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.