find_optimal_components: Applies different methods for the determination of the...

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

Applies different methods for the determination of the optimal number of PLSR model components

Description

Applies different methods for the determination of the optimal number of PLSR model components

Usage

find_optimal_components(
  dataset = NULL,
  targetVariable = NULL,
  method = "pls",
  maxComps = 20,
  iterations = 20,
  seg = 100,
  prop = 0.7,
  random_seed = 123456789
)

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
method	Which approach to use to find optimal components. Options: pls, firstPlateau, firstMin
maxComps	maximum number of components to consider
iterations	how many different permutations to run
seg	For the built-in pls method, how many different data segments to select from the input dataset
prop	proportion of data to preserve for each permutation
random_seed	random seed to use for splitting data

Value

nComps the optimal number of PLSR components

Author(s)

Julien Lamour, Jeremiah Anderson, Shawn P. Serbin

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