optimize_variance: Optimizes variance

Description Usage Arguments Details Value

Description

Finds the prior parameter that maximizes the marginal likelihood given the prediction.

Usage

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calc.a(y, mu, sf)

calc.b(y, mu, sf)

calc.k(y, mu, sf)

Arguments

y

A vector of observed gene counts.

mu

A vector of predictions from expr.predict.

sf

Vector of normalized size factors.

Details

calc.a returns a prior alpha parameter assuming constant coefficient of variation. calc.b returns a prior beta parameter assuming constant Fano factor. calc.k returns a prior variance parameter assuming constant variance.

Value

A vector with the optimized parameter and the negative log-likelihood.


SAVER documentation built on Nov. 14, 2019, 1:06 a.m.