ve_step: E-Step of the VEM algorithm

In MagmaClustR: Clustering and Prediction using Multi-Task Gaussian Processes with Common Mean

E-Step of the VEM algorithm

Description

Expectation step of the Variational EM algorithm used to compute the parameters of the hyper-posteriors distributions for the mean processes and mixture variables involved in MagmaClust.

Usage

ve_step(db, m_k, kern_k, kern_i, hp_k, hp_i, old_mixture, iter, pen_diag)

Arguments

db	A tibble or data frame. Columns required: ID, Input, Output. Additional columns for covariates can be specified.
m_k	A named list of vectors, corresponding to the prior mean parameters of the K mean GPs.
kern_k	A kernel function, associated with the K mean GPs.
kern_i	A kernel function, associated with the M individual GPs.
hp_k	A named vector, tibble or data frame of hyper-parameters associated with kern_k.
hp_i	A named vector, tibble or data frame of hyper-parameters associated with kern_i.
old_mixture	A list of mixture values from the previous iteration.
iter	A number, indicating the current iteration of the VEM algorithm.
pen_diag	A number. A jitter term, added on the diagonal to prevent numerical issues when inverting nearly singular matrices.

Value

A named list, containing the elements mean, a tibble containing the Input and associated Output of the hyper-posterior mean parameters, cov, the hyper-posterior covariance matrices, and mixture, the probabilities to belong to each cluster for each individual.

Examples

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MagmaClustR documentation built on June 29, 2024, 1:06 a.m.