Create pibblefit object
pibblefit(
D,
N,
Q,
coord_system,
iter = NULL,
alr_base = NULL,
ilr_base = NULL,
Eta = NULL,
Lambda = NULL,
Sigma = NULL,
Sigma_default = NULL,
Y = NULL,
X = NULL,
upsilon = NULL,
Theta = NULL,
Xi = NULL,
Xi_default = NULL,
Gamma = NULL,
init = NULL,
names_categories = NULL,
names_samples = NULL,
names_covariates = NULL
)
object of class pibblefit
number of multinomial categories
number of samples
number of covariates
coordinate system objects are represented in (options include "alr", "clr", "ilr", and "proportions")
number of posterior samples
integer category used as reference (required if coord_system=="alr")
(D x D-1) contrast matrix (required if coord_system=="ilr")
Array of samples of Eta
Array of samples of Lambda
Array of samples of Sigma (null if coord_system=="proportions")
Array of samples of Sigma in alr base D, used if coord_system=="proportions"
DxN matrix of observed counts
QxN design matrix
scalar prior dof of inverse wishart prior
prior mean of Lambda
Matrix of prior covariance for inverse wishart (null if coord_system=="proportions")
Matrix of prior covariance for inverse wishart in alr base D (used if coord_system=="proportions")
QxQ covariance matrix prior for Lambda
matrix initial guess for Lambda used for optimization
character vector
character vector
character vector
pibble