model_selection_PGMM {lnmCluster}

Model selections for lnmfa

Description

fit several models for lnmfa along with 3 criteria values: AIC BIC and ICL

Usage

model_selection_PGMM(
  W_count,
  range_G,
  range_Q,
  model,
  permutation,
  iter,
  const,
  X
)

Arguments

W_count

The microbiome count matrix that you want to analyze.

range_G

All possible number of component groups, a vector.

range_Q

All possible number of bicluster groups Q, a vector.

model

A vector of string that contain cov_str you want to select. Default is all 8 models.

permutation

Only has effect when model contains UUU, UUG, UUD or UUC. If TRUE, it assume the number of latent dimension could be different for different components. If FALSE, it assume the number of latent dimension are the same cross all components.

iter

Max iterations, defaul is 150.

const

Constant permutation term in multinomial distribution.

X

The regression covariates matrix, which generates from model.matrix.

Value

A dataframe that contain the cov_str, K, Q, AIC, BIC, ICL values for model. There may be a lot rows if large K and Q, because of lots of combinations: it is a sum of a geometric series with multiplier max(Q) from 1 to max(K).