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Sampling from Dirichlet process mixture models with unknown concentration parameter: mixing issues in large data implementations
Sampling from Dirichlet process mixture models with unknown concentration parameter: mixing issues in large data implementations
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Sampling from Dirichlet process mixture models with unknown concentration parameter: mixing issues in large data implementations

Statistics and Computing, 2015, Vol.25(5), pp.1023-1037 [Peer Reviewed Journal]

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A semi-parametric approach to estimate risk functions associated with multi-dimensional exposure profiles: application to smoking and lung cancer
A semi-parametric approach to estimate risk functions associated with multi-dimensional exposure profiles: application to smoking and lung cancer
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A semi-parametric approach to estimate risk functions associated with multi-dimensional exposure profiles: application to smoking and lung cancer

BMC medical research methodology, 23 October 2013, Vol.13, pp.129 [Peer Reviewed Journal]

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Sampling from Dirichlet process mixture models with unknown concentration parameter: Mixing issues in large data implementations
Sampling from Dirichlet process mixture models with unknown concentration parameter: Mixing issues in large data implementations
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Sampling from Dirichlet process mixture models with unknown concentration parameter: Mixing issues in large data implementations

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Model choice using reversible jump Markov chain Monte Carlo
Model choice using reversible jump Markov chain Monte Carlo
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Model choice using reversible jump Markov chain Monte Carlo

Statistica Neerlandica, Aug 2012, pp.309-338 [Peer Reviewed Journal]

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PReMiuM: An R Package for Profile Regression Mixture Models Using Dirichlet Processes
PReMiuM: An R Package for Profile Regression Mixture Models Using Dirichlet Processes
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PReMiuM: An R Package for Profile Regression Mixture Models Using Dirichlet Processes

Journal of Statistical Software, 01 March 2015, Vol.64(1), pp.1-30 [Peer Reviewed Journal]

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PReMiuM: An R Package for Profile Regression Mixture Models using Dirichlet Processes
PReMiuM: An R Package for Profile Regression Mixture Models using Dirichlet Processes
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PReMiuM: An R Package for Profile Regression Mixture Models using Dirichlet Processes

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7
++: a C++ objected-oriented algorithm for Bayesian stochastic search model exploration
++: a C++ objected-oriented algorithm for Bayesian stochastic search model exploration
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++: a C++ objected-oriented algorithm for Bayesian stochastic search model exploration

Bioinformatics, 2011, Vol. 27(4), pp.587-588 [Peer Reviewed Journal]

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ESS++: a C++ objected-oriented algorithm for Bayesian stochastic search model exploration.
ESS++: a C++ objected-oriented algorithm for Bayesian stochastic search model exploration.
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ESS++: a C++ objected-oriented algorithm for Bayesian stochastic search model exploration.

Bioinformatics (Oxford, England), February 15, 2011, Vol.27(4), pp.587-588 [Peer Reviewed Journal]

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GUESS-ing polygenic associations with multiple phenotypes using a GPU-based evolutionary stochastic search algorithm
GUESS-ing polygenic associations with multiple phenotypes using a GPU-based evolutionary stochastic search algorithm
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GUESS-ing polygenic associations with multiple phenotypes using a GPU-based evolutionary stochastic search algorithm

PLoS Genetics, 01 January 2013, Vol.9(8), p.e1003657 [Peer Reviewed Journal]

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Assessing Poisson Variation of Intestinal Tumour Multiplicity in Mice Carrying a Robertsonian Translocation
Assessing Poisson Variation of Intestinal Tumour Multiplicity in Mice Carrying a Robertsonian Translocation
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Assessing Poisson Variation of Intestinal Tumour Multiplicity in Mice Carrying a Robertsonian Translocation

Journal of the Royal Statistical Society. Series C (Applied Statistics), 1 January 2006, Vol.55(1), pp.123-138 [Peer Reviewed Journal]

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by this Author/Contributor:

  1. Campbell, Harry
  2. Vitart, Veronique
  3. Rudan, Igor
  4. Hayward, Caroline
  5. Teumer, Alexander

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