Gives default initial guesses for penalized logistic-normal multinomial Factor analyzer algorithm.
initial_variational_lasso(W_count, G, Q_g, cov_str, X)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_B_g Initial guess of loading matrix.
new_T_g The identity matrix of latent variable: u
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.
The microbiome count matrix that you want to analyze.
The number of component
A specific number of latent dimension.
The covaraince structure you choose, there are 2 different models belongs to this family:UUU, GUU.
The regression covariates matrix, which generated by model.matrix.