mixAK (version 0.4)

NMixPredCondDensJoint2: Pairwise bivariate conditional predictive densities

Description

This function serves as an inference tool for the MCMC output obtained using the function 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).

Usage

NMixPredCondDensJoint2(x, ...)
## S3 method for class 'default':
NMixPredCondDensJoint2(x, icond, scale, K, w, mu, Li, Krandom=FALSE, \dots)
## S3 method for class 'NMixMCMC':
NMixPredCondDensJoint2(x, icond, grid, lgrid=50, scaled=FALSE, \dots)

Arguments

x

an object of class NMixMCMC for NMixPredCondDensJoint2.NMixMCMC function.

A list with the grid values (see below) for NMixPredCondDensJoint2.default function.

icond

index of the margin by which we want to condition

scale

a two component list giving the shift and the scale. If not given, shift is equal to zero and scale is equal to one.

K

either a number (when Krandom$=$FALSE) or a numeric vector with the chain for the number of mixture components.

w

a numeric vector with the chain for the mixture weights.

mu

a numeric vector with the chain for the mixture means.

Li

a numeric vector with the chain for the mixture inverse variances (lower triangles only).

Krandom

a logical value which indicates whether the number of mixture components changes from one iteration to another.

grid

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 usin

lgrid

a length of the grid used to create the grid if that is not specified.

scaled

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.

Value

• An object of class NMixPredCondDensJoint2 which has the following components:
• x
  a list with the grid values for each margin. The components of the list are named x1, ...or take names from grid argument.
• icond
  index of the margin by which we condition.
• dens
  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.

See Also

plot.NMixPredCondDensJoint2, NMixMCMC.