log_comp_dens_conv.normalmix

a list with components x and s to be interpreted as a normally-distributed observation and its standard error

data


returns log-density of convolution of each component
    of a normal mixture with N(0,s^2) or s*t(v) at x. Note that
    convolution of two normals is normal, so it works that way


The R package 'ashr' implements an Empirical Bayes approach for large-scale hypothesis testing and false discovery rate (FDR) estimation based on the methods proposed in M. Stephens, 2016, "False discovery rates: a new deal", <DOI:10.1093/biostatistics/kxw041>. These methods can be applied whenever two sets of summary statistics---estimated effects and standard errors---are available, just as 'qvalue' can be applied to previously computed p-values. Two main interfaces are provided: ash(), which is more user-friendly; and ash.workhorse(), which has more options and is geared toward advanced users.

log_comp_dens_conv.normalmix: log_comp_dens_conv.normalmix

Description

Usage

Arguments

Value