'from.mcmc.list' takes a list of chains of class MCMC and returns a list of chains with one component per parameter.  Each component is a matrix whose columns are the chains for that parameter.  The very last component of the output ($doc) is a list of character objects that describe the chains, leaving unknown aspects labeled as "unknown".  

This function appears to work well (5/2/2012), but it is still under development.  It needs much more testing.

'func' takes a n x 2 matrix, and interprets it as a function.
ARGUMENTS:
'mat' is a n x 2 matrix
'x' is particular x value or a vector of x values.
The output is a vector of the function values that are paired
with the x arguments.
Set 'exact=T' if only an exact match on x-value is acceptable.
If 'exact=F', linear interpolation is used to find the
function value.
If 'XY=T' then the output is the (x, f(x)) pair;
Otherwise it is just the f(x) function value.

'\r\rdoc\funslist.htm' is an html document that lists all functions in jmfuns.rda

funlist is a dummy string variable.  doc(funlist) loads the funlist.htm webpage into the default browser.

gamma.parameters returns the parameters of a gamma distribution, given a subset of the parameters, e.g., if given the shape and rate parameters, it returns the mean, sd, and scale parameters. The output is a dataframe that is formatted without scientific notation.
 
gamma.parameters(shape = NA, rate = NA, scale = NA, mean = NA, sd = NA, 
   qt = c(0.01, 0.5, 0.99), digits = 4) 

Arguments:
shape=  shape parameter; 
rate=  rate parameter; 
scale=  scale parameter

mean & sd are the mean and sd of the gamma distribution

User should specify either (i) shape & rate; or (ii) shape & scale; or (iii) mean & sd.

qt are quantiles of the gamma to be displayed.  qt defaults to c( 0.01, 0.50, 0.99).  

digits specifies rounding of the parameters to a maximum of digits.

'get.vars' arguments:
'vn' = a character vector of variable names;
'd.frm' = the name of a dataframe or 'All vars on search path'
if the variables are all on the search path;
'bool' = a boolean vector indicating which variables are
in the dataframe and which are on the search path.
The output is a dataframe whose columns are the variables
named in 'vn'.