Customer Reviews

Nonlinear Regression Analysis and Its Applications (Wiley Series in Probability and Statistics)

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Along with Gallant's book on nonlinear regression this book is one of the best. It is on an intermediate level and assumes some knowledge of linear regression. Notable unique aspects of the book are (1) good use of geometry, (2) discussion of derivative free methods, (3) use of profile likelihood and profile t plots and (4) measures of degree of nonlinearity of the problem. The authors also provide many real world applications directly from their consulting experience.

These authors were among the researchers that developed these measures of nonlinearity and so that aspect of the book is original and is emphasized in this book more than in others such as Gallant's.

I am a non-statistics graduate student, but I needed to learn this material for my thesis project. Nonlinear regression is definitely an advanced topic, but with only one class in matrix algebra and a year of calculus, I was able to understand and follow along. Many sections I had to re-read a few times, but they do make sense. I don't expect that this topic could be any more simply put at this level of detail. Bonus: Bates is an author of the nls function in R. All the terminology in this book matches the terminolgy in the function parameters.

If you are looking for some general guidelines into non-linear regression this is NOT for you. This is way over basic if not over intermediate bordering on super advanced non-linear regression discussion. The beginner and fairly knowledgeable person that is looking for some basic insight into non-linear work should stay away from this. A long way from this!