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There is no test to prove a distribution is non-normal stable. However there are tests that indicate stability. One of these is a test for infinite variance. For the normal (a special case of stable) distribution the variance converges to a finite real number as ... grows without bounds. When tails are heavy (stable ... ) variance does not exist or is infinite. Granger and Orr (1972) devised a running variance test for infinite variance that is displayed here. Note that when ... , the distribution is normal and the plot of the test shows the variance converging. At lower levels of ... the plot remains "wild" indicating infinite or nonexistent variance.

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      EUN,LOM,LRE4,work-cmr-id:398603,http://demonstrations.wolfram.com:http://demonstrations.wolfram.com/GrangerOrrRunningVarianceTest/,ilox,learning resource exchange,LRE metadata application profile,LRE

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