Crate linregress

source ·
Expand description

linregress provides an easy to use implementation of ordinary least squared linear regression with some basic statistics. See RegressionModel for details.

The builder FormulaRegressionBuilder is used to construct a model from a table of data and an R-style formula or a list of columns to use. Currently only very simple formulae are supported, see FormulaRegressionBuilder.formula for details.

Example

use linregress::{FormulaRegressionBuilder, RegressionDataBuilder};

let y = vec![1., 2. ,3. , 4., 5.];
let x1 = vec![5., 4., 3., 2., 1.];
let x2 = vec![729.53, 439.0367, 42.054, 1., 0.];
let x3 = vec![258.589, 616.297, 215.061, 498.361, 0.];
let data = vec![("Y", y), ("X1", x1), ("X2", x2), ("X3", x3)];
let data = RegressionDataBuilder::new().build_from(data)?;
let formula = "Y ~ X1 + X2 + X3";
let model = FormulaRegressionBuilder::new()
    .data(&data)
    .formula(formula)
    .fit()?;
let parameters: Vec<_> = model.iter_parameter_pairs().collect();
let pvalues: Vec<_> = model.iter_p_value_pairs().collect();
let standard_errors: Vec<_> = model.iter_se_pairs().collect();
assert_eq!(
    parameters,
    vec![
        ("X1", -0.9999999999999745),
        ("X2", 1.5872719805187785e-15),
        ("X3", -1.4246416546459528e-15),
    ]
);
assert_eq!(
    standard_errors,
    vec![
        ("X1", 9.799066977595267e-13),
        ("X2", 4.443774660560714e-15),
        ("X3", 2.713389610740135e-15),
    ]
);
assert_eq!(
    pvalues,
    vec![
        ("X1", 6.238279788691533e-13),
        ("X2", 0.7815975465725482),
        ("X3", 0.6922074604135647),
    ]
);

Macros

  • assert_almost_eq
    Only exposed for use in doc comments. This macro is not considered part of this crate’s stable API.
  • assert_slices_almost_eq
    Only exposed for use in doc comments. This macro is not considered part of this crate’s stable API.

Structs

Enums

  • Error
    An error that can occur in this crate.
  • InvalidValueHandling
    How to proceed if given non real f64 values (NaN or infinity or negative infinity).

Functions