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Linganisha mbinu

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Mfumo wa ARIMA (Autoregressive Integrated Moving Average)×Upepeshaji wa kielelezo rahisi na mara mbili (SES / Holt)×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili20151957
MwanzilishiBox & Jenkins (Box-Jenkins methodology)Robert G. Brown (SES); Charles C. Holt (linear trend)
AinaUnivariate time-series modelExponential smoothing forecasting model
Chanzo asiliaBox, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Brown, R. G. (1959). Statistical Forecasting for Inventory Control. McGraw-Hill. link ↗
Majina mbadalaBox-Jenkins model, ARIMA(p,d,q), ARIMA ModeliSES, Holt's linear trend method, exponential smoothing forecasting, Basit ve Çift Üstel Düzleştirme (SES / Holt)
Zinazohusiana53
MuhtasariARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).Exponential smoothing is a family of basic time-series forecasting models in which each new observation updates a smoothed estimate by a weighting parameter. Simple exponential smoothing (SES), introduced by Robert G. Brown in 1959, forecasts series with a stable level, while Holt's double exponential smoothing, introduced by Charles C. Holt in 1957, adds a trend term using the parameters alpha and beta.
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ScholarGateLinganisha mbinu: ARIMA · Exponential Smoothing. Imepatikana 2026-06-17 kutoka https://scholargate.app/sw/compare