NMixMCMC
. It computes
estimates of univariate conditional densities obtained by using posterior
summary statistics (e.g., posterior means) of mixture weights, means
and variances (plug-in estimate).NMixPlugCondDensMarg(x, ...)## S3 method for class 'default':
NMixPlugCondDensMarg(x, icond, scale, w, mu, Sigma, \dots)
## S3 method for class 'NMixMCMC':
NMixPlugCondDensMarg(x, icond, grid, lgrid=50, scaled=FALSE, \dots)
## S3 method for class 'GLMM_MCMC':
NMixPlugCondDensMarg(x, icond, grid, lgrid=50, scaled=FALSE, \dots)
NMixMCMC
for
NMixPlugCondDensMarg.NMixMCMC
function. An object of class GLMM_MCMC
for
NMixPlugCondDensMarg.GLMM_MCMC
function.
A list with the grid values (see be
shift
and the
scale
. If not given, shift is equal to zero and scale is
equal to one.mu
has
$K$ rows and $p$ columns, where $K$ denotes the number
of mixture components and $p$ is dimension of the mixture
distribution.grid[[icond]]
determines the values by which we condition. If grid
is not specified, it is created automatically usin
grid
if
that is not specified.TRUE
, the density of shifted and scaled data is
summarized. The shift and scale vector are taken from the
scale
component of the object x
.NMixPlugCondDensMarg
which has the following components:x1
, ...or take names from
grid
argument.x[[icond]]
. Each dens[[j]]
is again a list
with conditional densities for each margin given margin
icond
equal to x[[icond]][j]
.
The value of dens[[j]][[imargin]]
gives a value
of a marginal density of the imargin
-th margin at x[[icond]][j]
.plot
method implemented for the resulting object.plot.NMixPlugCondDensMarg
, NMixMCMC
, GLMM_MCMC
, NMixPredCondDensMarg
.