| sampleParms {EDISON} | R Documentation |
Sample initial parameters for the MCMC simulation.
Description
This function samples the initial hyperparameters and parameters that are needed for the MCMC simulation.
Usage
sampleParms(X, GLOBvar, HYPERvar, s_init = NULL, options)
Arguments
X |
Input data. |
GLOBvar |
Global variables of the MCMC simulation. |
HYPERvar |
Hyperparameter variables. |
s_init |
Initial number of changepoints. |
options |
MCMC options, as given by e.g. |
Value
Returns a list with elements:
E |
The initial changepoint vector. |
S |
The intial networks structure. |
B |
The initial regression parameters. |
Sig2 |
The inital sigma squared variances. |
betas |
The intial hyperparameters for the exponential information sharing prior. |
hyper_params |
The initial hyperparameters for the binomial information sharing prior. |
Author(s)
Sophie Lebre
Frank Dondelinger
References
For more information about the parameters and hyperparameters, 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.