| initial_variational_PGMM {lnmCluster} | R Documentation |
Gives default initial guesses for logistic-normal multinomial Factor analyzer algorithm.
Description
Gives default initial guesses for logistic-normal multinomial Factor analyzer algorithm.
Usage
initial_variational_PGMM(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 latent dimensions for each component, a vector. |
cov_str |
The covaraince structure you choose, there are 8 different models belongs to this family:UUU, UUG, UUD, UUC, GUU, GUG, GUD, GUC. |
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_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.