Package: ebnm 1.1-34

Peter Carbonetto

ebnm: Solve the Empirical Bayes Normal Means Problem

Provides simple, fast, and stable functions to fit the normal means model using empirical Bayes. For available models and details, see function ebnm(). A detailed introduction to the package is provided by Willwerscheid and Stephens (2023) <arxiv:2110.00152>.

Authors:Jason Willwerscheid [aut], Matthew Stephens [aut], Peter Carbonetto [aut, cre], Andrew Goldstein [ctb], Yusha Liu [ctb]

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ebnm.pdf |ebnm.html✨
ebnm/json (API)

Peer review:

Bug tracker:https://github.com/stephenslab/ebnm/issues

On CRAN:

28 exports 12 stars 2.44 score 43 dependencies 1 dependents 108 scripts 353 downloads

Last updated 3 months agofrom:faaea4729b. Checks:OK: 1 NOTE: 6. Indexed: yes.

Exports:ebnmebnm_add_samplerebnm_ashebnm_check_fnebnm_deconvolverebnm_flatebnm_generalized_binaryebnm_groupebnm_horseshoeebnm_normalebnm_normal_scale_mixtureebnm_npmleebnm_output_allebnm_output_defaultebnm_point_exponentialebnm_point_laplaceebnm_point_massebnm_point_normalebnm_scale_normalmixebnm_scale_npmleebnm_scale_unimixebnm_unimodalebnm_unimodal_nonnegativeebnm_unimodal_nonpositiveebnm_unimodal_symmetricgammamixhorseshoelaplacemix

Dependencies:ashrclicolorspacedeconvolveRdplyretrunctfansifarvergenericsggplot2gluegtablehorseshoeinvgammairlbaisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmixsqpmunsellnlmepillarpkgconfigR6RColorBrewerRcppRcppArmadillorlangscalesSQUAREMtibbletidyselecttruncnormtrustutf8vctrsviridisLitewithr