initial_variational_gaussian {lnmCluster}R Documentation

Gives default initial guesses for logistic-normal multinomial biclustering algorithm.

Description

Gives default initial guesses for logistic-normal multinomial biclustering algorithm.

Usage

initial_variational_gaussian(W_count, G, Q_g, cov_str, X)

Arguments

W_count

The microbiome count matrix that you want to analyze.

G

The number of component

Q_g

The number of biclusters for each component, a vector.

cov_str

The covaraince structure you choose, there are 16 different models belongs to this family:UUU, UUG, UUD, UUC, UGU, UGG, UGD, UGC, GUU, GUG, GUD, GUC, GGU, GGG, GGD, GGC.

X

The regression covariates matrix, which generated by model.matrix.

Value

new_pi_g Initial guess of proportion

new_mu_g Initial guess of mean vector

new_sig_g Initial guess of covariance matrix for each component

new_T_g Initial guess of covariance of latent variable: u

new_B_g Initial guess of bicluster membership

new_D_g Initial guess of error matrix

new_m Initial guess of variational mean

new_V Initial guess of variational varaince

new_beta_g Initial guess of covariates coefficients.


[Package lnmCluster version 0.3.1 Index]