computeRho4 {EDISON} | R Documentation |
This function calculates the frequency at which each of the different changepoint moves is proposed. For the poisson network structure prior, this ensures that the proposal frequency is equal to the prior probability.
computeRho4(k, kmin, kmax, c, lambda)
k |
The number of hidden states. |
kmin |
Minimum number of hidden states. |
kmax |
Maximum number of hidden states |
c |
Parameter. |
lambda |
Hyperparameter controlling the number of hidden states. |
Vector containing the proposal frequencies for the different changepoint moves.
Sophie Lebre
For more information about the hyperparameters and the functional form of the likelihood, see:
Dondelinger et al. (2012), "Non-homogeneous dynamic Bayesian networks with Bayesian regularization for inferring gene regulatory networks with gradually time-varying structure", Machine Learning.