NAME: A_CORRELATE2d PURPOSE: 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). CATEGORY: Statistics. CALLING SEQUENCE: Result = a_correlate2d(X, Lag) INPUTS: X: an 2 dimension Array [nx,ny] LAG: 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. KEYWORD PARAMETERS: 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. EXAMPLE: PROCEDURE: nx-k-1 ny-l-1 sigma sigma (X[i,j]-Xmean)(X[i+k,j+l]-Ymean) i=0 j=0 correlation(X,[k,l])=------------------------------------------------------ nx-1 ny-1 sigma sigma (X[i,j]-Xmean)^2) i=0 j=0 nx-k-1 ny-l-1 sigma sigma (X[i,j]-Xmean)(Y[i+k,j+l]-Ymean) i=0 j=0 covariance(X,[k,l])=------------------------------------------------------ nx*ny Where Xmean is the mens of the sample population x=(x[0,0],x[1,0],...,x[nx-1,ny-1]). REFERENCE: MODIFICATION HISTORY: