nmf.rrr.signed.rank: Rank selection for nmfae.signed (paired rank, concise...
In nmfkc: Non-Negative Matrix Factorization with Kernel Covariates

nmf.rrr.signed.rank

R Documentation

Rank selection for nmfae.signed (paired rank, concise diagnostics)

Description

Fits nmfae.signed with a paired decoder/encoder rank (Q = R) across a range of ranks and reports r.squared, the effective rank (of the latent encoding H), and the element-wise CV error sigma.ecv, with the same concise plot as nmfkc.rank. For a full (Q, R) grid use nmfae.signed.ecv.

Usage

nmf.rrr.signed.rank(
  Y1,
  Y2 = Y1,
  rank1 = 1:5,
  detail = c("full", "fast"),
  plot = TRUE,
  ...,
  rank = NULL
)

Arguments

`Y1`	Endogenous matrix (`P_1 \times N`); may be signed.
`Y2`	Exogenous matrix; defaults to `Y1`.
`rank1`	Integer vector of (paired) ranks to evaluate (both bases use the same value). Legacy `Q` accepted via `...`.
`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 `nmfae.signed` and `nmfae.signed.ecv`.
`rank`	Deprecated alias of `rank1`.

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)