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A time series is said to be autocorrelated if it is possible to predict the value of the series at a given time from recent measured values of the series. For example, yesterday's temperature at noon is often a good predictor of today's temperature at noon; and the value of stock market indices similarly bears stronger resemblance to immediately previous values than to historic values. Underlying these observations is the notion that some phenomena vary relatively slowly through time. Spatial autocorrelation refers to similar behavior in space, though unlike the temporal case, space may be twoor even three-dimensional. A general statement by Tobler, often termed Tobler's first law of geography, asserts that spatial autocorrelation is positive for almost all geographic phenomena.

Numerous indices of spatial autocorrelation ...

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