predict.fPi0: Predict the functional proportion

In StoreyLab/fFDR: Functional FDR for multiple hypothesis testing

Description

Predict the values of the functional proportion when it is evaluated at a vector z' whose entries are between 0 and 1.

Usage

## S3 method for class 'fPi0'
predict(object, z0 = NULL, z = NULL, lambda = NULL, ...)

Arguments

object	fPi0 object
z0	New z0 values (when they are between 0 and 1)
z	New z values (as the quantile transformed values of z0)
lambda	The value of the tuning parameter to be used for prediction. If null, defaults to the lambda chosen in the fPi0 object
...	Extra arguments, not used

Details

Assume the random variable z0 may affect the power of a statistical test (that induces the p-values) or the likelihood of a true null hypothesis. The m observations z0_i, i=1,...,m of z0 are quantile transformed into z_i, i=1,...,m such that z_i = rank(z0_i) / m, where rank(z0_i) is the rank of z0_i among z0_i, i=1,...,m. Consequently, z_i, i=1,...,m are approximately uniformly distributed on the interval [0,1]. When z_i, i=1,...,m are regarded as observations from the random variable z, then z is approximately uniformly distributed on [0,1]. Namely, z0 has been quantile transformed into z, and they are equivalent. Further, z or z0 is referred to as the informative variable.

Value

Vector of fPi0 predictions

StoreyLab/fFDR documentation built on March 8, 2021, 10:14 p.m.