/
holt_winters.js
67 lines (64 loc) · 1.54 KB
/
holt_winters.js
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/**
* Holt-Winters method
*/
export default class HoltWinters {
// https://takuti.me/ja/note/holt-winters/
/**
* @param {number} a Weight for last value
* @param {number} [b] Weight for trend value
* @param {number} [g] Weight for seasonal data
* @param {number} [s] Length of season
*/
constructor(a, b = 0, g = 0, s = 0) {
this._a = a
this._b = b
this._g = g
this._s = s
}
/**
* Fit model and return predict values.
*
* @param {number[]} x Training data
* @returns {number[]} Predicted values
*/
fit(x) {
const f = [x[0]]
this._level = x[0]
this._trend = 0
this._season = []
for (let i = 0; i < this._s; i++) {
this._season[i] = 0
}
for (let i = 1; i < x.length; i++) {
const level =
this._a * (this._s <= 0 ? x[i] : x[i] - this._season[i % this._s]) +
(1 - this._a) * (this._level + this._trend)
this._trend = this._b * (level - this._level) + (1 - this._b) * this._trend
const ft = level + this._trend
this._level = level
if (this._s > 0) {
this._season[i % this._s] = this._g * (x[i] - level) + (1 - this._g) * this._season[i % this._s]
}
f.push(ft)
}
this._step_offset = x.length + 1
return f
}
/**
* Returns predicted future values.
*
* @param {number} k Prediction count
* @returns {Array<Array<number>>} Predicted values
*/
predict(k) {
const pred = []
for (let i = 0; i < k; i++) {
let p = this._level + this._trend * (i + 1)
if (this._s > 0) {
p += this._season[(i + this._step_offset) % this._s]
}
pred.push(p)
}
return pred
}
}