পদ্ধতির তুলনা করুন

	অরৈখিক টোডা-ইয়ামামো কার্যকারণ পরীক্ষা	ভেক্টর অটো রিগ্রেশন (VAR) মডেল
ক্ষেত্র	অর্থমিতি	অর্থমিতি
পরিবার	Regression model	Regression model
উদ্ভবের বছর	1995 (base); nonlinear extensions 2000s–2010s	2005
প্রবর্তক	Toda & Yamamoto (1995) for the linear base; nonlinear extension developed by subsequent researchers applying rank transformations or neural-network-augmented VAR	Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
ধরন	Causality test	Multivariate time-series model
মৌলিক উৎস	Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250.	Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer.
অপর নাম	nonlinear TY causality, rank-based Toda-Yamamoto test, modified Wald nonlinear causality, NTY causality test	vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
সম্পর্কিত	5	4
সারসংক্ষেপ	The Nonlinear Toda-Yamamoto causality test extends the classic Toda-Yamamoto (1995) modified Wald procedure to detect causal linkages that are hidden in the means of series but manifest through nonlinear dynamics such as asymmetries, threshold effects, or volatility transmission. It fits an augmented VAR on rank-transformed or otherwise nonlinearly mapped series and applies a chi-squared Wald test on the extra-lag coefficients.	Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).