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