Estimate nuisance values for matrix or sparse matrices.

Usage

# Default S3 method
estimate_nuisance(
  input_obj,
  mean_mat,
  library_mat,
  bool_use_log = F,
  min_val = 1e-04,
  verbose = 0,
  ...
)

input_obj: Dataset (either matrix or dgCMatrix) where the \(n\) rows represent cells and \(p\) columns represent genes. The rows and columns of the matrix should be named.
mean_mat: A matrix of \(n\) rows and \(p\) columns that represents the expected value of each entry.
library_mat: A matrix of \(n\) rows and \(p\) columns that represents the library size of each entry.
bool_use_log: Boolean if the nuisance (i.e., over-dispersion) parameter should be estimated on the log scale, default is FALSE.
min_val: Minimum value of the nuisance parameter.
verbose: Integer.
...: Additional parameters.

Vector of length \(p\)