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