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Spherical Minimum Description Length
We consider the problem of model selection using the Minimum Description Length (MDL) criterion for distributions with parameters on the hypersphere. Model selection algorithms aim to find a compromise between goodness of fit and model complexity. Variables often considered for complexity penalties involve number of parameters, sample size and shape of the parameter space, with the penalty term often referred to as stochastic complexity. Current model selection criteria either ignore the shapedoi:10.3390/e20080575 pmid:33265664 fatcat:jz4f65dwjbexnlitygebakexim