Skip to contents

Average conditional effects of a FINN model

Source: R/xAI.R
averageConditionalEffects.Rd

Summarises the conditional effects into a per process x species x variable average marginal effect: the mean local derivative (mean_effect, an approximate linear effect). Derived cheaply from the cached conditional effects.

Usage

averageConditionalEffects(
  model,
  env = NULL,
  init_cohort = NULL,
  env_autoscale = TRUE,
  sim_seed = 42L,
  env_only = TRUE
)

Arguments

model

(finn_class)
fitted model.

env

(data.table|data.frame|NULL)
env covariates; NULL uses the cached training env.

init_cohort

(CohortMat|NULL)
initial cohort; NULL uses the cached training init_cohort.

env_autoscale

(logical(1))
see ALE().

sim_seed

(integer(1))
seed for the state-harvesting simulation (see ALE()).

env_only

(logical(1))
if TRUE (default) report only the environmental predictors of each process; if FALSE also include the stand-state inputs (dbh, light, growth) each process depends on.

Value

a named list (one entry per process) of data.frames with columns species, variable, mean_effect.