R using logdet volume approximation.volnmf_logdet finds matrix R that minimizes objective
||X-C*R||^2 + w.vol*log(det(R)+delta).
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
)Numeric Matrices. Matrices involved in objective function.Matrix R serves as initialization.
Numeric Matrices. Matrices involved in objective function.Matrix R serves as initialization.
Numeric Matrices. Matrices involved in objective function.Matrix R serves as initialization.
A character. Set up ('pos') or not ('no') non-negative constraints on matrix R (by default 'pos').
A boolean. Majorate logdet each iteration (by default FALSE).
A boolean. Use Nesterov acceleration (by default FALSE, currently is not supported).
A numeric. Maximum asymptotic (1 - 1/qmax) of extrapolation step.
A numeric. Volume (logdet) weight in objective function.
A numeric. Determinant pseudocount in objective function.
A numeric. Stop algorithm if relative erro in R between iteration is less than err.cut.
An integer. Number of iterations.
An updated matrix R.