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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