autoregression sentence in Hindi
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- In econometrics and other applications of multivariate time series analysis, a "'variance decomposition "'or "'forecast error variance decomposition "'( FEVD ) is used to aid in the interpretation of a vector autoregression ( VAR ) model once it has been fitted.
- :The OP could try becoming proficient with R ( programming language ), could read Granger causality, Vector autoregression, and other econometrics texts about the dangers of over-fitting, could obtain a wide set of financial and economic time series, and then could put them all together and reach some conclusion.
- Third, the principle that effects cannot precede causes can be invoked, by including on the right side of the regression only variables that precede in time the dependent variable; this principle is invoked, for example, in testing for Granger causality and in its multivariate analog, vector autoregression, both of which control for lagged values of the dependent variable while testing for causal effects of lagged independent variables.
- Second, in the MA model a shock affects X values only for the current period and " q " periods into the future; in contrast, in the AR model a shock affects X values infinitely far into the future, because \ varepsilon _ t affects X _ t, which affects X _ { t + 1 }, which affects X _ { t + 2 }, and so on forever ( see Vector autoregression # Impulse response ).
- The Royal Statistical Society, UK, awarded him their Guy Medal in Silver in 2007 in recognition of his " . . . many important contributions to time series analysis over a distinguished career and in particular for his fundamental and highly influential paper " Threshold autoregression, limit cycles and cyclical data ", read to the Society in 1980, which paved the way for a major body of work in non-linear time series modelling . " In 2012, the International Chinese Statistical Association awarded him the Distinguished Achievement Award.
- If \ rho is not known, then it is estimated by first regressing the untransformed model and obtaining the residuals { \ hat { \ varepsilon } _ t }, and regressing \ hat { \ varepsilon } _ t on \ hat { \ varepsilon } _ { t-1 }, leading to an estimate of \ rho and making the transformed regression sketched above feasible . ( Note that one data point, the first, is lost in this regression . ) This procedure of autoregressing estimated residuals can be done once and the resulting value of \ rho can be used in the transformed " y " regression, or the residuals of the residuals autoregression can themselves be autoregressed in consecutive steps until no substantial change in the estimated value of \ rho is observed.
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