How does one derive a physical model from a finite set of observations containing errors ? And how can one determine the quality of such a model ? This book takes on these challenging problems, providing readers with an overview of a broad array of inverse methods. Aster, Borchers, and Thurber present both the underlying theory and practical algorithms for solving inverse problems. The authors' treatment targets advanced undergraduate and first-year graduate courses on inverse problems and geophysical inverse theory. Parameter Estimation and Inverse Problems introduces readers to Classical and Bayesian approaches to linear and nonlinear problems, with particular attention paid to computational, mathematical, and statistical issues related to their application to geophysical problems. The accompanying CD-ROM features computational examples and exercises using MATLAB routines. After learning this material, students should be well prepared to appreciate research papers that apply these methods.