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a_correlate2d.pro

This function computes the autocorrelation Px(K,L) or autocovariance Rx(K,L) of a sample population X[nx,ny] as a function of the lag (K,L).

Routine summary

result = auto_cov2d(X, Lag, Double=Double, zero2nan=zero2nan)

result = a_correlate2d(X, Lag, Covariance=Covariance, Double=Double)

topauto_cov2d Statistics

result = auto_cov2d(X, Lag, Double=Double, zero2nan=zero2nan)

Parameters

X        in required

An 2 dimension Array [nx,ny]

Lag        in required

2-element vector, in the intervals [-(nx-2), (nx-2)],[-(ny-2), (ny-2)], of type integer that specifies the absolute distance(s) between indexed elements of X.

Keywords

Double       

If set to a non-zero value, computations are done in double precision arithmetic.

zero2nan       

Version history

Version

$Id: a_correlate2d.pro 163 2006-08-29 12:59:46Z navarro $

History

28/2/2000 Sebastien Masson (smasson@lodyc.jussieu.fr) Based on the A_CORRELATE procedure of IDL

Statistics

McCabe cyclic 2
McCabe essential 1
McCabe modular design 1

topa_correlate2d Statistics

result = a_correlate2d(X, Lag, Covariance=Covariance, Double=Double)

Parameters

X        in required

An 2 dimension Array [nx,ny]

Lag        in required

2-element vector, in the intervals [-(nx-2), (nx-2)],[-(ny-2), (ny-2)], of type integer that specifies the absolute distance(s) between indexed elements of X.

Keywords

Covariance       

If set to a non-zero value, the sample autocovariance is computed.

Double       

If set to a non-zero value, computations are done in double precision arithmetic.

Version history

Version

$Id: a_correlate2d.pro 163 2006-08-29 12:59:46Z navarro $

History

28/2/2000 Sebastien Masson (smasson@lodyc.jussieu.fr) Based on the A_CORRELATE procedure of IDL

Statistics

McCabe cyclic 8
McCabe essential 1
McCabe modular design 1
Produced by IDLdoc 2.0.