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To compute the two-dimensional or multi-dimensional autocorrelation function and autocorrelation density function, we can follow the following steps:
1. Define the dimensions of the data set that need to be analyzed.
2. Calculate the mean of the dataset.
3. Subtract the mean from each data point to obtain the deviation from the mean.
4. Calculate the autocovariance function by taking the product of the deviations at each pair of points separated by the distance vector.
5. Normalize the autocovariance function by dividing it by the variance of the data set.
6. Obtain the autocorrelation function by dividing the autocovariance function by the corresponding variance product.
7. Calculate the autocorrelation density function using the Fourier transform of the autocorrelation function.
By following these steps, we can obtain a more detailed analysis of the data set using autocorrelation functions and densities.