This book gives a comprehensive introduction to exponential family nonlinear models, which are the natural extension of generalized linear models and normal nonlinear regression models. The differential geometric framework is presented for these models and the geometric methods are widely used in this book. The author also pays more attention to regression diagnostics and influence analysis. The book is ideally suited for researchers who work in statistical inference and for graduate students with a basic knowledge of statistics.Exponential Family.- Exponential Family Nonlinear Models.- Geometric Framework.- Some Second Order Asymptotics.- Confidence Regions.- Diagnostics and Influence Analysis.- Extension.- Appendices.- Bibliography.- Author Index.- Subject Index.* It is the FIRST book to deal with the subject on exponential family nonlinear models - a subject still very much in its infancy * The differential geometric framework is presented for these models and the geometric methods are widely used in this book * The author pays more attention to regression diagnostics and influence analysis, subjects which are being discussed for the first time * New models, new approaches and some new problems are introduced * The book is ideally suited for researchers who work in statistical inference and for graduate students with a basic knowledge of statisticsThis book gives a comprehensive introduction to exponential family nonlinear models, which are the natural extension of generalized linear models and normal nonlinear regression models. The differential geometric framework is presented for these models and the geometric methods are widely used in this book. The author also pays more attention to regression diagnostics and influence analysis. The book is ideally suited for researchers who work in statistical inference and for graduate students with a basic knowledge of statistics.Springer Book Archives