Ebook Download Simultaneous Statistical Inference: With Applications in the Life SciencesBy Thorsten Dickhaus
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Simultaneous Statistical Inference: With Applications in the Life SciencesBy Thorsten Dickhaus
Ebook Download Simultaneous Statistical Inference: With Applications in the Life SciencesBy Thorsten Dickhaus
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This monograph will provide an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate (FDR) and related error measures, particularly addressing applications to fields such as genetics, proteomics, neuroscience and general biology. The book will also include a detailed description how to implement these methods in practice. Moreover new developments focusing on non-standard assumptions are also included, especially multiple tests for discrete data. The book primarily addresses researchers and practitioners but will also be beneficial for graduate students.
- Sales Rank: #4189336 in Books
- Published on: 2014-01-23
- Original language: English
- Number of items: 1
- Dimensions: 9.21" h x .50" w x 6.14" l, .90 pounds
- Binding: Hardcover
- 180 pages
Review
“Thorsten Dickhaus’ Simultaneous Statistical Inference is without a doubt the most thorough yet concise roundup of multiple-test procedures that has come out in many years. … It is all the more worthwhile reading for statistical researchers, who will be guided through the maze of multiple-testing approaches that have accumulated over the past decades. … a rich source of inspiration for anyone who has some mathematical background and seeks a deep understanding of state-of-the-art simultaneous inference.” (Philip Pallmann, Biometrical Journal, Vol. 57 (6), 2015)
From the Back Cover
This monograph will provide an in-depth mathematical treatment of modern multiple test procedures controlling the false discovery rate (FDR) and related error measures, particularly addressing applications to fields such as genetics, proteomics, neuroscience and general biology. The book will also include a detailed description how to implement these methods in practice. Moreover, new developments focusing on non-standard assumptions are also included, especially multiple tests for discrete data. The book primarily addresses researchers and practitioners but will also be beneficial for graduate students.
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