find_optimal_comp_by_groups: Uses the firstMin and firstPlateau methods for 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

Uses the firstMin and firstPlateau methods for the determination of the optimal number of PLSR model components, by group (i.e. optimal selection by stratification)

Description

Uses the firstMin and firstPlateau methods for the determination of the optimal number of PLSR model components, by group (i.e. optimal selection by stratification)

Usage

find_optimal_comp_by_groups(
  dataset = NULL,
  targetVariable = NULL,
  method = "firstPlateau",
  maxComps = 20,
  iterations = 20,
  prop = 0.7,
  random_seed = 123456789,
  group_variables = NULL
)

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: firstPlateau, firstMin
maxComps	maximum number of components to consider
iterations	how many different permutations to run
prop	proportion of data to preserve for each permutation
random_seed	random seed to use for splitting data
group_variables	group_variables character vector of the form c("var1", "var2"..."varn") providing the factors used for stratified sampling.

Value

nComps the optimal number of PLSR components

Author(s)

asierrl, Shawn P. Serbin

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