ScholarGate
المساعد

قارن الطرق

راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.

Prophet×التنعيم الأسي الثلاثي لهولت-وينترز×نموذج فضاء الحالة (مرشح كالمان)×
المجالالاقتصاد القياسيالاقتصاد القياسيالاقتصاد القياسي
العائلةRegression modelRegression modelRegression model
سنة النشأة201819601990
صاحب الطريقةTaylor & Letham (Facebook/Meta)Charles C. Holt and Peter R. WintersHarvey; Durbin & Koopman (state space treatment); Kalman filter
النوعDecomposable (structural) time series modelExponential smoothing forecasting modelState space time series model
المصدر التأسيسيTaylor, S. J. & Letham, B. (2018). Forecasting at Scale. The American Statistician, 72(1), 37-45. DOI ↗Winters, P. R. (1960). Forecasting Sales by Exponentially Weighted Moving Averages. Management Science, 6(3), 324-342. DOI ↗Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. DOI ↗
الأسماء البديلةProphet, Facebook Prophet, Meta Prophet, forecasting at scaletriple exponential smoothing, Winters' method, Holt-Winters seasonal method, Holt-Winters Üçlü Üstel Düzleştirmestate space, Kalman filter, unobserved components model, Durum Uzayı Modeli (State Space / Kalman Filter)
ذات صلة544
الملخصProphet is a Bayesian structural time series model introduced by Taylor and Letham at Facebook/Meta in 2018. It forecasts a continuous series by decomposing it into separate, interpretable trend, seasonality, and holiday components, and is designed to be approachable for analysts working at scale.Holt-Winters triple exponential smoothing is a forecasting model that extends Holt's double smoothing by adding a seasonal component, introduced by Peter Winters in 1960 building on Charles Holt's work. It tracks three evolving quantities — level, trend, and season — and combines them to forecast a continuous time series.A state space model is a general time series framework that describes a series through unobserved (latent) state variables linked by a measurement equation and a transition equation, with the states estimated in real time by the Kalman filter. Developed in the state space tradition of Harvey (1990) and Durbin & Koopman (2012), it nests ARIMA and exponential smoothing as special cases.
ScholarGateمجموعة البيانات
  1. v1
  2. 2 المصادر
  3. PUBLISHED
  1. v1
  2. 2 المصادر
  3. PUBLISHED
  1. v1
  2. 2 المصادر
  3. PUBLISHED

انتقل إلى البحث تنزيل الشرائح

ScholarGateقارن الطرق: Prophet · Holt-Winters · State Space Model. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare