Advanced SPLUS Training

David Remer (dremer@statsci.com)
Fri, 16 Jan 1998 13:51:51 -0800 (PST)


Subject: Advanced SPLUS Training Course

MathSoft will be holding an SPLUS Statistical Models class in San Francisco, CA the week of February 18-20. This is an intermediate/advanced level course for SPLUS users that want to learn more about creating models and interpreting results. The tuition for 3 day class is $1050. The course is already partially filled, so please let me know ASAP if you want to attend. A syllabus follows.

David Remer
MathSoft Inc.
800-569-0123 x247

Statistical Models in S-PLUS

Days: 3
CEU: 2.2 (22 contact hours)
Cost: $1050

Course covers the modern modeling methods available with the latest version of S-PLUS. The underlying theory of the modern modeling methods is stressed with hands-on applications using S-PLUS and interpretation of results. The course includes: linear models, ANOVA (including Design of Experiments), generalized linear models, generalized additive models, local regression (LOESS-local smoothers), tree based modeling, and non-linear least squares modeling.

Day 1, AM
Introductions
Overview
- Overview of statistical models in S-PLUS
- Review of object types and classes
- Object orientation
- Specifying models with formulas
Linear Models
- Background
- The Fitting Algorithm
- Fitting models
- Extracting information
- Options in fitting
- Modifying models
- Plotting the fits
- Prediction
- Repeated fitting
- Diagnostics

Day 1, PM
ANOVA and Design of Experiments
- Background
- Generating experimental designs
- The Fitting Algorithm
- Formulas: factors, interactions, nesting,
contrasts
- Fitting models
- Plotting the fits
- Aliasing

Day 2, AM
Generalized Linear Models
- Background: link and variance
- The Fitting Algorithm
- Fitting models
- Residuals
- Family generator functions
- Analysis of deviance
- Plotting the fits
- Diagnostics
- Prediction
- Stepwise selection

Day 2, PM
Generalized Additive Models
- Background
- Spline and local regressions smoothers
- The Fitting Algorithm
- Fitting models
- Plotting the fits
- Prediction

Day 3, AM
Local Regression (Loess) Models
- Background
- The Fitting Algorithm
- Fitting models
- Plotting the fits
- Prediction

Day 3, PM
Tree-Based Models
- Background
- The Fitting Algorithm
- Fitting models
- Plotting the fits
- Interacting with trees
Nonlinear Models
- Background
- The Fitting Algorithms
- Specifying models
- Fitting models
- Plotting the fits