dot-fitter_curve: General-purpose optimization

In flexFitR: Flexible Non-Linear Least Square Model Fitting

General-purpose optimization

Description

The function .fitter_curve is used internally to find the parameters requested.

Usage

.fitter_curve(data, id, fn, method, lower, upper, control, metadata, trace)

Arguments

data	A nested data.frame with columns <plot, genotype, row, range, data, initials, fx_params>.
id	An optional vector of IDs to filter the data. Default is NULL, meaning all ids are used.
fn	A string specifying the name of the function to be used for the curve fitting. Default is "fn_lin_plat".
method	A character vector specifying the optimization methods to be used. See optimx package for available methods. Default is c("subplex", "pracmanm", "anms").
lower	Numeric vector specifying the lower bounds for the parameters. Default is -Inf for all parameters.
upper	Numeric vector specifying the upper bounds for the parameters. Default is Inf for all parameters.
control	A list of control parameters to be passed to the optimization function. For example, list(maxit = 500).
trace	If TRUE , convergence monitoring of the current fit is reported in the console. FALSE by default.

Value

A list containing the following elements:

kkopt

opm object.

param

Data frame with best solution parameters.

rr

Data frame with all methods tested.

details

Additional details of the best solution.

hessian

Hessian matrix.

type

Data frame describing the type of coefficient (estimable of fixed)

conv

Convergency.

p

Number of parameters estimated.

n_obs

Number of observations.

uid

Unique identifier.

fn_name

Name of the curve-fitting function used.

Examples

library(flexFitR)
data(dt_potato)
mod_1 <- dt_potato |>
  modeler(
    x = DAP,
    y = GLI,
    grp = Plot,
    fn = "fn_lin_pl_lin",
    parameters = c(t1 = 38.7, t2 = 62, t3 = 90, k = 0.32, beta = -0.01),
    subset = 195,
    options = list(add_zero = TRUE)
  )

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