ScholarGate
Pembantu

Bandingkan kaedah

Semak kaedah pilihan anda secara bersebelahan; baris yang berbeza akan diserlahkan.

Model Autoregresif (AR)×Ujian Kausaliti Granger×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal1970s (popularised 1976)1969
PengasasGeorge E. P. Box and Gwilym M. JenkinsClive W. J. Granger
JenisTime series modelCausality test (F-test on VAR)
Sumber perintisBox, G. E. P., & Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0816211043Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438. DOI ↗
AliasAR model, AR(p) model, autoregression, AR processGranger test, GC test, predictive causality test, Granger non-causality test
Berkaitan65
RingkasanAn 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.The Granger causality test is a statistical hypothesis test that determines whether past values of one time series help predict future values of another, beyond what that series' own past already explains. Introduced by Clive Granger in 1969, it is the standard approach for assessing predictive causality in VAR-based time-series analysis.
ScholarGateSet data
  1. v1
  2. 2 Sumber
  3. PUBLISHED
  1. v1
  2. 2 Sumber
  3. PUBLISHED

Pergi ke carian Muat turun slaid

ScholarGateBandingkan kaedah: Autoregressive model · Granger Causality Test. Dicapai 2026-06-17 daripada https://scholargate.app/ms/compare