penalty_BaraudGiraudHuet_likelihood is the penalty defined by :
pen' = ntaxa * log(1 + pen/(ntaxa - K)) with
pen = C * (ntaxa - K)/(ntaxa - K - 1) * EDkhi[K + 1; ntaxa - K - 1; exp(-Delta_K)/(K + 1)]
and Delta = log(model_complexity) + log(K + 1)
such that sum(exp(-Delta_K)) < infty.
penalty_BaraudGiraudHuet_likelihood(K, model_complexity, ntaxa, C = 1.1)value of the penalty.
the dimension of the model.
the complexity of the set of models with dimension K.
the number of tips.
a constant, C > 1. Default is C = 1.1 (as suggested in Baraud Giraud Huet (2009))
See Baraud Giraud Huet (2009, 2011).
Must be applied to log-likelihood criterion.
Function pen is computed using function penalty from package
LINselect.
penalty_BirgeMassart_shape1,
penalty_BirgeMassart_shape2