GRENITS (version 1.24.0)

plotPriors: Plot prior using parameter vector

Description

Plot appropriate priors using parameters from vector

Usage

plotPriors(parameter.vec)

Arguments

parameter.vec

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

Details

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

References

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

See Also

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

Examples

    # 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)