Main function for MUGS algorithm

Usage

MUGS(
  TUNE = F,
  Eva = T,
  Lambda = c(10),
  Lambda.delta = c(1000),
  n.core = 4,
  tol = 1,
  seed = 1,
  S.1 = NULL,
  S.2 = NULL,
  X.group.source = NULL,
  X.group.target = NULL,
  pairs.rel.CV = NULL,
  pairs.rel.EV = NULL,
  p = 100,
  n.group = 400
)

Arguments

TUNE: Logical value indicating whether the function should tune parameters 'TRUE' or use predefined parameters 'FALSE'.
Eva: Logical value indicating whether to perform evaluation (TRUE) or skip it (FALSE).
Lambda: The candidate values for the tuning parameter controls the intensity of penalization on the code effects.
Lambda.delta: The candidate values for the tuning parameter controls the intensity of penalization on the code-site effects.
n.core: Integer specifying the number of cores to use for parallel processing.
tol: Numeric value representing the tolerance level for convergence in the algorithm.
seed: Integer used to set the seed for random number generation, ensuring reproducibility of the simulated data or any stochastic process within the algorithm.
S.1: The SPPMI matrix from site 1.
S.2: The SPPMI matrix from site 2.
X.group.source: The dummy matrix on the group structure of codes at site 1.
X.group.target: The dummy matrix on the group structure of codes at site 2.
pairs.rel.CV: Code-code pairs used for tuning via cross validation
pairs.rel.EV: Code-code pairs used for evaluation
p: Integer indicating the length of embeddings.
n.group: The number of groups.

Value

The final result