Functions for generating prior functions for use with
mcmc, etc.
Usage
make.prior.exponential(r)
Arguments
r
Scalar or vector of rate parameters
Details
The prior probability distribution has probability density
$$\sum_i r_i e^{-r_i x_i}$$ where the
$i$ denotes the $i$th parameter. If r is a scalar,
then the same rate is used for all parameters.
This function returns a function that may be used as the prior
argument to the likelihood functions returned elsewhere.