Correlograms and Covariance Analysis

Correlograms and Covariance plots allow you to visualize both negative and positive autocorrelation when present – values near zero indicate no autocorrelation for that lag class interval.

Moran's I

Moran’s I is similar in interpretation to the Pearson’s Product Moment correlation statistic for independent samples in that autocorrelation values range between -1.0 and 1.0 depending on the degree of correlation.

Fractal Analysis

The fractal dimension D , also called the Hausdorff-Besicovitch statistic, can be calculated as the slope of a log-log variogram plot. GS+ provides both D and its standard error.

Additional Autocorrelation Measures

Standardized Variograms

Compute variograms as a proportion of sample variance

Madograms and Rodograms

Compute semivariance using differences or square roots of the distance interval pairs

Drift or Trend Analysis

Detect underlying trends in your data

General Relative Variogram

Standardize semivariance by the squared mean of the data used for each distance interval

Pairwise Relative Variograms

Normalize semivariance by the squared average of tail and head values of each distance interval