Regression Models for Time Series Analysis

each chapter are designed for readers with a strong statistical background and are primarily theoretical; only a few datasets are given. In the discussion at the end of each chapter, the author provides brief computational notes to refer the reader to various software packages that may be used to apply the methods in the chapter to data. The lack of software integration might limit the ability of this book to be used as the sole text in a course on survival analysis. This text would be best suited for a theoretical course in survival analysis. However, if supplemented with material from a software-oriented book, such as Allison (1995), one could create a more applied course using this text. Due to the aforementioned omission of many reliability topics, this book is limited as a text for a reliability course. The author’s Ž rst goal of creating an excellent reference book is clearly achieved and the goal of creating a text for a Ž rst graduate course is also achieved. The Ž rst edition of this book, published in 1982, has become a standard reference for many statisticians working in survival analysis; the second edition is sure to continue the legacy. For a uniŽ ed and thorough reference of classical theory and models, this book is a excellent choice.