volnmf_logdet: Update volume-regularized matrix 'R' using logdet volume...

In vrnmf: Volume-Regularized Structured Matrix Factorization

Update volume-regularized matrix R using logdet volume approximation.

Description

volnmf_logdet finds matrix R that minimizes objective ||X-C*R||^2 + w.vol*log(det(R)+delta).

Usage

volnmf_logdet(
  C,
  X,
  R,
  R.constraint = "pos",
  majorate = FALSE,
  extrapolate = TRUE,
  qmax = 100,
  w.vol = 0.1,
  delta = 1,
  err.cut = 0.001,
  n.iter = 1000
)

Arguments

C	Numeric Matrices. Matrices involved in objective function.Matrix R serves as initialization.
X	Numeric Matrices. Matrices involved in objective function.Matrix R serves as initialization.
R	Numeric Matrices. Matrices involved in objective function.Matrix R serves as initialization.
R.constraint	A character. Set up ('pos') or not ('no') non-negative constraints on matrix R (by default 'pos').
majorate	A boolean. Majorate logdet each iteration (by default FALSE).
extrapolate	A boolean. Use Nesterov acceleration (by default FALSE, currently is not supported).
qmax	A numeric. Maximum asymptotic (1 - 1/qmax) of extrapolation step.
w.vol	A numeric. Volume (logdet) weight in objective function.
delta	A numeric. Determinant pseudocount in objective function.
err.cut	A numeric. Stop algorithm if relative erro in R between iteration is less than err.cut.
n.iter	An integer. Number of iterations.

Value

An updated matrix R.

vrnmf documentation built on March 18, 2022, 6:11 p.m.