Autocorrelation

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Autocorrelation

The correlation of a variable with itself over successive time intervals. Sometimes called serial correlation.

Serial Correlation

In technical analysis, a measure of how well past occurrences predict future occurrences. Most importantly, serial correlation checks whether and how often a particular price movement will result in a different price movement. Serial correlation lies at the heart of technical analysis. It is also called autocorrelation.
References in periodicals archive ?
Natural mortality was fixed at a single value in the estimation method across all years equal to the mean value that was used to generate the autocorrelated annual deviations in the operating model.
Gong, "Multisensor distributed weighted Kalman filter fusion with network delays, stochastic uncertainties, autocorrelated, and cross-correlated noises," IEEE Transactions on Systems Man and Cybernetics Systems, vol.
Hence, results of this specification might be misleading due to mis-specified dynamics and/or the presence of autocorrelated errors.
Zhou, "Autoregressive coefficient-invariant control chart pattern recognition in autocorrelated manufacturing processes using neural network ensemble," Journal of Intelligent Manufacturing, vol.
To overcome the effect of autocorrelated errors, Aitken [13] proposed the generalized least squares estimator (GLSE) for [beta] in (1) which can be obtained by applying least squares technique in model (3) as
The p-values reported for AR(1) and AR(2) are the p-values for first and second-order autocorrelated disturbances.
For example, an optimal KF is presented for linear dynamic systems with sensor noises cross-correlated [8]and a distributed weighted robust KF fusion is studied for a class of uncertain systems with autocorrelated and cross-correlated noises [7].
The second examines the hypothesis that the errors are not autocorrelated. The third tests the presence of a unit root.
Even for oysters, however, the ecological memory embedded in the population would suggest that interannual variability frequently should be positively autocorrelated; that is, shifts in population metrics should occur over multiyear time scales.
We used Bayesian statistical approach to quantify a spatially autocorrelated random effects.
At a lag of one month, the weather effects are significantly negatively autocorrelated. This is because they are estimates of the weather effects in month-over-month changes.
This indicates that in Alberta, immunization rates are more spatially autocorrelated, i.e., more self-similar over short distances, in 2012 than in 2008.