A function to compute the Bayesian Information Criterion (BIC), also known as Schwarz's Bayesian criterion (SBC), for the fitted IFA model, according to the formula
-2*log-likelihood + npar*log(nobs), where
npar represents the number of parameters and
nobs the number of observations in the fitted model.
The fitted IFA model object, a list including the log-likelihood, the number of observations and the number of parameters.
It returns a numeric value with the corresponding BIC.
Schwarz, G. (1978) Estimating the Dimension of a Model, Annals of Statistics, 6, 461-464.
Viroli, C. (2005). Choosing the number of factors in Independent Factor Analysis model, Metodoloski Zvezki, Advances in Methodology and Statistics, Vol. II, N. 2, 219-229. Available at $www2.stat.unibo.it/viroli$.
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