This function serves as an inference tool for the MCMC output
obtained using the function NMixMCMC. It computes
(posterior predictive) estimates of univariate conditional cumulative distribution functions.
NMixPredCondCDFMarg(x, ...)# S3 method for default
NMixPredCondCDFMarg(x, icond, prob, scale, K, w, mu, Li, Krandom=FALSE, ...)
# S3 method for NMixMCMC
NMixPredCondCDFMarg(x, icond, prob, grid, lgrid=50, scaled=FALSE, ...)
# S3 method for GLMM_MCMC
NMixPredCondCDFMarg(x, icond, prob, grid, lgrid=50, scaled=FALSE, ...)
An object of class NMixPredCondCDFMarg 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 cdf's for each
value of x[[icond]]. Each cdf[[j]] is again a list
with conditional cdf's for each margin given margin
icond equal to x[[icond]][j].
The value of cdf[[j]][[imargin]] gives a value
of a marginal cdf of the imargin-th margin at x[[icond]][j].
a value of the argument prob.
if prob is given then there is one
additional component named “qXX%”, e.g., “q50%” for
each value of prob which has the same structure as the
component cdf and keeps computed posterior pointwise
quantiles.
There is also a plot method implemented for the resulting object.
an object of class NMixMCMC for
NMixPredCondCDFMarg.NMixMCMC function.
An object of class GLMM_MCMC for
NMixPredCondCDFMarg.GLMM_MCMC function.
A list with the grid values (see below) for
NMixPredCondCDFMarg.default function.
index of the margin by which we want to condition
a numeric vector. If given then also the posterior
pointwise quantiles of the conditional cdf's are computed for
probabilities given by prob. These can be used to draw
pointwise credible intervals.
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 cdf 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 cdf 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.NMixPredCondCDFMarg, NMixMCMC, GLMM_MCMC.