penalty_BirgeMassart_shape1
is the penalty shape defined by :
pen_shape = (sqrt(K) + sqrt(2 * K * L_K))^2 with sum(exp(- K * L_K)) < infty :
L_K = B + 1/K * log(model_complexity).
penalty_BirgeMassart_shape1(K, p, model_complexity, B = 0.1)
value of the penalty
the number of shifts
the dimension of the data
the complexity of the set of models with dimension K
a non-negative constant. Default is 0.1 (as suggested in Cleynen & Lebarbier 2015)
See Birgé Massart (2001). Must be applied to least-square criterion. This penalty should be calibrated using the slope heuristic.
penalty_BaraudGiraudHuet_likelihood
,
penalty_BirgeMassart_shape2