Table of Contents
Chapter 1: Introduction
1.1 Product Overview
1.2 Product Features
1.3 Software Requirements
1.4 Documentation
1.4.1 Online Documentation
1.4.2 Assumptions
1.4.3 Typographic Conventions
1.4.4 Class and Function Naming
1.4.5 Class Relationship Notation
1.5 Technical Support
1.5.1 Before Contacting Technical Support
1.5.2 How to Contact Technical Support
Chapter 2: Library Architecture
2.1 Components
2.2 Regression Classes
2.3 Parameter Calculation Classes
2.3.1 The Base Calculation
2.4 Model Selection Classes
Chapter 3: Definitions
3.1 Note
3.2 Multiple Linear Regression
3.2.1 Parameter Calculation by Least Squares Minimization
3.2.2 Model Variance
3.2.3 Parameter Dispersion (Variance-Covariance) Matrix
3.2.4 Significance of the Model (Overall F Statistic)
3.2.5 Significance of Predictor Variables
3.2.6 Prediction Intervals
3.3 Logistic Regression
3.3.1 Parameter Calculation
3.3.2 Parameter Variances and Covariances
3.3.3 Significance of the Model
3.3.4 Parameter Significance (Wald Test)
Chapter 4: Model Selection
4.1 Definition
4.2 Model Selection Viewed As Search
4.2.1 Exhaustive Search
4.2.2 Forward Selection
4.2.3 Backward Selection
4.2.4 Stepwise Selection
Chapter 5: Using the Classes
5.1 Overview
5.2 Regression Classes
5.2.1 Updating Parameter Estimates
5.2.2 Intercept Option
5.3 Parameter Estimate Classes
5.4 Regression Analysis Classes
5.4.1 Class RWLinearRegressionANOVA
5.4.2 Class RWLogisticFitAnalysis
5.4.3 Class RWLinearRegressionFTest
5.5 Parameter Calculation Classes
5.5.1 Calculation Methods for Linear Regression
5.5.2 Calculation Methods for Logistic Regression
5.5.3 Writing Your Own Parameter Calculation Class
5.6 Using the Model Selection Classes
5.6.1 Selection Evaluation Criteria: Function Objects
5.6.2 A Detailed Example
5.6.3 Writing Your Own Function Objects
Chapter 6: References
Topic Index
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