Struct HoltWinters 

pub struct HoltWinters { /* private fields */ }

Holt’s linear method — double exponential smoothing with a level and a trend component.

A single Ema tracks only a level and therefore lags any sustained trend. Holt’s method adds a second smoothed state, the trend, and reports the one-step-ahead forecast level + trend, which removes that lag on trending data while still smoothing noise.

level_t = α · price_t        + (1 − α) · (level_{t-1} + trend_{t-1})
trend_t = β · (level_t − level_{t-1}) + (1 − β) · trend_{t-1}
output  = level_t + trend_t          (one-step-ahead forecast)

α ∈ (0, 1] is the level smoothing constant and β ∈ (0, 1] the trend smoothing constant. The state is seeded from the first two inputs (level = price_1, trend = price_1 − price_0), so the first output lands on the second input.

On a perfectly linear series the forecast is exact from the second bar onward (for any α, β): if the level equals the current value and the trend equals the slope, both invariants are preserved and level + trend equals the next value.

Example

use wickra_core::{HoltWinters, Indicator};

let mut indicator = HoltWinters::new(0.2, 0.1).unwrap();
let mut last = None;
for i in 0..80 {
    last = indicator.update(100.0 + f64::from(i));
}
assert!(last.is_some());

Implementations

impl HoltWinters

pub fn new(alpha: f64, beta: f64) -> Result<Self>

Construct Holt’s linear smoother with level constant alpha and trend constant beta.

Errors

Returns Error::InvalidPeriod if either constant is non-finite or outside (0.0, 1.0].

pub const fn alpha(&self) -> f64

Level smoothing constant alpha.

pub const fn beta(&self) -> f64

Trend smoothing constant beta.

pub fn level(&self) -> Option<f64>

Current smoothed level, if seeded.

pub fn trend(&self) -> Option<f64>

Current smoothed trend, if seeded.

pub fn value(&self) -> Option<f64>

Current one-step-ahead forecast level + trend, if seeded.

Trait Implementations

impl Clone for HoltWinters

fn clone(&self) -> Self

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for HoltWinters

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

Formats the value using the given formatter.

impl Indicator for HoltWinters

type Input = f64

Type of one input data point (typically f64 for a price, or Candle / Tick).

type Output = f64

Type of one output value.

fn update(&mut self, price: f64) -> Option<f64>

Feed one new data point into the indicator and return the freshly computed output, or None if there is no value for this input.

fn reset(&mut self)

Reset all internal state, leaving the indicator equivalent to a freshly constructed instance with the same parameters.

fn warmup_period(&self) -> usize

Number of inputs required before the first non-None output can be produced.

fn is_ready(&self) -> bool

Whether the indicator has emitted at least one value since the last reset.

fn name(&self) -> &'static str

Stable, human-readable indicator name. Used by chaining and diagnostics.

fn batch_nan_into(&mut self, inputs: &[Self::Input], out: &mut [f64])

where Self::Input: Copy, Self::Output: Into<f64>,

Run the indicator over inputs, writing one output per input into the caller-owned out buffer (NaN where update returns None). It exists for every indicator whose output converts to an f64; the batch pipelines use it for the scalar f64 -> f64 ones.

fn batch_fast_into(&mut self, inputs: &[Self::Input], out: &mut [f64])

where Self::Input: Copy, Self::Output: Into<f64>,

Opt-in fast batch: like batch_nan_into, but an indicator with a vectorised kernel may reassociate its arithmetic to run it in SIMD lanes. Each value then agrees with the exact batch to within the tolerance the indicator documents (a few units in the last place), not bit for bit; warmup positions, NaN placement and the output length are identical. The kernels are deterministic: the same input produces the same bits on every platform, with or without SIMD hardware.