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Accumulated local effect plots

Source: R/xAI.R
ALE.Rd

Calculates accumulated local effects (ALE) for the three processes

Usage

ALE(
  model,
  env = NULL,
  init_cohort = NULL,
  env_autoscale = TRUE,
  sim_seed = 42L,
  plot = TRUE,
  process = NULL,
  scale = FALSE,
  ...
)

Arguments

model

(finn_class)
Model object of class finn_class.

env

(data.table|data.frame)
Environmental covariates for which the ALE should be calculated. If NULL (default) the training env cached by fit() is used.

init_cohort

(CohortMat)
Initial cohort of class CohortMat. If NULL (default) the training init_cohort cached by fit() is used (or bare ground if none was cached).

env_autoscale

(logical(1))
If TRUE (default) env is assumed to be on the raw (unscaled) scale and the model's stored env_scaling is applied internally before the effects are computed, mirroring how the model was fitted (see fit()'s env_autoscale). Set FALSE if env is already on the model scale, or for a model fitted without autoscaling.

sim_seed

(integer(1))
Seed applied via FINN.seed() before the state-harvesting simulation, so the (stochastic) conditional effects / ALE are reproducible and cacheable. NULL disables seeding.

plot

(logical(1))
If TRUE (default) an ALE plot is drawn via plot.FINNale() (rows = processes, columns = environmental predictors, one coloured line per species).

process

(character|NULL)
If given (one of "growth", "mortality", "regeneration") only that process is plotted. NULL (default) plots all three.

scale

(logical(1))
If TRUE each curve is divided by the SD of its process x species rate, yielding dimensionless, comparable effects (the curve's variance then equals the Sobol-style normalised importance). Default FALSE.

...

Not supported yet.

Value

A list with one table per process (e.g. $growth, $mortality, $regeneration). Each table gives the accumulated local effect (ale) of every driver (var) across its observed range (x), per species. When plot = TRUE the effects are also drawn.