diss_pls: PLS dissimilarity method constructor

In resemble: Similarity Retrieval and Local Learning for Spectral Chemometrics

PLS dissimilarity method constructor

Description

Creates a configuration object for computing dissimilarity based on Mahalanobis distance in PLS score space. Requires Yr in dissimilarity().

Usage

diss_pls(
  ncomp = ncomp_by_opc(),
  method = c("pls", "mpls"),
  scale = FALSE,
  return_projection = FALSE
)

Arguments

ncomp	Component selection method. Can be: A positive integer for a fixed number of components ncomp_fixed(n): explicit fixed selection ncomp_by_var(min_var): retain components explaining at least min_var variance each ncomp_by_cumvar(min_cumvar): retain components until cumulative variance reaches min_cumvar ncomp_by_opc(): optimize using side information (default; recommended for PLS since Yr is already required)
method	Character. PLS algorithm: "pls" (default) or "mpls" (modified PLS, Shenk & Westerhaus 1991).
scale	Logical. Scale data? Default FALSE. Note: PLS always centers internally.
return_projection	Logical. Return projection object? Default FALSE.

Value

An object of class c("diss_pls", "diss_method").

Author(s)

Leonardo Ramirez-Lopez

See Also

Component selection: ncomp_by_var, ncomp_by_cumvar, ncomp_by_opc, ncomp_fixed

Other dissimilarity methods: diss_pca, diss_correlation, diss_euclidean, diss_cosine, diss_mahalanobis

Examples

# Default: OPC optimization (recommended)
diss_pls()

# Fixed number of components
diss_pls(ncomp = 15)

# Custom opc settings
diss_pls(ncomp = ncomp_by_opc(max_ncomp = 50))

# Modified PLS
diss_pls(ncomp = 10, method = "mpls")

resemble documentation built on April 21, 2026, 1:07 a.m.