countprop (version 1.0.1)

ebic: Extended Bayesian Information Criterion

Description

Calculates the Extended Bayesian Information Criterion (EBIC) of a model. Used for model selection to asses the fit of the multinomial logit-Normal model which includes a graphical lasso penalty.

Usage

ebic(l, n, d, df, gamma)

Value

The value of the EBIC.

Arguments

l

Log-likelihood estimates of the model

n

Number of rows of the data set for which the log-likelihood has been calculated

d

The size of the (k-1) by (k-1) covariance matrix of a k by k count-compositional data matrix

df

Degrees of freedom

gamma

A tuning parameter. Larger values means more penalization

Examples

data(singlecell)
mle <- mleLR(singlecell, lambda.gl=0.5)
log.lik_1 <- mle$est[[1]]$log.lik
n <- NROW(singlecell)
k <- NCOL(singlecell)
df_1 <- mle$est[[1]]$df

ebic(log.lik_1, n, k, df_1, 0.1)