Maximum likelihood estimation and inference : with examples in R, SAS, and ADMB / / Russell B. Millar.
"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 mos...
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| Superior document: | Statistics in practice |
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| Year of Publication: | 2011 |
| Language: | English |
| Series: | Statistics in practice.
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| Online Access: | |
| Physical Description: | xvi, 357 p. :; ill. |
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| Summary: | "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"-- |
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| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9780470094822 (hardback) 9780470094846 (oBook) 9781119977728 (Mobi) 9781119977711 (electronic bk.) 9780470094839 (electronic bk.) |
| Hierarchical level: | Monograph |
| Statement of Responsibility: | Russell B. Millar. |