Fit the covariate-augmented overdispersed Poisson factor model

RR_COAP(
  X_count,
  multiFac = rep(1, nrow(X_count)),
  Z = matrix(1, nrow(X_count), 1),
  rank_use = 5,
  q = 15,
  epsELBO = 1e-05,
  maxIter = 30,
  verbose = TRUE,
  fast_version = c("Laplace_Taylor", "Rough_Approx"),
  joint_opt_beta = FALSE,
  fast_svd = TRUE
)

Arguments

X_count

a count matrix, the observed count matrix.

multiFac

an optional vector, the normalization factor for each unit; default as full-one vector.

Z

an optional matrix, the covariate matrix; default as a full-one column vector if there is no additional covariates.

rank_use

an optional integer, specify the rank of the regression coefficient matrix; default as 5.

q

an optional string, specify the number of factors; default as 15.

epsELBO

an optional positive vlaue, tolerance of relative variation rate of the envidence lower bound value, defualt as '1e-5'.

maxIter

the maximum iteration of the VEM algorithm. The default is 30.

verbose

a logical value, whether output the information in iteration.

joint_opt_beta

a logical value, whether use the joint optimization method to update bbeta. The default is FALSE, which means using the separate optimization method.

fast_svd

a logical value, whether use the fast SVD algorithm in the update of bbeta; default is TRUE.

Value

return a list including the following components: (1) H, the predicted factor matrix; (2) B, the estimated loading matrix; (3) bbeta, the estimated low-rank large coefficient matrix; (4) invLambda, the inverse of the estimated variances of error; (5) H0, the factor matrix; (6) ELBO: the ELBO value when algorithm stops; (7) ELBO_seq: the sequence of ELBO values.

Details

None

References

None

See also

RR_COAP