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Variation independent parametrizations

Evans, R (Stats Lab)
Monday 26 September 2011, 12:30-12:40

Seminar Room 1, Newton Institute


Variation independence can be a useful tool for developing algorithms and for param- eter interpretation. We present a simple method for creating variation independent parametrizations of some discrete models using Fourier-Motzkin elimination, with some examples.


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