NMixMCMC
. It computes
estimates of pairwise bivariate conditional densities (given one margin)
obtained by using posterior summary statistics (e.g., posterior means)
of mixture weights, means and variances (plug-in estimate).NMixPlugCondDensJoint2(x, ...)## S3 method for class 'default':
NMixPlugCondDensJoint2(x, icond, scale, w, mu, Sigma, \dots)
## S3 method for class 'NMixMCMC':
NMixPlugCondDensJoint2(x, icond, grid, lgrid=50, scaled=FALSE, \dots)
## S3 method for class 'GLMM_MCMC':
NMixPlugCondDensJoint2(x, icond, grid, lgrid=50, scaled=FALSE, \dots)
NMixMCMC
for
NMixPlugCondDensJoint2.NMixMCMC
function. An object of class GLMM_MCMC
for
NMixPlugCondDensJoint2.GLMM_MCMC
function.
A list with the grid values (se
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
.NMixPlugCondDensJoint2
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 pair of margins given margin
icond
equal to x[[icond]][j]
.
The value of dens[[j]][[i-k]]
gives values
of conditional density of the (i,k)-th margins given margin
icond
equal to x[[icond]][j]
.plot
method implemented for the resulting object.plot.NMixPlugCondDensJoint2
, NMixMCMC
, GLMM_MCMC
, NMixPredCondDensJoint2
.