vm_step {MagmaClustR} | R Documentation |
V-Step of the VEM algorithm
Description
Maximization step of the Variational EM algorithm used to compute hyper-parameters of all the kernels involved in MagmaClust.
Usage
vm_step(
db,
old_hp_k,
old_hp_i,
list_mu_param,
kern_k,
kern_i,
m_k,
common_hp_k,
common_hp_i,
pen_diag
)
Arguments
db |
A tibble or data frame. Columns required: ID, Input, Output. Additional columns for covariates can be specified. |
old_hp_k |
A named vector, tibble or data frame, containing the hyper-parameters from the previous M-step (or initialisation) associated with the mean GPs. |
old_hp_i |
A named vector, tibble or data frame, containing the hyper-parameters from the previous M-step (or initialisation) associated with the individual GPs. |
list_mu_param |
List of parameters of the K mean GPs. |
kern_k |
A kernel used to compute the covariance matrix of the mean GP at corresponding timestamps. |
kern_i |
A kernel used to compute the covariance matrix of individuals GP at corresponding timestamps. |
m_k |
A named list of prior mean parameters for the K mean GPs. Length = 1 or nrow(unique(db$Input)) |
common_hp_k |
A boolean indicating whether hp are common among mean GPs (for each mu_k) |
common_hp_i |
A boolean indicating whether hp are common among individual GPs (for each y_i) |
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 hp_k
, a tibble
containing the hyper-parameters associated with each cluster,
hp_i
, a tibble containing the hyper-parameters
associated with the individual GPs, and prop_mixture_k
,
a tibble containing the hyper-parameters associated with each individual,
indicating the probabilities to belong to each cluster.
Examples
TRUE