plotPriors: Plot prior using parameter vector
In GRENITS: Gene Regulatory Network Inference Using Time Series

Description Usage Arguments Details References See Also Examples

Plot appropriate priors using parameters from vector

1	plotPriors(parameter.vec)

parameter.vec

MCMC parameter vector of the type generated by e.g. mcmc.defaultParams_Linear

This function takes the parameter vector that will be used for network inference function and plots the priors associated with the parameters given.

Morrissey, E.R., Juarez, M.A., Denby, K.J. and Burroughs, N.J. 2010. On reverse engineering of gene interaction networks using time course data with repeated measurements. Bioinformatics 2010; doi: 10.1093/bioinformatics/btq421

Morrissey, E.R., Juarez, M.A., Denby, K.J. and Burroughs, N.J. 2011 Inferring the time-invariant topology of a nonlinear sparse gene regulatory network using fully Bayesian spline autoregression Biostatistics 2011; doi: 10.1093/biostatistics/kxr009

mcmc.defaultParams_gauss, mcmc.defaultParams_Linear, mcmc.defaultParams_nonLinear , mcmc.defaultParams_student .

    # Get default parameters
    nonLinearNet.params <- mcmc.defaultParams_nonLinear()

    # Change run length
    nonLinearNet.params[1] <- 150000

    # Change prior on smoothness parameter
    nonLinearNet.params[6] <- 30000 # Change truncation 
    nonLinearNet.params[12] <- 3 # Concentrate more mass close to linear region

    # Plot to check changes
    plotPriors(nonLinearNet.params)