Description Usage Arguments Details Value Author(s) Examples
The assign.convergence checks the convergence of the MCMC chain of the model parameters generated by the Gibbs sampling algorithm.
1 2 3 | 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 charater string indicating which model parameter is to be checked for convergency. 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. |
To compute the convergency of the gth gene in B, set whichGene=g, whichSample=NA, whichPath=NA.
To compute the convergency of the gth gene in the kth pathway within the signature matrix (S), set whichGene=g, whichSample=NA, whichPath=NA.
To compute the convergency of the kth pathway in the jth test sample within the pathway activation matrix (A), set whichGene=NA, whichSample=n, whichPath=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.
Ying Shen
1 2 3 4 5 6 | ## Not run:
# check the 10th gene in the 1st pathway for the convergency
trace.plot <- assign.convergence(test=mcmc.chain, burn_in=0, iter=2000, parameter="S",
whichGene=10, whichSample=NA, whichPath=1)
## End(Not run)
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