A balanced presentation of the theoretical, practical, and computational aspects of nonlinear regression. This book provides background material on linear regression, including a geometrical development for linear and nonlinear least squares. The authors employ real data sets throughout, and their extensive use of geometric constructs and continuing examples makes the progression of ideas appear very natural. The book also includes pseudocode for computing algorithms.