A theoretical comparison of the data augmentation, marginal augmentation and PX-DA algorithms
نویسندگان
چکیده
منابع مشابه
A theoretical comparison of the data augmentation, marginal augmentation and PX-DA algorithms
The data augmentation (DA) algorithm is a widely used Markov chain Monte Carlo (MCMC) algorithm that is based on a Markov transition density of the form p(x|x′) = ∫ Y fX|Y (x|y)fY |X(y|x) dy, where fX|Y and fY |X are conditional densities. The PX-DA and marginal augmentation algorithms (Liu and Wu, 1999; Meng and van Dyk, 1999) are alternatives to DA that often converge much faster and are only...
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چکیده ندارد.
15 صفحه اولConnectivity augmentation algorithms
The main subject of the thesis is connectivity augmentation: we would like to make a given graph k-connected by adding a minimum number of new edges. There are four basic problems in this field, since one might consider both edgeand node-connectivity augmentation in both graphs and digraphs. The thesis wishes to contribute to three out of these four problems: directedand undirected node-connect...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2008
ISSN: 0090-5364
DOI: 10.1214/009053607000000569