assign.convergence.RdThe assign.convergence checks the convergence of the MCMC chain of the model parameters generated by the Gibbs sampling algorithm.
assign.convergence(test, burn_in = 0, iter = 2000, parameter = c("B", "S", "Delta", "beta", "kappa", "gamma", "sigma"), whichGene, whichSample, whichPath)
| test | The list object returned from the assign.mcmc function. The list components are the MCMC chains of the B, S, Delta, beta, gamma, and sigma. |
|---|---|
| burn_in | The number of burn-in iterations. These iterations are discarded when computing the posterior means of the model parameters. The default is 0. |
| iter | The number of total iterations. The default is 2000. |
| parameter | A character string indicating which model parameter is to be checked for convergence. This must be one of "B", "S", "Delta", "beta", "kappa", "gamma", and "sigma". |
| whichGene | A numerical value indicating which gene is to be checked for convergence. The value has to be in the range between 1 and G. |
| whichSample | A numerical value indicating which test sample is to be checked for convergence. The value has to be in the range between 1 and N. |
| whichPath | A numerical value indicating which pathway is to be checked for convergence. The value has to be in the range between 1 and K. |
The assign.convergence function returns the a vector of the estimated values from each Gibbs sampling iteration of the model parameter to be checked, and a trace plot of this parameter.
To compute the convergence of the gth gene in B, set whichGene=g, whichSample=NA, whichPath=NA.
To compute the convergence of the gth gene in the kth pathway within the signature matrix (S), set whichGene=g, whichSample=NA, whichPath=NA.
To compute the convergence of the kth pathway in the jth test sample within the pathway activation matrix (A), set whichGene=NA, whichSample=n, whichPath=k.
# NOT RUN { # check the 10th gene in the 1st pathway for the convergence trace.plot <- assign.convergence(test=mcmc.chain, burn_in=0, iter=2000, parameter="S", whichGene=10, whichSample=NA, whichPath=1) # }