gmgm (version 1.1.2)

logLik: Compute the log-likelihood of a Gaussian mixture model or graphical model

Description

This function computes the log-likelihood of a Gaussian mixture model or graphical model.

Usage

# S3 method for gmm
logLik(object, data, y = NULL, regul = 0.01, ...)
# S3 method for gmbn
logLik(object, data, col_seq = NULL, ...)
# S3 method for gmdbn
logLik(object, data, col_seq = NULL, ...)

Value

If object is a gmm object, a numeric value corresponding to the log-likelihood.

If object is a gmbn or gmdbn object, a list with elements:

global

A numeric value corresponding to the global log-likelihood.

local

For a gmbn object, a numeric vector containing the local conditional log-likelihoods. For a gmdbn object, a list of numeric vectors containing these values for each gmbn element.

Arguments

object

An object of class gmm, gmbn or gmdbn.

data

A data frame containing the data used to compute the log-likelihood. Its columns must explicitly be named after the variables (or nodes) of object. If object is a gmm object, a numeric matrix can be passed.

y

A character vector containing the dependent variables if a conditional log-likelihood is computed. If NULL (the default), the joint log-likelihood is computed.

regul

A positive numeric value corresponding to the regularization constant if a penalty term is added for Bayesian regularization. If NULL, no penalty term is added. If a conditional log-likelihood is computed, this argument is ignored.

...

Unused arguments from the generic function.

col_seq

A character vector containing the column names of data that describe the observation sequence. If NULL (the default), all the observations belong to a single sequence. If object is a temporal gmbn or gmdbn object, the observations of a same sequence must be ordered such that the \(t\)th one is related to time slice \(t\) (note that the sequences can have different lengths). If object is a non-temporal gmbn object, this argument is ignored.

See Also

AIC, BIC

Examples

data(gmm_body, data_body)
loglik_1 <- logLik(gmm_body, data_body)
loglik_2 <- logLik(gmm_body, data_body, y = "WAIST")

data(gmbn_body, data_body)
loglik_3 <- logLik(gmbn_body, data_body)

data(gmdbn_air, data_air)
loglik_4 <- logLik(gmdbn_air, data_air, col_seq = "DATE")