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.