ScholarGate
Msaidizi
Regression modelEconometrics / time series

Kipimo cha Utafiti cha Utafiti cha Bayesian Toda-Yamamoto

Utaratibu wa utafiti wa Bayesian Toda-Yamamoto unachanganya mkakati wa nyongeza wa Toda-Yamamoto VAR — ambao unajiepusha na hitaji la kupima kabla ya ujumuishi na ushirikiano — na sasisho la Bayesian kutoka awali hadi baadae. Unapima kutosababisha kwa Granger kati ya mfululizo wa muda ambao unaweza kuwa umeunganishwa au kushirikiana bila kuhitaji kupunguza tofauti au uundaji wa marekebisho ya makosa, huku ukijumuisha habari za awali na kutoa usambazaji kamili wa baadae juu ya vigezo vya kusababisha.

Tumia kupitia EconMindHivi karibuniVideoHivi karibuniDownload slides

Soma mbinu kamili

Kwa wanachama pekee

Ingia kwa akaunti ya bure ili kusoma sehemu hii.

Ingia

Method map

The neighbourhood of related methods — select a node to explore.

Kipimo cha Utafiti cha Utafiti cha Bayesian Toda-Yamamoto
Kipimo cha Granger Causa…Kipimo cha Umuhimu cha G…Ubora wa Utegemezi wa Vi…

Vyanzo

  1. Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI: 10.1016/0304-4076(94)01616-8
  2. Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471982326

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Bayesian Toda-Yamamoto Granger Causality Test. ScholarGate. https://scholargate.app/sw/econometrics/bayesian-toda-yamamoto-causality

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

Compare side by side
ScholarGateBayesian Toda-Yamamoto Causality (Bayesian Toda-Yamamoto Granger Causality Test). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/econometrics/bayesian-toda-yamamoto-causality · Seti ya data: https://doi.org/10.5281/zenodo.20539026