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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").

Examples

# Default: OPC optimization (recommended)
diss_pls()
#> Dissimilarity: PLS
#>   method            : pls 
#>   ncomp             :  
#>   scale             : FALSE 
#>   return_projection : FALSE 

# Fixed number of components
diss_pls(ncomp = 15)
#> Dissimilarity: PLS
#>   method            : pls 
#>   ncomp             : fixed: 15 
#>   scale             : FALSE 
#>   return_projection : FALSE 

# Custom opc settings
diss_pls(ncomp = ncomp_by_opc(max_ncomp = 50))
#> Dissimilarity: PLS
#>   method            : pls 
#>   ncomp             :  
#>   scale             : FALSE 
#>   return_projection : FALSE 

# Modified PLS
diss_pls(ncomp = 10, method = "mpls")
#> Dissimilarity: PLS
#>   method            : mpls 
#>   ncomp             : fixed: 10 
#>   scale             : FALSE 
#>   return_projection : FALSE