cICS_L: C++ function to estimate Pitman-Yor univariate mixtures via...

In BNPmix: Bayesian Nonparametric Mixture Models

C++ function to estimate Pitman-Yor univariate mixtures via importance conditional sampler - LOCATION

Description

C++ function to estimate Pitman-Yor univariate mixtures via importance conditional sampler - LOCATION

Arguments

data	a vector of observations
grid	vector to evaluate the density
niter	number of iterations
nburn	number of burn-in iterations
m0	expectation of location component
s20	variance of location component
a0	parameter of scale component
b0	parameter of scale component
m1	hyperparameter, mean of distribution of m0
k1	hyperparameter, scale factor of distribution of m0
a1	hyperparameter, shape of distribution of s20
b1	hyperparameter, scale of distribution of s20
strength	parameter
napprox	number of approximating values
nupd	number of iterations to show current updating
out_param	if TRUE, return also the location and scale paramteres lists
out_dens	if TRUE, return also the estimated density (default TRUE)
discount	discount parameter
print_message	print the status
hyper,	if TRUE use hyperpriors, default TRUE

BNPmix documentation built on July 16, 2022, 1:04 a.m.