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目次情報: 続きを見る

Preface

Unconstrained Optimization via Calculus / 1：

Convex and Convex Functions / 2：

Iterative Methods for Unconstrained Optimization / 3：

Least Squares Optimization / 4：

Convex Programming and the Karush-Kuhn-Tucker Conditions / 5：

Penalty Methods / 6：

Optimization with Equality Constraints / 7：

Index

Preface

Unconstrained Optimization via Calculus / 1：

Convex and Convex Functions / 2：

目次情報: 続きを見る

The Prediction Matrix

Role of Variables in a Regression Equation

Effects of an Observation on a Regression Equation

Assessing the Influence of Multiple Observations

Joint Impact of a Variable and an Observation

Assessing the Effect of Errors of Measurements

A Study of Model Sensitivity by the Generalized Linear Model Approach

Computational Considerations

Appendix: Summary of Vector and Matrix Norms, Proofs of Three Theorems

Refernces

Index

The Prediction Matrix

Role of Variables in a Regression Equation

Effects of an Observation on a Regression Equation