This function serves as an inference tool for the MCMC output
obtained using the function NMixMCMC. It computes
(posterior predictive) estimates of pairwise bivariate conditional
densities (given one margin).
NMixPredCondDensJoint2(x, ...)# S3 method for default
NMixPredCondDensJoint2(x, icond, scale, K, w, mu, Li, Krandom=FALSE, ...)
# S3 method for NMixMCMC
NMixPredCondDensJoint2(x, icond, grid, lgrid=50, scaled=FALSE, ...)
# S3 method for GLMM_MCMC
NMixPredCondDensJoint2(x, icond, grid, lgrid=50, scaled=FALSE, ...)
An object of class NMixPredCondDensJoint2 which has the
following components:
a list with the grid values for each margin. The components
of the list are named x1, ... or take names from
grid argument.
index of the margin by which we condition.
a list with the computed conditional densities for each
value of 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].
There is also a plot method implemented for the resulting object.
an object of class 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.
index of the margin by which we want to condition
a two component list giving the shift and the
scale. If not given, shift is equal to zero and scale is
equal to one.
either a number (when Krandom\(=\)FALSE) or a
numeric vector with the chain for the number of mixture components.
a numeric vector with the chain for the mixture weights.
a numeric vector with the chain for the mixture means.
a numeric vector with the chain for the mixture inverse variances (lower triangles only).
a logical value which indicates whether the number of mixture components changes from one iteration to another.
a list with the grid values for each margin in which
the density should be evaluated. The value of 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.
a length of the grid used to create the grid if
that is not specified.
if 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.
optional additional arguments.
Arnošt Komárek arnost.komarek@mff.cuni.cz
plot.NMixPredCondDensJoint2, NMixMCMC, GLMM_MCMC.