rvalueBoot {rvalues} | R Documentation |
Bootstrapped r-values
Description
Estimates a new prior for each bootstrap replications ... (need to add)
Usage
rvalueBoot(object, statistic = median, R, type = "nonparametric")
Arguments
object |
An object of class "rvals" |
statistic |
The statistic used to summarize the bootstrap replicates. |
R |
Number of bootstrap replicates |
type |
Either |
Details
When type="nonparametric"
, the prior is re-estimated (using the resampled data)
in each bootstrap replication, and r-values are re-computed with respect to this new model.
When type="parametric"
,
Value
A list with the following two components
rval.repmat |
A matrix where each column corresponds to a separate bootstrap replication. |
rval.boot |
A vector of r-values obtained by applying the statistic to each row
of |
Author(s)
Nicholas Henderson and Michael Newton
References
Henderson, N.C. and Newton, M.A. (2016). Making the cut: improved ranking and selection for large-scale inference. J. Royal Statist. Soc. B., 78(4), 781-804. doi: 10.1111/rssb.12131 https://arxiv.org/abs/1312.5776
See Also
Examples
## Not run:
n <- 3000
theta <- rnorm(n, sd = 3)
ses <- sqrt(rgamma(n, shape = 10, rate = 1))
XX <- theta + ses*rnorm(n)
dd <- cbind(XX,ses)
rv <- rvalues(dd, family = gaussian, prior = "conjugate")
rvb <- rvalueBoot(rv, R = 10)
summary(rvb$rval.repmat[512,])
## End(Not run)