sampleParms: Sample initial parameters for the MCMC simulation.

Description Usage Arguments Value Author(s) References See Also

View source: R/sampleParms.R

Description

This function samples the initial hyperparameters and parameters that are needed for the MCMC simulation.

Usage

1
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. defaultOptions.

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.

See Also

init


EDISON documentation built on May 29, 2017, 3:51 p.m.