|aMaximum likelihood estimation and inference :|bwith examples in R, SAS, and ADMB /|cby Russell B. Millar.
|aChichester, West Sussex :|bJohn Wiley & Sons,|c2011.
|axvi, 357 p. :|bill. ;|c24 cm.
|aStatistics in practice
|aIncludes bibliographical references and index.
|a"Applied Likelihood Methods provides an accessible and practical introduction to likelihood modeling, supported by examples and software. The book features applications from a range of disciplines, including statistics, medicine, biology, and ecology. The methods are implemented in SAS--the most widely used statistical software package--and the data sets and SAS code are provided on a Web site, enabling the reader to use the methods to solve problems in their own work. This book serves as an ideal text for applied scientists and researchers and graduate students of statistics"-- |c Provided by publisher.
|a"This book is the first to provide an accessible and practical introduction to likelihood modeling, supported by examples and software, and is suitable for the applied scientist"-- |c Provided by publisher.