পদ্ধতির তুলনা করুন

	বেয়েশীয়ান গ্র্যাঞ্জার কার্যকারণ	টোডা-ইয়ামামো তোষণ পরীক্ষা (Toda-Yamamoto Causality Test)
ক্ষেত্র	অর্থমিতি	অর্থমিতি
পরিবার	Regression model	Regression model
উদ্ভবের বছর	1969 (frequentist); 1984 (Bayesian treatment)	1995
প্রবর্তক	Clive W. J. Granger (frequentist basis, 1969); Bayesian extension by Geweke (1984) and subsequent literature	Toda, H. Y. and Yamamoto, T.
ধরন	Bayesian causal inference test	Causality test
মৌলিক উৎস	Geweke, J. (1984). Inference and causality in economic time series models. Handbook of Econometrics, 2, 1101-1144. Elsevier.	Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250.
অপর নাম	Bayesian Granger test, Bayesian predictive causality, BGC, Bayesian causality in mean	Toda-Yamamoto test, TY causality test, modified Wald test for Granger causality, TY-MWALD
সম্পর্কিত	6	5
সারসংক্ষেপ	Bayesian Granger causality tests whether past values of one time series carry predictive information about another, framing the hypothesis through Bayesian inference rather than frequentist p-values. It combines a vector autoregressive (VAR) structure with prior distributions over coefficients and evaluates causal claims via posterior probabilities or Bayes factors, providing a probabilistic and nuanced alternative to the classical Granger test.	The Toda-Yamamoto (TY) causality test is a modified Wald procedure for testing Granger causality in vector autoregressions (VARs) estimated in levels, even when variables are nonstationary or cointegrated. By intentionally over-fitting the VAR with extra lags equal to the maximum integration order, it restores the standard chi-squared asymptotic distribution of the Wald statistic without requiring prior unit-root or cointegration pretesting.