R: run main microbiome Factor Analyzer algorithm.

Mico_bi_PGMM {lnmCluster}

R Documentation

run main microbiome Factor Analyzer algorithm.

run main microbiome Factor Analyzer algorithm.

Mico_bi_PGMM(
  W_count,
  G,
  Q_g,
  pi_g,
  mu_g,
  sig_g,
  V,
  m,
  B_K,
  T_K,
  D_K,
  cov_str,
  iter,
  const,
  beta_g,
  X
)

`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.
`pi_g`	A vector of initial guesses of component proportion
`mu_g`	A list of initial guess of mean vector
`sig_g`	A list of initial guess of covariance matrix for each component
`V`	A list of initial guess of variational varaince
`m`	A list of initial guess of variational mean
`B_K`	A list of initial guess of loading matrix.
`T_K`	A list of identity matrix with dimension q.
`D_K`	A list of initial guess of error matrix
`cov_str`	The covaraince structure you choose, there are 8 different models belongs to this family:UUU, UUG, UUD, UUC, GUU, GUG, GUD, GUC.
`iter`	Max iterations, default is 150.
`const`	the permutation constant in multinomial distribution. Calculated before the main algorithm in order to save computation time.
`beta_g`	initial guess of covariates coefficients.
`X`	The regression covariates matrix, which generates by model.matrix.

z_ig Estimated latent variable z

cluster Component labels

mu_g Estimated component mean

pi_g Estimated component proportion

B_g Estimated loading matix.

D_g Estimated error covariance

COV Estimated component covariance

beta_g Estimated covariates coefficients.

overall_loglik Complete log likelihood value for each iteration

ICL ICL value

BIC BIC value

AIC AIC value

[Package lnmCluster version 0.3.1 Index]