inverse_predict.modeler: Inverse prediction from a `modeler` object

Description

Computes the x-value at which a fitted model reaches a user-specified response value (y-value).

Usage

# S3 method for modeler
inverse_predict(
  object,
  y,
  id = NULL,
  interval = NULL,
  tol = 1e-06,
  resolution = 1000,
  ...
)

Value

A tibble with one row per group, containing:

uid – unique identifier of the group,
fn_name – the name of the fitted function,
lower and upper – the search interval used,
y – the predicted y-value (from the function at the root),
x – the x-value at which the function reaches y.

Arguments

object: A fitted object of class modeler.
y: A numeric scalar giving the target y-value for which to compute the corresponding x.
id: Optional vector of uids for which to perform inverse prediction. If NULL, all groups are used.
interval: Optional numeric vector of length 2 specifying the interval in which to search for the root. If NULL, the interval is inferred from the range of the observed x-values.
tol: Numerical tolerance passed to uniroot for root-finding accuracy.
resolution: Integer. Number of grid points used to scan the interval.
...: Additional parameters for future functionality.

Details

The function uses numeric root-finding to solve f(t, ...params) = y. If no root is found in the interval, NA is returned.

Examples

Run this code

library(flexFitR)
data(dt_potato)
mod_1 <- dt_potato |>
  modeler(
    x = DAP,
    y = Canopy,
    grp = Plot,
    fn = "fn_lin_plat",
    parameters = c(t1 = 45, t2 = 80, k = 0.9),
    subset = c(15, 2, 45)
  )
print(mod_1)
inverse_predict(mod_1, y = 50)
inverse_predict(mod_1, y = 75, interval = c(20, 80))