| confint.ebnm | R Documentation |
The confint method for class ebnm.
Estimates posterior "credible intervals" for each "true mean" \theta_i.
We define the (1 - \alpha)% credible interval for \theta_i as
the narrowest continuous interval [a_i, b_i] such that
\theta_i \in [a_i, b_i] with posterior probability at least
1 - \alpha, where \alpha \in (0,1). We estimate these credible
intervals using Monte Carlo sampling. Note
that by default, ebnm does not return a posterior
sampler; one can be added to the ebnm object using function
ebnm_add_sampler.
## S3 method for class 'ebnm'
confint(object, parm, level = 0.95, nsim = 1000, ...)
object |
The fitted |
parm |
A vector of numeric indices specifying which means |
level |
The "confidence level" |
nsim |
The number of samples to use to estimate confidence intervals. |
... |
Additional arguments to be passed to the posterior sampler
function. Since |
A matrix with columns giving lower and upper confidence limits for
each mean \theta_i. These will be labelled as "CI.lower" and
"CI.upper".
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