IDL Reference Guide: Procedures and Functions |

The A_CORRELATE function computes the autocorrelation *Px*(*L*) or autocovariance *Rx*(*L*) of a sample population *X* as a function of the lag *L*.

where
x is the mean of the sample population *x* = (*x*_{0}, *x*_{1}, *x*_{2}, ... , *x*_{N-1}).

NoteThis routine is primarily designed for use in 1-D time-series analysis. The mean is subtracted before correlating. For image processing, methods based on FFT should be used instead if more than a few tens of points exist. For example: `Function AutoCorrelate, X` |

This routine is written in the IDL language. Its source code can be found in the file `a_correlate.pro`

in the `lib`

subdirectory of the IDL distribution.

*Result* = A_CORRELATE(*X*, *Lag* [, /COVARIANCE] [, /DOUBLE] )

An *n*-element integer, single-, or double-precision floating-point vector.

An *n*-element integer vector in the interval [-(*n*-2), (*n*-2)], specifying the signed distances between indexed elements of *X*.

Set this keyword to compute the sample autocovariance rather than the sample autocorrelation.

Set this keyword to force the computation to be done in double-precision arithmetic.

; Define ann-element sample population: X = [3.73, 3.67, 3.77, 3.83, 4.67, 5.87, 6.70, 6.97, 6.40, 5.57] ; Compute the autocorrelation of X for LAG = -3, 0, 1, 3, 4, 8: lag = [-3, 0, 1, 3, 4, 8] result = A_CORRELATE(X, lag) PRINT, result

IDL prints:

0.0146185 1.00000 0.810879 0.0146185 -0.325279 -0.151684

CORRELATE, C_CORRELATE, M_CORRELATE, P_CORRELATE, R_CORRELATE, Correlation Analysis

IDL Online Help (March 06, 2007)