Fits nmfkc.signed across a range of ranks and reports
r.squared, the effective rank, and the element-wise CV error
sigma.ecv, with the same concise plot as
nmfkc.rank.
Usage
nmfkc.signed.rank(
Y,
A,
rank = 1:5,
detail = c("full", "fast"),
plot = TRUE,
...
)Arguments
- Y
Observation matrix (may contain negative entries).
- A
Covariate matrix (may be signed).
- rank
Integer vector of ranks to evaluate.
- detail
"full"(default) also runs element-wise CV (sigma.ecv);"fast"skips it (plots r.squared and eff.rank only, and recommends the R-squared elbow).- plot
Logical; draw the diagnostics plot (default
TRUE).- ...
Passed on to
nmfkc.signedandnmfkc.signed.ecv(e.g.\maxit,nfolds,seed).
Value
A list with rank.best and criteria
(rank, effective.rank, effective.rank.ratio,
r.squared, sigma.ecv).
References
Roy, O., & Vetterli, M. (2007). The effective rank: A measure of
effective dimensionality. Proc. EUSIPCO, 606–610.
(effective.rank)
Wold, S. (1978). Cross-validatory estimation of the number of
components in factor and principal components models.
Technometrics, 20(4), 397–405. (sigma.ecv)