A wrapper to function ash in package ashr.
Identical to function ebnm with argument
prior_family = "ash".
ebnm_ash(
x,
s = 1,
mode = 0,
scale = "estimate",
g_init = NULL,
fix_g = FALSE,
output = ebnm_output_default(),
control = NULL,
...
)A vector of observations. Missing observations (NAs) are
not allowed.
A vector of standard errors (or a scalar if all are equal). Standard errors may not be exactly zero, and missing standard errors are not allowed.
Passed to ash as parameter mode.
Passed to ash as parameter mixsd.
Passed to ash as parameter g.
Passed to ash as parameter fixg.
A character vector indicating which values are to be returned.
Function ebnm_output_default() provides the default return values, while
ebnm_output_all() lists all possible return values. See Value
below.
Passed to ash as parameter control.
Additional parameters to be passed to ash.
An ebnm object. Depending on the argument to output, the
object is a list containing elements:
dataA data frame containing the observations x
and standard errors s.
posteriorA data frame of summary results (posterior means, standard deviations, second moments, and local false sign rates).
fitted_gThe fitted prior \(\hat{g}\).
log_likelihoodThe optimal log likelihood attained, \(L(\hat{g})\).
posterior_samplerA function that can be used to
produce samples from the posterior. The sampler takes a single
parameter nsamp, the number of posterior samples to return per
observation.
S3 methods coef, confint, fitted, logLik,
nobs, plot, predict, print, quantile,
residuals, simulate, summary, and vcov
have been implemented for ebnm objects. For details, see the
respective help pages, linked below under See Also.
See ebnm for examples of usage and model details.
Available S3 methods include coef.ebnm,
confint.ebnm,
fitted.ebnm, logLik.ebnm,
nobs.ebnm, plot.ebnm,
predict.ebnm, print.ebnm,
print.summary.ebnm, quantile.ebnm,
residuals.ebnm, simulate.ebnm,
summary.ebnm, and vcov.ebnm.