correlogram


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correlogram

[kə′rel·ə‚gram]
(mathematics)
A curve showing the assumed correlation between two mathematical variables. Also known as correlation curve.
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The extent of the autocorrelation of the response variable was obtained from the spatial correlogram 9(h) (13) of HPAI presence or absence.
The rationale behind using the effective correlation distance, D, instead of the correlogram range of significance, a, is that at the distances close to a the correlation with topography is very weak.
Following the standard approach used in the time-series literature to model macroeconomic variables over time, the optimal lag length (n) in equation (1) is selected based on (a) an inspection of the inflation correlogram of the autocorrelations and partial correlations, (b) Q tests for serial correlation in the subsequently estimated inflation equations, and (c) an inspection of the correlograms of the inflation residuals from estimated ARMA equations for inflation.
Further, we inspect the correlogram for each series as an additional test for non-stationarity.
We propose that a suitable tool for making this inference is the spline correlogram (Bjornstad and Falck 1997), a modification of the nonparametric covariance function developed by Hall and coworkers (Hall and Patil 1994, Hall et al.
Keywords: CPI inflation, WPI inflation, Unit root, Correlogram, Granger causality.
By saving residuals of VAR model (repeatedly starting from VAR with lag 2) and checking the correlogram of its residuals (to avoid the problem of autocorrelation), the optimum lag length is selected.
The stability of a time series could be graphically examined with a correlogram of its level.
However, analysis using the Mantel correlogram indicated no spatial structuring of ACL between neighboring villages, which emphasizes the highly focal distribution of ACL transmission at the village level and corroborating significant household clustering of ACL.
Different tools exist in geostatistics to explore and quantify the spatial continuity of a data set, which include h-scatterplots, semivariograms, non-ergotic correlograms (N-E correlogram) and non-ergotic covariance measures (Rossi et al.
These values are subsequently represented in a correlogram that displays how autocorrelation varies with genetic distance to determine if and where phylogenetic patterns are located.
In the present application, the Assumptions 1 and 2 imply that all of the stochastic disturbances share the same serial correlogram or equivalently, spectral density function.