R: Solve the Empirical Bayes Normal Means Problem

# Solve the Empirical Bayes Normal Means Problem

## Documentation for package ‘ebnm’ version 1.1-42

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

coef.ebnm | Extract posterior means from a fitted EBNM model
confint.ebnm | Obtain credible intervals using a fitted EBNM model
ebnm | Solve the EBNM problem
ebnm_add_sampler | Add sampler to an ebnm_object
ebnm_ash | Solve the EBNM problem using an ash family of distributions
ebnm_check_fn | Check a custom ebnm function
ebnm_deconvolver | Solve the EBNM problem using the "deconvolveR" family of distributions
ebnm_flat | Solve the EBNM problem using a flat prior
ebnm_generalized_binary | Solve the EBNM problem using generalized binary priors
ebnm_group | Solve the EBNM problem for grouped data
ebnm_horseshoe | Solve the EBNM problem using horseshoe priors
ebnm_normal | Solve the EBNM problem using normal priors
ebnm_normal_scale_mixture | Solve the EBNM problem using scale mixtures of normals
ebnm_npmle | Solve the EBNM problem using the family of all distributions
ebnm_output_all | Solve the EBNM problem
ebnm_output_default | Solve the EBNM problem
ebnm_point_exponential | Solve the EBNM problem using point-exponential priors
ebnm_point_laplace | Solve the EBNM problem using point-Laplace priors
ebnm_point_mass | Solve the EBNM problem using a point mass prior
ebnm_point_normal | Solve the EBNM problem using point-normal priors
ebnm_scale_normalmix | Set scale parameter for scale mixtures of normals
ebnm_scale_npmle | Set scale parameter for NPMLE and deconvolveR prior family
ebnm_scale_unimix | Set scale parameter for nonparametric unimodal prior families
ebnm_unimodal | Solve the EBNM problem using unimodal distributions
ebnm_unimodal_nonnegative | Solve the EBNM problem using unimodal nonnegative distributions
ebnm_unimodal_nonpositive | Solve the EBNM problem using unimodal nonpositive distributions
ebnm_unimodal_symmetric | Solve the EBNM problem using symmetric unimodal distributions
fitted.ebnm | Extract posterior estimates from a fitted EBNM model
gammamix | Constructor for gammamix class
horseshoe | Constructor for horseshoe class
laplacemix | Constructor for laplacemix class
logLik.ebnm | Extract the log likelihood from a fitted EBNM model
nobs.ebnm | Get the number of observations used to fit an EBNM model
plot.ebnm | Plot an ebnm object
predict.ebnm | Use the estimated prior from a fitted EBNM model to solve the EBNM problem for new data
print.ebnm | Print an ebnm object
print.summary.ebnm | Print a summary.ebnm object
quantile.ebnm | Obtain posterior quantiles using a fitted EBNM model
residuals.ebnm | Calculate residuals for a fitted EBNM model
simulate.ebnm | Sample from the posterior of a fitted EBNM model
summary.ebnm | Summarize an ebnm object
vcov.ebnm | Extract posterior variances from a fitted EBNM model
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