DETECTION OF RANDOMNESS IN SPARSE DATA SET OF THREE DIMENSIONAL TIME SERIES DISTRIBUTIONS

A two-stage method is provided for automatically characterizing the spatial arrangement among data points of a three-dimensional time series distribution in a data processing system wherein the classification of this time series distribution is required. The invention utilizes two-stage method Cartesian grids to determine (1) the number of cubes in the grids containing at least one input data point of the time series distribution; (2) the expected number of cubes which would contain at least one data point in a statistically determined random distribution in these grids; and (3) an upper and lower probability of false alarm above and below this expected value utilizing a second discrete probability relationship in order to analyze the randomness characteristic of the input time series distribution.