NMixMCMC. It computes
(posterior predictive) estimates of pairwise bivariate conditional
densities (given one margin).
NMixPredCondDensJoint2(x, ...)
"NMixPredCondDensJoint2"(x, icond, scale, K, w, mu, Li, Krandom=FALSE, ...)
"NMixPredCondDensJoint2"(x, icond, grid, lgrid=50, scaled=FALSE, ...)
"NMixPredCondDensJoint2"(x, icond, grid, lgrid=50, scaled=FALSE, ...)NMixMCMC for
NMixPredCondDensJoint2.NMixMCMC function. An object of class GLMM_MCMC for
NMixPredCondDensJoint2.GLMM_MCMC function.
A list with the grid values (see below) for
NMixPredCondDensJoint2.default function.
shift and the
scale. If not given, shift is equal to zero and scale is
equal to one.
Krandom$=$FALSE) or a
numeric vector with the chain for the number of mixture components.grid[[icond]]
determines the values by which we condition. If grid is not specified, it is created automatically using
the information from the posterior summary statistics stored in x.
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.
NMixPredCondDensJoint2 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.NMixPredCondDensJoint2, NMixMCMC, GLMM_MCMC.