ComputeLogLikelihood: Compute the log-likelihood for a given mixture model.

In tohein/linearMTL: Linear Models for Multi-Task Learning

Description

Compute the log-likelihood for a given mixture model.

Usage

ComputeLogLikelihood(models, prior, sigmas, X = NULL,
  task.specific.features = list(), Y)

Arguments

models	List of TGGL models.
prior	Vector of prior probabilities for each component.
sigmas	M by K Matrix of standard deviations.
X	N by J1 matrix of features common to all tasks.
task.specific.features	List of features which are specific to each task. Each entry contains an N by J2 matrix for one particular task (where columns are features). List has to be ordered according to the columns of Y.
Y	N by K output matrix for every task.

Value

Log-likelihood.

tohein/linearMTL documentation built on May 17, 2019, 8:22 a.m.