autocorrelation

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autocorrelation

[¦ȯd·ō‚kär·ə′lā·shən]
(electronics)
A technique used to detect cyclic activity in a complex signal.
(statistics)
In a time series, the relationship between values of a variable taken at certain times in the series and values of a variable taken at other, usually earlier times.
References in periodicals archive ?
Autocorrelated errors were specified between adjacent error terms of the manifest indicators (for test scores at Times 1, 2, 3, and 4).
8) Assessing how public liabilities respond to a shock in the surplus to GDP, conditional on surpluses being positively and persistently autocorrelated, in a monetary dominant regime, an increase (or positive shock in the current surplus leads to a fall in future liabilities to guarantee fiscal solvency.
We recognize that making population level inferences from four autocorrelated subsamples, taken from a single individual, implies numerous assumptions including: the single specimen grew in a similar way to all northern California abalone, that [sup.
SEM is an innovative technique for such studies, in dealing effectively with multiple structural equations, autocorrelated panel data, unobserved underlying factors, and other issues that are not simultaneously addressed in other methodologies.
On the other hand, the MLE method permits modelers to account for spatially autocorrelated error terms.
However, some mathematical manipulations are required to pre-whiten autocorrelated noise terms within the algorithm.
To analyze the relationship between rates of maltreatment by child race or ethnicity, we used spatial regression models that assess and control for spatially autocorrelated errors.
where P contains an nx1 vector of spatially autocorrelated variables, W is a row normalized nxn connectivity matrix, [rho] is the 'global' estimate of spatial interdependency, and [epsilon] is a normally distributed vector of error terms (Anselin 1988).
The effects of temporally autocorrelated data on methods of home-range analysis.
He then proceeds to information about test estimation include simple models, Stein-type estimation, the ANOVA model, the parallelism model, the multiple regression model, stochastic subspace in the regression model, ridge regression, regression models with autocorrelated errors, multivariate models, and discrete data models.
To determine magnitude of change in the treatment, generalization, and control probes relative to the timing of conditions, we performed an independent time series analysis of autocorrelated data (ITSACORR) [22] using all baseline points for the pretreatment phase and the final two data points for the posttreatment phase.

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