plotPriors {GRENITS} | R Documentation

## 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)

[Package GRENITS version 1.39.0 Index]