Measurement Error in Nonlinear Models

It's been over a decade since the first edition of Measurement Error in Nonlinear Modelssplashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Second Editionhas been revamped and extensively updated to offer the most comprehensive and up-to-date survey of measurement error models currently available.What's new in the Second Edition?· Greatly expandeddiscussion and applications of Bayesian computation via Markov Chain Monte Carlo techniques· A new chapteron longitudinal data and mixed models· Athoroughly revisedchapter on nonparametric regression and density estimation· A totally newchapter on semiparametric regression· Survival analysis expandedinto its own separate chapter· Completely rewrittenchapter on score functions· Many moreexamples and illustrative graphs· Unique data setscompiled and made available onlineIn addition, the authors expanded the background material in Appendix A and integrated the technical material from chapter appendices into a new Appendix B for convenient navigation. Regardless of your field, if you're looking for the most extensive discussion and review of measurement error models, then Measurement Error in Nonlinear Models: A Modern Perspective, Second Editionis your ideal source.