View source: R/model_selection.R
penalty_BirgeMassart_shape1 | R Documentation |
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)
K |
the number of shifts |
p |
the dimension of the data |
model_complexity |
the complexity of the set of models with dimension K |
B |
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.
value of the penalty
penalty_BaraudGiraudHuet_likelihood
,
penalty_BirgeMassart_shape2
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