Description Usage Arguments Details Value See Also Examples
Defines a probability distribution object for use with
compare.samplers
.
1 2 3 4 
ndim 
The size of the distribution's state space. 
name 
A humanreadable name for the distribution. 
name.expression 
A name for the distribution in

log.density 
A function taking a vector argument that returns the log density of the distribution evaluated at that point. 
grad.log.density 
A function taking a vector argument that returns the gradient of the log density of the distribution evaluated at that point. 
log.density.and.grad 
A function taking a vector argument
and a logical that returns a list with two elements,

initial 
A function that returns an overdispersed initial
state for an MCMC simulation of this distribution, used by

mean 
A vector specifying the true mean of the distribution. 
cov 
A matrix specifying the true covariance of the distribution. 
mean.log.dens 
A scalar specifying the true mean of the log density of the distribution. This will depend on the normalization of the log density function. 
Every distribution must have a name and a dimension. The log density and its gradient are optional; they are used by samplers implemented in R. Samplers implemented in other languages could specifically recognize the name of the distribution instead of calling back into R, though there is a mechanism for C functions to call back. The mean and covariance do not affect sampling, only postsample diagnostics like autocorrelation time.
For many distributions, it is easier to compute the log density
and its gradient at the same time than separately; these will
generally specify log.density.and.grad
and leave
log.density
and log.density.and.grad
as NULL
. The
returned object will fill those in with calls to
log.density.and.grad
. Similarly, if it is simpler to
compute them separately, log.density.and.grad
will be
synthesized from log.density
and grad.log.density
if necessary.
mean
, cov
, and mean.log.dens
values are
intended to be used by diagnostic routines. mean
and
mean.log.dens
are currently used by compare.samplers
when estimating autocorrelation times.
See make.c.dist
for a way to define distributions
whose densities are implemented in C instead of R.
A scdist
object. It has elements with the same names as the arguments
to make.dist
.
compare.samplers
,
make.c.dist
,
check.dist.gradient
,
“R/C Glue in SamplerCompare” (vignette)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20  # A one dimensional Gamma(3,2) distribution.
# So that the density does not return NaN outside the support.
inflog < function(x) ifelse(x<=0, Inf, log(x))
# Define density; unnormalized densities are fine.
gamma32.log.density < function(x) (31)*inflog(x)  x/2
gamma32.grad < function(x) (31)/x  1/2
# Use make.dist to define the distribution object.
gamma32.dist < make.dist(1, 'Gamma32', 'plain("Gamma")(3,2)',
log.density=gamma32.log.density,
grad.log.density=gamma32.grad,
mean=3*2, cov=as.matrix(3*2^2))
# Make sure the log density and gradient agree at an arbitrary point.
check.dist.gradient(gamma32.dist, 17)

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