- D
number of multinomial categories
-- N
+- N
number of samples
-- Q
+- Q
number of covariates
-- P
+- P
number of variance components
-- coord_system
+- coord_system
coordinate system objects are represented in (options
include "alr", "clr", "ilr", and "proportions")
-- iter
+- iter
number of posterior samples
-- alr_base
+- alr_base
integer category used as reference
(required if coord_system=="alr")
-- ilr_base
+- ilr_base
(D x D-1) contrast matrix (required if coord_system=="ilr")
-- Eta
+- Eta
Array of samples of Eta
-- Lambda
+- Lambda
Array of samples of Lambda
-- Sigma
+- Sigma
Array of samples of Sigma (null if coord_system=="proportions")
-- Sigma_default
+- Sigma_default
Array of samples of Sigma in alr base D, used if
coord_system=="proportions"
-- Y
+- Y
DxN matrix of observed counts
-- X
+- X
QxN design matrix
-- upsilon
+- upsilon
scalar prior dof of inverse wishart prior
-- Theta
+- Theta
prior mean of Lambda
-- Xi
+- Xi
Matrix of prior covariance for inverse wishart
(null if coord_system=="proportions")
-- Xi_default
+- Xi_default
Matrix of prior covariance for inverse wishart in alr
base D (used if coord_system=="proportions")
-- Gamma
+- Gamma
QxQ covariance matrix prior for Lambda
-- init
+- init
matrix initial guess for Lambda used for optimization
-- ellinit
+- ellinit
P vector initialization values for ell for optimization
-- names_categories
+- names_categories
character vector
-- names_samples
+- names_samples
character vector
-- names_covariates
+- names_covariates
character vector
-- VCScale
+- VCScale
scale factors (delta) for variance components
-- U
+- U
a PQ x Q matrix of stacked variance components (each of dimension Q x Q)