Variance Decomposition

In econometrics and other applications of multivariate time series analysis, a variance decomposition or forecast error variance decomposition is used to aid in the interpretation of a vector autoregression (VAR) model once it has been fitted. The variance decomposition indicates the amount of information each variable contributes to the other variables in the autoregression. It determines how much of the forecast error variance of each of the variables can be explained by exogenous shocks to the other variables.

Read more about Variance Decomposition:  Calculating The Forecast Error Variance

Famous quotes containing the word variance:

    There is an untroubled harmony in everything, a full consonance in nature; only in our illusory freedom do we feel at variance with it.
    Fyodor Tyutchev (1803–1873)