Enhanced System for Detection of Randomness in Sparse Time Series Distributions

A two-step method and apparatus are provided for automatically characterizing the spatial arrangement among the data points of a time series distribution in a data processing system wherein the classification of said time series distribution is required. In a first stage, the method and apparatus utilize a grid in Cartesian coordinates to determine (1) the number of cells in the grid containing at least one input data point of the time series distribution; (2) the expected number of cells which would contain at least one data point in a random distribution in said grid; and (3) an upper and lower probability of false alarm above and below said expected value utilizing a discrete binomial probability relationship in order to analyze the randomness characteristic of the input time series distribution. In a second stage, a statistical test of significance of the sparse data is utilized to determine the existence of noise and/or signal whereby a comparison of the results from the first stage and the second stage increase the probability of distinguishing noise from signal.