Crate linregress

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", -1.0000000000000004),
        ("X2", 1.5508427875232655e-15),
        ("X3", -1.4502288259166107e-15),
    ]
);
assert_eq!(
    standard_errors,
    vec![
        ("X1", 9.22799842631787e-13),
        ("X2", 4.184801029355531e-15),
        ("X3", 2.5552590991720465e-15),
    ]
);
assert_eq!(
    pvalues,
    vec![
        ("X1", 5.874726257570879e-13),
        ("X2", 0.7740647742008093),
        ("X3", 0.6713674042015161),
    ]
);

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§

FormulaRegressionBuilder: A builder to create and fit a linear regression model.
InconsistentSlopes
LowLevelRegressionModel: A fitted regression model
RegressionData: A container struct for the regression data.
RegressionDataBuilder: A builder to create a RegressionData struct for use with a FormulaRegressionBuilder.
RegressionModel: A fitted regression model.

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§