Struct linregress::RegressionParameters [−][src]
pub struct RegressionParameters { pub intercept_value: f64, pub regressor_names: Vec<String>, pub regressor_values: Vec<f64>, }
Expand description
A parameter of a fitted RegressionModel
given for the intercept and each regressor.
The values and names of the regressors are given in the same order.
You can obtain name value pairs using pairs
.
Fields
intercept_value: f64
regressor_names: Vec<String>
regressor_values: Vec<f64>
Implementations
Returns the parameters as a Vec of tuples of the form (name: &str, value: f64)
.
Usage
use linregress::{FormulaRegressionBuilder, RegressionDataBuilder}; let y = vec![1.,2. ,3. , 4.]; let x1 = vec![4., 3., 2., 1.]; let x2 = vec![1., 2., 3., 4.]; let data = vec![("Y", y), ("X1", x1), ("X2", x2)]; let data = RegressionDataBuilder::new().build_from(data)?; let model = FormulaRegressionBuilder::new().data(&data).formula("Y ~ X1 + X2").fit()?; let pairs = model.parameters.pairs(); assert_eq!(pairs[0], ("X1", -0.0370370370370372)); assert_eq!(pairs[1], ("X2", 0.9629629629629629));
Trait Implementations
Auto Trait Implementations
impl RefUnwindSafe for RegressionParameters
impl Send for RegressionParameters
impl Sync for RegressionParameters
impl Unpin for RegressionParameters
impl UnwindSafe for RegressionParameters
Blanket Implementations
Mutably borrows from an owned value. Read more
type Output = T
type Output = T
Should always be Self
The inverse inclusion map: attempts to construct self
from the equivalent element of its
superset. Read more
pub fn is_in_subset(&self) -> bool
pub fn is_in_subset(&self) -> bool
Checks if self
is actually part of its subset T
(and can be converted to it).
pub fn to_subset_unchecked(&self) -> SS
pub fn to_subset_unchecked(&self) -> SS
Use with care! Same as self.to_subset
but without any property checks. Always succeeds.
pub fn from_subset(element: &SS) -> SP
pub fn from_subset(element: &SS) -> SP
The inclusion map: converts self
to the equivalent element of its superset.
pub fn vzip(self) -> V