Struct SesModel 

pub struct SesModel { /* private fields */ }

Simple Exponential Smoothing model.

Flat-forecast at last smoothed level. Alpha is auto-optimized via Brent’s method (1-D line search) minimizing MSE if not specified.

Implementations

impl SesModel

pub fn new(alpha: Option<f64>) -> Self

Creates a new SES model. If alpha is None, it will be auto-optimized.

Trait Implementations

impl<'de> Deserialize<'de> for SesModel

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl ForecastModel for SesModel

fn fit( &mut self, timestamps: &[i64], values: &[f64], ) -> Result<(), ForecastError>

Fit the model on historical data.

fn predict(&self, horizon: usize) -> Result<ForecastResult, ForecastError>

Predict horizon steps ahead.

fn update(&mut self, timestamp: i64, value: f64) -> Result<(), ForecastError>

Online update with a single new observation.

fn model_type(&self) -> ModelType

Returns the model type.

fn params(&self) -> &ModelParams

Returns the fitted parameters.

impl ModelStore for SesModel

fn to_bytes(&self) -> Result<Vec<u8>, StorageError>

Serializes this model to a byte vector.

fn from_bytes(bytes: &[u8]) -> Result<Self, StorageError>

where Self: Sized,

Deserializes a model from bytes.

impl Serialize for SesModel

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.