Description Usage Arguments Value Author(s) See Also Examples
Generates an MCMC model fit of the BaySIC BMR model
1  baysic.fit(dat.out, snv.cat, covar = NULL, excl.list = NULL, burn.in = 10000,n.samp = 25000, fn.jags = "baysic.jags", prior = NULL)

dat.out 
Output from 
snv.cat 
a 
covar 
optional G \times Q matrix of genelevel covariate data, where G is the total number of genes and Q the number of covariates. 
excl.list 
optional vector of genes to be excluded from model fitting process. The format of 
burn.in 
an integer; represents the burnin size to apply in the MCMC model fitting using JAGS. Defaults to 10,000 
n.samp 
an integer; represents the size of the MCMC posterior sample draw from the fitted model. Defaults to 25,000 
fn.jags 
a character string; corresponds to the file name and location of the JAGS model file to be written. Defaults to "baysic.jags" in the current working directory. 
prior 
optional vector of prior distribution specifications (as character strings). If 
Returns a list
object with the following components:
fit.post 
an 
covar 

snv.cat 
the 
excl.list 

Nicholas B. Larson
1 2 3 4 5 6 7 8 9 10 11  ## Not run:
data(example.dat)
data(ccds.19)
baysic.dat.ex<baysic.data(example.dat,ccds.19)
snv.cat.ex<list()
snv.cat.ex[[1]]<grep("[^T]C[^G]",colnames(ccds.19)[c(1:2)])
snv.cat.ex[[2]]<unique(c(grep("TC.",colnames(ccds.19)[c(1:2)]),grep(".CG",colnames(ccds.19)[c(1:2)])))
snv.cat.ex[[3]]<grep(".T.",colnames(ccds.19)[c(1:2)])
baysic.fit.ex<baysic.fit(baysic.dat.ex,snv.cat.ex)
## End(Not run)

Loading required package: rjags
Loading required package: coda
Linked to JAGS 4.2.0
Loaded modules: basemod,bugs
Loading required package: fields
Loading required package: spam
Loading required package: dotCall64
Loading required package: grid
Spam version 2.11 (20170702) is loaded.
Type 'help( Spam)' or 'demo( spam)' for a short introduction
and overview of this package.
Help for individual functions is also obtained by adding the
suffix '.spam' to the function name, e.g. 'help( chol.spam)'.
Attaching package: 'spam'
The following objects are masked from 'package:base':
backsolve, forwardsolve
Loading required package: maps
Loading required package: poibin
Compiling model graph
Resolving undeclared variables
Allocating nodes
Graph information:
Observed stochastic nodes: 4
Unobserved stochastic nodes: 4
Total graph size: 41
Initializing model
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