augment: Augment a 'modeler' object with influence diagnostics

In flexFitR: Flexible Non-Linear Least Square Model Fitting

Augment a modeler object with influence diagnostics

Description

This function computes various influence diagnostics, including standardized residuals, studentized residuals, and Cook's distance, for an object of class modeler.

Usage

augment(x, id = NULL, metadata = TRUE, ...)

Arguments

x	An object of class modeler.
id	Optional unique identifier to filter by a specific group. Default is NULL.
metadata	Logical. If TRUE, metadata is included with the predictions. Default is FALSE
...	Additional parameters for future functionality.

Value

A tibble containing the following columns:

uid	Unique identifier for the group.
fn_name	Function name associated with the model.
x	Predictor variable values.
y	Observed response values.
.fitted	Fitted values from the model.
.resid	Raw residuals (observed - fitted).
.hat	Leverage values for each observation.
.cooksd	Cook's distance for each observation.
.std.resid	Standardized residuals.
.stud.resid	Studentized residuals.

Author(s)

Johan Aparicio [aut]

Examples

library(flexFitR)
data(dt_potato)
mod_1 <- dt_potato |>
  modeler(
    x = DAP,
    y = Canopy,
    grp = Plot,
    fn = "fn_logistic",
    parameters = c(a = 0.199, t0 = 47.7, k = 100),
    subset = 2
  )
print(mod_1)
augment(mod_1)

flexFitR documentation built on April 16, 2025, 5:09 p.m.