Use the estimated prior from a fitted EBNM model to solve the EBNM problem for new data

The predict method for class ebnm.

# S3 method for class 'ebnm'
predict(object, newdata, s = 1, ...)

Arguments

object: The fitted ebnm object.
newdata: A vector of new observations. Missing observations (NAs) are not allowed.
s: 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. Two prior families have additional restrictions: when horseshoe priors are used, errors must be homoskedastic; and since function deconv in package deconvolveR takes \(z\)-scores, the "deconvolver" family requires that all standard errors be equal to 1.
...: Not used. Included for consistency as an S3 method.

A data frame that includes posterior means, posterior standard deviations, and local false sign rates for the observations in newdata.