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...

Bibliografiset tiedot
Päätekijä:	Konis, K
Muut tekijät:	Ripley, B
Aineistotyyppi:	Opinnäyte
Kieli:	English
Julkaistu:	2007
Aiheet:	Statistics (see also social sciences) Computationally-intensive statistics

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