vectorised_multi {ProteoBayes}

Vectorised version of multi_posterior_mean()

Description

Alternative vectorised version, highly efficient when nb_peptide < 30.

Usage

vectorised_multi(data, mu_0 = NULL, lambda_0 = 1, Sigma_0 = NULL, nu_0 = 10)

Arguments

data

A tibble or data frame containing imputed data sets for all groups. Required columns: Peptide, Group, Sample, Output. If missing data have been estimated from multiple imputations, each imputation should be identified in an optional Draw column.

mu_0

A vector, corresponding to the prior mean. If NULL, all groups are initialised with the same empirical mean for each peptide.

lambda_0

A number, corresponding to the prior covariance scaling parameter.

Sigma_0

A matrix, corresponding to the prior covariance parameter. If NULL, the identity matrix will be used by default.

nu_0

A number, corresponding to the prior degrees of freedom.

Value

A tibble providing the parameters of the posterior t-distribution for the mean of the considered groups for each peptide.

Examples

TRUE