# gleastsq
[](https://hex.pm/packages/gleastsq)
[](https://hexdocs.pm/gleastsq/)
A curve fitting library for Gleam. This library uses the [Nx](https://hexdocs.pm/nx/Nx.html) library from Elixir to perform matrix operations.
## Levenberg-Marquardt vs Leasts Squares for curve fitting
The library provides two functions for curve fitting: `least_squares` and `levenberg_marquardt`.
### Least Squares
The `least_squares` function is generally simpler and faster but may not converge for some functions, specially for non-linear functions.
It is generally recommended for simpler models where the relationship between the parameters and the function is linear.
### Levenberg-Marquardt
The `levenberg_marquardt` function is more robust but may be slower due to the extra calculations.
It is generally recommended for non-linear functions where the relationship between the parameters and the function is non-linear.
## Installation
```sh
gleam add gleastsq
```
```gleam
import gleam/option.{None}
import gleam/io
import gleastsq
fn parabola(x: Float, params: List(Float)) -> Float {
let assert [a, b, c] = params
a *. x *. x +. b *. x +. c
}
pub fn main() {
let x = [0.0, 1.0, 2.0, 3.0, 4.0, 5.0]
let y = [0.0, 1.0, 4.0, 9.0, 16.0, 25.0]
let initial_guess = [1.0, 1.0, 1.0]
let assert Ok(result) =
gleastsq.least_squares(x, y, parabola, initial_guess, opts: [])
io.debug(result) // [1.0, 0.0, 0.0] (within numerical error)
}
```
Further documentation can be found at <https://hexdocs.pm/gleastsq>.
