Strong Inference

Calculating Bayes factors with PyMC. Statisticians are sometimes interested in comparing two or more models, with respect to their relative support by a particular dataset. This may be in order to select the best model to use for inference, or to weight models so that they can be averaged for use in multimodel inference. Is a good choice when comparing two arbitrary models, and the parameters of those models have been estimated. Bayes factors are simply ratios of. Likelihoods for competing models.

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This web site stronginference.com was first recorded on October 08, 2009. This web site was updated on the date of September 30, 2013. This site will go back on the market on October 07, 2014. As of today, it is seven hundred and sixty-eight weeks, twenty-four days, twenty-two hours, and fifty-three minutes old.
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KeepingMeHonest Just another WordPress.com site

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Neal Caren by nealcaren

University of North Carolina, Chapel Hill mail. Learning Python for Social Scientists. My big list of tutorials. How the New York Times writes about men and women. Generating field hockey power ratings. IPynb notebooks are also available.

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Strong Inference

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Calculating Bayes factors with PyMC. Statisticians are sometimes interested in comparing two or more models, with respect to their relative support by a particular dataset. This may be in order to select the best model to use for inference, or to weight models so that they can be averaged for use in multimodel inference. Is a good choice when comparing two arbitrary models, and the parameters of those models have been estimated. Bayes factors are simply ratios of. Likelihoods for competing models.

CONTENT

This web site had the following in the homepage, "Statisticians are sometimes interested in comparing two or more models, with respect to their relative support by a particular dataset." We noticed that the web page stated " This may be in order to select the best model to use for inference, or to weight models so that they can be averaged for use in multimodel inference." It also said " Is a good choice when comparing two arbitrary models, and the parameters of those models have been estimated. Bayes factors are simply ratios of."

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