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ashr  

Methods for Adaptive Shrinkage, using Empirical Bayes
View on CRAN: Click here


Download and install ashr package within the R console
Install from CRAN:
install.packages("ashr")

Install from Github:
library("remotes")
install_github("cran/ashr")

Install by package version:
library("remotes")
install_version("ashr", "2.2-63")



Attach the package and use:
library("ashr")
Maintained by
Peter Carbonetto
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-12-27
Latest Update: 2023-08-21
Description:
The R package 'ashr' implements an Empirical Bayes approach for large-scale hypothesis testing and false discovery rate (FDR) estimation based on the methods proposed in M. Stephens, 2016, "False discovery rates: a new deal", . These methods can be applied whenever two sets of summary statistics---estimated effects and standard errors---are available, just as 'qvalue' can be applied to previously computed p-values. Two main interfaces are provided: ash(), which is more user-friendly; and ash.workhorse(), which has more options and is geared toward advanced users. The ash() and ash.workhorse() also provides a flexible modeling interface that can accommodate a variety of likelihoods (e.g., normal, Poisson) and mixture priors (e.g., uniform, normal).
How to cite:
Peter Carbonetto (2016). ashr: Methods for Adaptive Shrinkage, using Empirical Bayes. R package version 2.2-63, https://cran.r-project.org/web/packages/ashr. Accessed 06 Nov. 2024.
Previous versions and publish date:
2.0.5 (2016-12-27 15:28), 2.2-7 (2018-03-01 23:02), 2.2-32 (2019-02-22 10:50), 2.2-39 (2019-10-17 20:00), 2.2-40 (2020-02-03 21:10), 2.2-47 (2020-02-20 06:40), 2.2-54 (2022-02-22 17:10)
Other packages that cited ashr R package
View ashr citation profile
Other R packages that ashr depends, imports, suggests or enhances
Complete documentation for ashr
Functions, R codes and Examples using the ashr R package
Some associated functions: ash . ash_pois . ashci . ashr . calc_logLR . calc_loglik . calc_mixmean . calc_mixsd . calc_null_loglik . calc_null_vloglik . calc_vlogLR . calc_vloglik . cdf.ash . cdf_conv . cdf_post . comp_cdf . comp_cdf_conv.normalmix . comp_cdf_conv . comp_cdf_conv.unimix . comp_cdf_post . comp_dens . comp_dens_conv.normalmix . comp_dens_conv . comp_dens_conv.unimix . comp_mean.normalmix . comp_mean . comp_mean.tnormalmix . comp_mean2 . comp_postmean . comp_postmean2 . comp_postprob . comp_postsd . comp_sd.normalmix . comp_sd . comp_sd.tnormalmix . compute_lfsr . cxxMixSquarem . dens . dens_conv . dlogf . estimate_mixprop . gen_etruncFUN . get_density . get_lfdr . get_post_sample . igmix . lik_binom . lik_logF . lik_normal . lik_normalmix . lik_pois . lik_t . log_comp_dens_conv.normalmix . log_comp_dens_conv . log_comp_dens_conv.unimix . loglik_conv.default . loglik_conv . mixEM . mixIP . mixSQP . mixVBEM . mixcdf.default . mixcdf . mixmean2 . mixprop . my_e2truncbeta . my_e2truncgamma . my_e2truncnorm . my_e2trunct . my_etruncbeta . my_etruncgamma . my_etrunclogf . my_etruncnorm . my_etrunct . my_vtruncnorm . ncomp.default . ncomp . normalmix . pcdf_post . plogf . plot.ash . plot_diagnostic . pm_on_zero . post_sample.normalmix . post_sample . post_sample.unimix . posterior_dist . postmean . postmean2 . postsd . print.ash . prune . qval.from.lfdr . set_data . summary.ash . tnormalmix . unimix . vcdf_post . w_mixEM . 
Some associated R codes: RcppExports.R . ash.R . ashCI.R . ash_estmode.R . ash_pois.R . ashr-package.R . ashutility.R . get_functions.R . igmix.R . lik.R . logF.R . mix.R . mix_opt.R . normalmix.R . output.R . process_args.R . set_data.R . tnormalmix.R . truncbeta.R . truncgamma.R . truncgen.R . truncnorm.R . trunct.R . unimix.R .  Full ashr package functions and examples
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