EbayesThresh

Empirical Bayes Thresholding and Related Methods

Empirical Bayes thresholding using the methods developed by I. M. Johnstone and B. W. Silverman. The basic problem is to estimate a mean vector given a vector of observations of the mean vector plus white noise, taking advantage of possible sparsity in the mean vector. Within a Bayesian formulation, the elements of the mean vector are modelled as having, independently, a distribution that is a mixture of an atom of probability at zero and a suitable heavy-tailed distribution. The mixing parameter can be estimated by a marginal maximum likelihood approach. This leads to an adaptive thresholding approach on the original data. Extensions of the basic method, in particular to wavelet thresholding, are also implemented within the package.

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Description file content

Package
EbayesThresh
Encoding
UTF-8
Type
Package
Title
Empirical Bayes Thresholding and Related Methods
Version
1.4-12
Date
2017-07-29
URL
BugReports
https://github.com/stephenslab/EbayesThresh/issues
Description
Empirical Bayes thresholding using the methods developed by I. M. Johnstone and B. W. Silverman. The basic problem is to estimate a mean vector given a vector of observations of the mean vector plus white noise, taking advantage of possible sparsity in the mean vector. Within a Bayesian formulation, the elements of the mean vector are modelled as having, independently, a distribution that is a mixture of an atom of probability at zero and a suitable heavy-tailed distribution. The mixing parameter can be estimated by a marginal maximum likelihood approach. This leads to an adaptive thresholding approach on the original data. Extensions of the basic method, in particular to wavelet thresholding, are also implemented within the package.
Imports
stats, wavethresh
Suggests
testthat, knitr, rmarkdown, dplyr, ggplot2
NeedsCompilation
no
License
GPL (>= 2)
VignetteBuilder
knitr
Packaged
2017-07-30 12:06:51 UTC; pcarbo
Author
Bernard W. Silverman [aut], Ludger Evers [aut], Kan Xu [aut], Peter Carbonetto [aut, cre], Matthew Stephens [aut]
Maintainer
Peter Carbonetto
Repository
CRAN
Date/Publication
2017-08-08 04:02:13 UTC

install.packages('EbayesThresh')

1.4-12

2 months ago

https://github.com/stephenslab/EbayesThresh

Peter Carbonetto

GPL (>= 2)

Imports

stats, wavethresh

Suggests

testthat, knitr, rmarkdown, dplyr, ggplot2

Discussions