Linear programming algorithms for detecting separated data in binary logistic regression models

Linear programming algorithms for detecting separated data in binary logistic regression models

This thesis is a study of the detection of separation among the sample points in binary logistic regression models. We propose a new algorithm for detecting separation and demonstrate empirically that it can be computed fast enough to be used routinely as part of the fitting process for logistic reg...

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Dettagli Bibliografici
Autore principale:	Konis, K
Altri autori:	Ripley, B
Natura:	Tesi
Lingua:	English
Pubblicazione:	2007
Soggetti:	Statistics (see also social sciences) Computationally-intensive statistics

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