pls_permutation: Run a PLSR model permutation analysis. Can be used to...

In TESTgroup-BNL/PLSR_for_plant_trait_prediction: A simple add-on package to aid in the fitting of leaf or canopy scale spectra-trait PLSR models

Run a PLSR model permutation analysis. Can be used to determine the optimal number of components or conduct a boostrap uncertainty analysis

Description

See Serbin et al. (2019). DOI: https://doi.org/10.1111/nph.16123

Usage

pls_permutation(
  dataset = NULL,
  targetVariable = NULL,
  maxComps = 20,
  iterations = 20,
  prop = 0.7,
  verbose = FALSE
)

Arguments

dataset	input full PLSR dataset. Usually just the calibration dataset
targetVariable	What object or variable to use as the Y (predictand) in the PLSR model? Usually the "inVar" variable set at the beginning of a PLS script
maxComps	maximum number of components to use for each PLSR fit
iterations	how many different permutations to run
prop	proportion of data to preserve for each permutation
verbose	Should the function report the current iteration status/progress to the terminal or run silently? TRUE/FALSE. Default FALSE

Value

output a list containing the PRESS and coef_array. output <- list(PRESS=press.out, coef_array=coefs)

Author(s)

Julien Lamour, Shawn P. Serbin

TESTgroup-BNL/PLSR_for_plant_trait_prediction documentation built on Feb. 15, 2025, 2:08 p.m.