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.