Crate linregress

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 = model.parameters;
let standard_errors = model.se;
let pvalues = model.pvalues;
assert_eq!(
    parameters.pairs(),
    vec![
        ("X1", -0.9999999999999745),
        ("X2", 0.00000000000000005637851296924623),
        ("X3", 0.00000000000000008283304597789254),
    ]
);
assert_eq!(
    standard_errors.pairs(),
    vec![
        ("X1", 0.00000000000019226371555402852),
        ("X2", 0.0000000000000008718958950659518),
        ("X3", 0.0000000000000005323837152041135),
    ]
);
assert_eq!(
    pvalues.pairs(),
    vec![
        ("X1", 0.00000000000012239888283055414),
        ("X2", 0.9588921357097694),
        ("X3", 0.9017368322742073),
    ]
);

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.
• RegressionParameters
  A parameter of a fitted RegressionModel given for the intercept and each regressor.

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

• fit_low_level_regression_model
  Fit a regression model directly on a matrix of input data
• fit_low_level_regression_model_without_statistics
  Like fit_low_level_regression_model but does not compute any statistics after fitting the model.