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 ?
The results of this comparison show that, for significantly autocorrelated data, the use of the ARIMA control chart will provide a more consistent technique for detecting assignable or special causes in the continuous production processes.
Furthermore, tick density on a cliff was autocorrelated between years (n = 66, P [less than] 0.
The use of lagged values of the dependent variable as RHS variables represents a fairly standard approach to correct serial correlation that would be caused by an autocorrelated dependent variable: see Granger and Newbold (1974).
Finally, inflation is much more autocorrelated in the data--the AR(1) coefficient is 0.
It shows that all these intervals are centered around the unit root and are slightly wider if the disturbances are weakly autocorrelated.
Although generalized linear mixed models generated more robust results with spatially autocorrelated data and uneven sampling, it is unclear how well these models perform given low sample sizes.
The p-values reported for AR(1) and AR(2) are the p-values for first and second-order autocorrelated disturbances.
A few authors, however, consider inflation to be persistent even if it is negatively autocorrelated (for details see Fuhrer (2009).
In these cases, series must be filtered with an autoregressive model, for example by using a modified Mann-Kendall test for autocorrelated series, as proposed by Hamed and Rao (1998).
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 purpose of this analysis was to examine the significance of interannual variability in parasites, pathologies, and selected physiological indices in Mussel Watch sentinel bivalves to evaluate the importance of long-term trends over a 16-y time span from 1995 to 2010, and determine the degree to which interannual changes are autocorrelated, suggesting a temporal memory or a response to cyclic environmental change in the population dynamics of the bivalve and its parasite complement.