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,...)## Default S3 method:NMixPredCondDensJoint2(x, icond, scale, K, w, mu, Li, Krandom=FALSE,...)## S3 method for class 'NMixMCMC'NMixPredCondDensJoint2(x, icond, grid, lgrid=50, scaled=FALSE,...)## S3 method for class 'GLMM_MCMC'NMixPredCondDensJoint2(x, icond, grid, lgrid=50, scaled=FALSE,...)
Arguments
x: 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.
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 using the information from the posterior summary statistics stored in x.
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.
Returns
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.