Man pages for ebnm
Solve the Empirical Bayes Normal Means Problem
| coef.ebnm | Extract posterior means from a fitted EBNM model |
| confint.ebnm | Obtain confidence 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_deconvolver | Solve the EBNM problem using the "deconvolveR" family of... |
| 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_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... |
| ebnm_unimodal_nonpositive | Solve the EBNM problem using unimodal nonpositive... |
| 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... |
| 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 |
| wOBA | 2022 MLB wOBA Data |
