rvaluesMCMC {rvalues}

R-values from MCMC output.

Description

Returns r-values from an array of MCMC output.

Usage

rvaluesMCMC(output, qtheta, alpha.grid = NULL, ngrid = NULL, smooth = "none")

Arguments

output

a matrix contatining mcmc ouput. The ith row should represent a sample from the posterior of the ith parameter of interest.

qtheta

either a function which returns the quantiles (for upper tail probs.) of theta or a vector of theta-quantiles.

alpha.grid

grid of values in (0,1); used for the discrete approximation approach for computing r-values.

ngrid

number of grid points for alpha.grid; only relevant when alpha.grid = NULL

smooth

either smooth="none" or smooth takes a value between 0 and 10; this determines the level of smoothing applied to the estimate of \lambda(\alpha); if smooth is given a number, the number is used as the bass argument in supsmu.

Value

An object of class "rvals" which is a list containing at least the following components:

main

a data frame containing the r-values, the r-value rankings along with the rankings from several other common procedures

aux

a list containing other extraneous information

rvalues

a vector of r-values

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

rvalues, PostSummaries

Examples

data(MCMCtest)

### For the MCMC output in MCMC_test, the prior assumed for the effect sizes of 
### interest was a mixture of two t-distributions. The function qthetaTMix 
### computes the quantiles for this prior.

qthetaTMix <- function(p) {
    ### function to compute quantiles (for upper tail probabilities) for a 
    ###  mixture of two t-distributions
    mu <- c(.35,-.12)
    sig <- c(.2,.08)
    mix.prop <- c(.25,.75)

    ff <- function(x,pp) {
        prob_less <- 0
        for(k in 1:2) {
            prob_less <- prob_less + pt((x - mu[k])/sig[k],df=4,lower.tail=FALSE)*mix.prop[k] 
        }
        return(prob_less - pp)
    }

    nn <- length(p)
    ans <- numeric(nn)
    for(i in 1:nn) {
        ans[i] <- uniroot(ff,interval=c(-5,5),tol=1e-6,pp=p[i])$root
    }
    return(ans)
}

rvs <- rvaluesMCMC(MCMCtest, qtheta = qthetaTMix)