Struct linregress::LowLevelRegressionModel [−][src]
pub struct LowLevelRegressionModel {
pub parameters: Vec<f64>,
pub se: Vec<f64>,
pub ssr: f64,
pub rsquared: f64,
pub rsquared_adj: f64,
pub pvalues: Vec<f64>,
pub residuals: Vec<f64>,
pub scale: f64,
}Expand description
A fitted regression model
Is the result of fit_low_level_regression_model.
If a field has only one value for the model it is given as f64.
Otherwise it is given as a Vec<f64> where the first value is the intercept value.
Fields
parameters: Vec<f64>The model’s intercept and slopes (also known as betas).
se: Vec<f64>The standard errors of the parameter estimates.
ssr: f64Sum of squared residuals.
rsquared: f64R-squared of the model.
rsquared_adj: f64Adjusted R-squared of the model.
pvalues: Vec<f64>The two-tailed p-values for the t-statistics of the params.
residuals: Vec<f64>The residuals of the model.
scale: f64A scale factor for the covariance matrix.
Note that the square root of scale is often
called the standard error of the regression.
Trait Implementations
Auto Trait Implementations
impl RefUnwindSafe for LowLevelRegressionModel
impl Send for LowLevelRegressionModel
impl Sync for LowLevelRegressionModel
impl Unpin for LowLevelRegressionModel
impl UnwindSafe for LowLevelRegressionModel
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.