ScholarGate
Asistent

Porovnať metódy

Prezrite si vybrané metódy vedľa seba; riadky, ktoré sa líšia, sú zvýraznené.

Model kĺzavých priemerov (MA)×Model ARMA (Autoregresívny kĺzavý priemer)×Autoregregresný model (AR)×
OdborEkonometriaEkonometriaEkonometria
RodinaRegression modelRegression modelRegression model
Rok vzniku197019701970s (popularised 1976)
TvorcaBox and JenkinsGeorge E. P. Box and Gwilym M. JenkinsGeorge E. P. Box and Gwilym M. Jenkins
TypLinear time series modelTime series modelTime series model
Pôvodný zdrojBox, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗Box, G. E. P., & Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0816211043
Ďalšie názvyMA model, MA(q) process, moving-average process, Box-Jenkins MAARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)AR model, AR(p) model, autoregression, AR process
Príbuzné556
ZhrnutieThe Moving Average model of order q — written MA(q) — expresses the current value of a time series as a linear combination of the current and past random shocks (innovations). Unlike the AR model which uses lagged values of the series itself, the MA model uses lagged error terms, making it well-suited for capturing short-lived disturbances that dissipate over q periods.The ARMA(p,q) model describes a stationary time series as a combination of two components: an autoregressive part that regresses the current value on its own past p values, and a moving average part that accounts for past q error terms. It is the foundational framework of the Box-Jenkins methodology for univariate time series modelling and short-run forecasting.An autoregressive model of order p — AR(p) — expresses the current value of a time series as a linear function of its own p most recent past values plus a white-noise error. It is the building block of the Box-Jenkins family of time-series models and is widely used for forecasting stationary economic and financial series.
ScholarGateDátová sada
  1. v1
  2. 2 Zdroje
  3. PUBLISHED
  1. v1
  2. 2 Zdroje
  3. PUBLISHED
  1. v1
  2. 2 Zdroje
  3. PUBLISHED

Prejsť na hľadanie Stiahnuť snímky

ScholarGatePorovnať metódy: Moving Average Model · ARMA model · Autoregressive model. Získané 2026-06-18 z https://scholargate.app/sk/compare