ScholarGate
アシスタント

手法を比較

選択した手法を並べて確認できます。異なる行はハイライト表示されます。

SARIMAモデル×移動平均 (MA) モデル×
分野計量経済学計量経済学
系統Regression modelRegression model
提唱年1970 (first edition); 1976 (revised)1970
提唱者Box, Jenkins, and ReinselBox and Jenkins
種類Seasonal time series modelLinear time series model
原典Box, 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., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744
別名SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal componentMA model, MA(q) process, moving-average process, Box-Jenkins MA
関連55
概要SARIMA extends ARIMA by adding seasonal autoregressive and moving-average operators to capture repeating patterns at fixed intervals — such as monthly, quarterly, or annual cycles. Denoted SARIMA(p,d,q)(P,D,Q)s, it is the standard workhorse for univariate seasonal time series forecasting in econometrics, economics, and official statistics.The 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.
ScholarGateデータセット
  1. v1
  2. 2 出典
  3. PUBLISHED
  1. v1
  2. 2 出典
  3. PUBLISHED

検索へ スライドをダウンロード

ScholarGate手法を比較: SARIMA model · Moving Average Model. 2026-06-15に以下より取得 https://scholargate.app/ja/compare