| opt.rank {fabisearch} | R Documentation |
Finds the optimal rank for non-negative matrix factorization (NMF)
Description
This function finds the optimal rank for non-negative matrix factorization (NMF).
Usage
opt.rank(Y, nruns = 50, algtype = "brunet")
Arguments
Y |
An input multivariate time series in matrix format, with variables organized in columns and time points in rows. All entries in Y must be positive. |
nruns |
A positive integer with default value equal to 50. It is used to define the number of runs in the NMF function. |
algtype |
A character string, which defines the algorithm to be used in the NMF function. By default it is set to "brunet". See the "Algorithms" section of
|
Value
A positive integer representing the optimal rank.
Author(s)
Martin Ondrus, mondrus@ualberta.ca, Ivor Cribben, cribben@ualberta.ca
References
"Factorized Binary Search: a novel technique for change point detection in multivariate high-dimensional time series networks", Ondrus et al. (2021), <arXiv:2103.06347>.
Examples
## Finding the optimal rank for an input data set "sim2" with nruns = 4
set.seed(123)
opt.rank(sim2, nruns = 4)
# [1] "Finding optimal rank"
# [1] "Optimal rank: 2"
# [1] 2