Struct Model 

pub struct Model { /* private fields */ }

A fitted ETS model.

Implementations

impl Model

pub fn log_likelihood(&self) -> f64

The log-likelihood of the model.

pub fn aic(&self) -> f64

The Akaike Information Criterion (AIC) of the model.

pub fn aicc(&self) -> f64

The corrected Akaike Information Criterion (AICC) of the model.

pub fn bic(&self) -> f64

The Bayesian Information Criterion (BIC) of the model.

pub fn mse(&self) -> f64

The mean squared error (MSE) of the model.

pub fn amse(&self) -> f64

The average mean squared error (AMSE) of the model.

This is the average of the MSE over the number of forecasting horizons (nmse).

pub fn model_type(&self) -> ModelType

The model type.

pub fn damped(&self) -> bool

Whether the model uses damped trend.

Trait Implementations

impl Clone for Model

fn clone(&self) -> Model

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for Model

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Predict for Model

type Error = Error

The type of error returned when predicting with the model.

fn predict_in_sample_inplace( &self, level: Option<f64>, forecast: &mut Forecast, ) -> Result<(), Self::Error>

Calculate the in-sample predictions, storing the results in the provided Forecast struct.

fn predict_inplace( &self, horizon: usize, level: Option<f64>, forecast: &mut Forecast, ) -> Result<(), Self::Error>

Calculate the n-ahead predictions for the given horizon, storing the results in the provided Forecast struct.

fn training_data_size(&self) -> usize

Return the number of training data points used to fit the model.

fn predict( &self, horizon: usize, level: impl Into<Option<f64>>, ) -> Result<Forecast, Self::Error>

Return the n-ahead predictions for the given horizon.

fn predict_in_sample( &self, level: impl Into<Option<f64>>, ) -> Result<Forecast, Self::Error>

Return the in-sample predictions.