autocorrelation

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autocorrelation

A measure of how closely a signal in a time series resembles a time-delayed image of itself—periodic signals are highly autocorrelated; random signals are not.
References in periodicals archive ?
We used time-series analysis, taking into account lagged effects, autocorrelation, and the seasonal fluctuation in incidences of foodborne illness.
Changes in level or autocorrelations that decline slowly at longer lags require first-order differencing, whereas slope changes require second-order differencing.
To analyze the randomness of the return series we used autocorrelations and Ljung-Box Q statistics and Table 3 shows the corresponding output.
This was supported by large autocorrelation coefficients, using Ljung-Box Q Statistic test, for residuals at a lags of 1 and 2 months from the simple monthly linear regression models.
Classical statistical inference such as conventional regressions are inadequate for an in-depth spatial analysis since they fail to take into account spatial effects and problems of spatial data analysis such as spatial autocorrelation, identification of spatial clusters and outliers, edge effects, modifiable areal unit problem, and lack of spatial independence [Arbia, Benedetti, and Espa (1996); Beck, Gleditsch, and Beardsley (2006); Franzese and Hays (2007)].
14) When we control for market risk, the residual autocorrelations decrease substantially relative to the regression with just the political dummy variable and generally become statistically insignificant at conventional levels.
The partial autocorrelations of x, y, and x + y have been calculated by computing the sum in Definition 1.
Binary codes with low autocorrelation sidelobe levels and high Discriminating factors are useful for radar pulse compression [4], channel estimation, and spread spectrum communication applications.
Although the full and partial autocorrelations of the LNSPRT series exhibit short-term autoregressive and moving average patterns, plus a seasonal moving-average pattern (see autocorrelation estimates below), the full short-term AR-MA component was not jointly estimable.
The results from the data for the period after AGOA (Table 4) reveal an autocorrelation function (ACF) that seems to show a typical autoregressive process:
These properties can be characterized by the autocorrelation function (ACF) and partial autocorrelation function (PACF).
2) Investigation of estimated autocorrelation function (ACF) of time series is a more objective method.