Change-point problems arise in a variety of experimental andmathematical sciences, as well as in engineering and healthsciences. This rigorously researched text provides a comprehensivereview of recent probabilistic methods for detecting various typesof possible changes in the distribution of chronologically orderedobservations. Further developing the already well-establishedtheory of weighted approximations and weak convergence, the authorsprovide a thorough survey of parametric and non-parametric methods,regression and time series models together with sequential methods.All but the most basic models are carefully developed with detailedproofs, and illustrated by using a number of data sets. Contains athorough survey of:

* The Likelihood Approach
* Non-Parametric Methods
* Linear Models
* Dependent Observations

This book is undoubtedly of interest to all probabilists andstatisticians, experimental and health scientists, engineers, andessential for those working on quality control and surveillanceproblems.

Foreword by David Kendall