contents:
Functions and operators. Graphics devices. High- and low-level graphics functions, Trellis graphics, multiple and conditioning plots.

Lecture 3

Contents:
Statistical analysis with S-Plus. Classical statistical tests, Linear and generalised linear models. Data input and output.

Lecture 4

Contents:
Introduction to programming in S. Syntax, special symbols and data values, iteration, frames, memory management and running batch processes.

Lecture 5

Contents:
Writing functions in S-Plus. Interfacing to C and Fortran. Debugging tools.

Lecture 6

Contents:
Fitting non-linear regression models. Maximum likelihood estimation with S-Plus.

Lecture 7

Contents:
S-Plus functions for statistical modelling of extreme values.