choosePriors: Function to plot an overview of possible priors for the...
In ARTIVA: Time-Varying DBN Inference with the ARTIVA (Auto Regressive TIme VArying) Model

Description Usage Arguments Value Author(s) References See Also Examples

Plots an overview of some possible priors used in the ARTIVAsubnet function for the number of changepoints (resp. incoming edges) according to a given number of maximum changepoints maxCP (resp. incoming Edges maxPred) when parameters (alphaCP, betaCP for the CPs or alphaEdges, betaEdges for the edges) in function ARTIVAsubnet are set to default (alpha=1, beta=0.5). In the ARTIVAsubnet procedure, the number of CPs (respectively the number of incoming edges) is sampled from a truncated Poisson with mean lambda, where lambda is drawn from an Inverse Gamma distribution (alpha, beta), see Lebre et al. (2010) for more details.

1	choosePriors(kmax,priors)

`kmax`	Maximum number of changepoints or incomins Edges (parents)
`priors`	Table describing the priors which can be loaded with data(priors)

NULL, a graph is plotted.

S. Lebre and G. Lelandais.

S. Lebre, J. Becq, F. Devaux, M. P. H. Stumpf, G. Lelandais (2010) Statistical inference of the time-varying structure of gene-regulation networks, BMC Systems Biology, 4:130.

ARTIVAsubnet, ARTIVAnet

# See some prior probabbility density when the maximal number of
# CPs/parents is equal to 5
data(priors)
choosePriors(kmax=5,priors)

Loading required package: MASS
Loading required package: igraph

Attaching package: 'igraph'

The following objects are masked from 'package:stats':

    decompose, spectrum

The following object is masked from 'package:base':

    union

Loading required package: gplots

Attaching package: 'gplots'

The following object is masked from 'package:stats':

    lowess