Series prefece
Authors' preface

1 Introduction
2 The Classical Maximum Entropy Formalism: A Review

PART ⅠPURE INVERSE PROBLEMS
3 Basic Maximum Entropy Principle: formulation and Extensions
4 Formulation and Solution of Pure Inverse Problems
5 Generalized Pure Inverse Problems

PART Ⅱ ㅣLINEAR INVERSE PROBLEMS WITH NOISE
6 Generalized Maximun Entropy(GME) and Cross-Entropy(GCE)
7Finite Sample Extensions of Gme-Gce

PART Ⅲ GENERAL LINEAR MODEL APPLICATIONS OF GME-GCE
8 GME-GCE Solutions to Ill-conditioned Problems
9 General Linear Statistical Model with a Non-scalar Identity Covariance Matrix
10 Statistical Nodel Selection

PART Ⅳ A SYSTEM OF ECONOMIC STATISTICAL RELATIONS
11 Sets of Linear Statistical Models
12 Simultaneous Equations Statistical Model

PART ⅤLINEAR AND NON-LINEAR DYNAMIC SYSTMES
13 Estimation and Inference of Dynamic Linear Inverse Problems
14 Linear and Non-linear Dynamic systems with Control

PART Ⅵ DISCRETE CHOICE-CENSORED PROBLEMS
15 Recovering Information from Multinomial response Data
16 Recovering Information from Censored response Data

PART Ⅶ COMPUTATIONAL NOTES
17 Computing GME-GCE Solutions

PART Ⅷ EPILOGUE
Selected Reading
Index