Posts Tagged ‘ mixtures of distributions ’

Statistical rethinking [book review]

April 5, 2016
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Statistical rethinking [book review]

Statistical Rethinking: A Bayesian Course with Examples in R and Stan is a new book by Richard McElreath that CRC Press sent me for review in CHANCE. While the book was already discussed on Andrew’s blog three months ago, and [rightly so!] enthusiastically recommended by Rasmus Bååth on Amazon, here are the reasons why I […]

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twilight zone [of statistics]

February 25, 2016
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twilight zone [of statistics]

“I have decided that mixtures, like tequila, are inherently evil and should be avoided at all costs.” L. Wasserman Larry Wasserman once remarked that finite mixtures were like the twilight zone of statistics, thanks to the numerous idiosyncrasies associated with such models. And George Casella had similar strong reservations about mixture estimation. Avi Feller and […]

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mixtures are slices of an orange

January 11, 2016
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mixtures are slices of an orange

After presenting this work in both London and Lenzerheide, Kaniav Kamary, Kate Lee and I arXived and submitted our paper on a new parametrisation of location-scale mixtures. Although it took a long while to finalise the paper, given that we came with the original and central idea about a year ago, I remain quite excited […]

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MCMskv #2 [ridge with a view]

January 6, 2016
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MCMskv #2 [ridge with a view]

Tuesday at MCMSkv was a rather tense day for me, from having to plan the whole day “away from home” [8km away] to the mundane worry of renting ski equipment and getting to the ski runs over the noon break, to giving a poster over our new mixture paper with Kaniav Kamary and Kate Lee, […]

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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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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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