Simultaneous Statistical Inference

Beschreibung

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.
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.
Concise treatment of theoretical and practical properties of the false discovery rate (FDR) Detailed examples from the life sciences, accompanied by software solutions Includes latest developments of simultaneous statistical inference methods for a variety of non-standard situations Includes supplementary material: sn.pub/extras

Autor*in

Thorsten Dickhaus

Themen in »Simultaneous Statistical Inference«

Binary Classification Error Measures for High-dimensional Data False Discovery Rate Large-scale Problems in the Life Sciences Least Favorable Parameter Configurations Multiple Testing Theory Multiple Tests for Discrete Data Simultaneous Statistical Inference Step-up-down Tests

Stimmen zu »Simultaneous Statistical Inference«

“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)

Details

Link teilen