Posts Tagged ‘ convergence of Gibbs samplers ’

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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likelihood-free inference in high-dimensional models

August 31, 2015
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likelihood-free inference in high-dimensional models

“…for a general linear model (GLM), a single linear function is a sufficient statistic for each associated parameter…” The recently arXived paper “Likelihood-free inference in high-dimensional models“, by Kousathanas et al. (July 2015), proposes an ABC resolution of the dimensionality curse [when the dimension of the parameter and of the corresponding summary statistics] by turning […]

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likelihood-free inference in high-dimensional models

August 31, 2015
By
likelihood-free inference in high-dimensional models

“…for a general linear model (GLM), a single linear function is a sufficient statistic for each associated parameter…” The recently arXived paper “Likelihood-free inference in high-dimensional models“, by Kousathanas et al. (July 2015), proposes an ABC resolution of the dimensionality curse [when the dimension of the parameter and of the corresponding summary statistics] by turning […]

Read more »


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