Posts Tagged ‘ computational statistics ’

reaching transcendence for Gaussian mixtures

September 2, 2015
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reaching transcendence for Gaussian mixtures

“…likelihood inference is in a fundamental way more complicated than the classical method of moments.” Carlos Amendola, Mathias Drton, and Bernd Sturmfels arXived a paper this Friday on “maximum likelihood estimates for Gaussian mixtures are transcendental”. By which they mean that trying to solve the five likelihood equations for a two-component Gaussian mixture does not […]

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future of computational statistics

September 28, 2014
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future of computational statistics

I am currently preparing a survey paper on the present state of computational statistics, reflecting on the massive evolution of the field since my early Monte Carlo simulations on an Apple //e, which would take a few days to return a curve of approximate expected squared error losses… It seems to me that MCMC is […]

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Bayesian computational tools

June 17, 2013
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Bayesian computational tools

I just updated my short review on Bayesian computational tools I first wrote in April for the Annual Review of Statistics and Its Applications. The coverage is quite restricted, as I took advantage of two phantom papers I had started a while ago, one with Jean-Michel Marin, on hierarchical Bayes methods and on ABC. (As […]

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