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Generalized Maximally Selected Statistics

Hothorn, Torsten and Zeileis, Achim (2007) Generalized Maximally Selected Statistics. Research Report Series / Department of Statistics and Mathematics, 52. Department of Statistics and Mathematics, WU Vienna University of Economics and Business, Vienna.

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Abstract

Maximally selected statistics for the estimation of simple cutpoint models are embedded into a generalized conceptual framework based on conditional inference procedures. This powerful framework contains most of the published procedures in this area as special cases, such as maximally selected chi-squared and rank statistics, but also allows for direct construction of new test procedures for less standard test problems. As an application, a novel maximally selected rank statistic is derived from this framework for a censored response partitioned with respect to two ordered categorical covariates and potential interactions. This new test is employed to search for a high-risk group of rectal cancer patients treated with a neo-adjuvant chemoradiotherapy. Moreover, a new efficient algorithm for the evaluation of the asymptotic distribution for a large class of maximally selected statistics is given enabling the fast evaluation of a large number of cutpoints.

Item Type: Paper
Keywords: asymptotic distribution / changepoint / conditional inference / maximally selected statistics
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Repository Administrator
Date Deposited: 18 Apr 2007 22:01
Last Modified: 02 Mar 2017 07:29
URI: http://epub.wu.ac.at/id/eprint/1252

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