Estimate hyperparameters for hierarchical variance model for continuous component

Source: R/ebayes-helpers.R

ebayesControl is a named list with (optional) components 'method' (one of 'MOM' or 'MLE') and 'model' (one of 'H0' or 'H1') method MOM uses a method-of-moments estimator, while MLE using the marginal likelihood. H0 model estimates the precisions using the intercept alone in each gene, while H1 fits the full model specified by mm

ebayes(assay_t, ebayesControl, mm, truncate = Inf)

Arguments

assay_t

cells X genes matrix

ebayesControl

list with (optional) components 'method', 'model'. See details.

mm

a model matrix, used when model='H1'.

truncate

Genes with sample precisions exceeding this value are discarded when estimating the hyper parameters

Value

numeric of length two, giving the hyperparameters in terms of a variance (v) and prior observations (df), inside a structure, with component hess, giving the Fisher Information of the hyperparameters.