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Detection of randomness in sparse data set of three dimensional time series distributions
Detection of randomness in sparse data set of three dimensional time series distributions
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机译:三维时间序列分布的稀疏数据集中的随机性检测
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摘要
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.
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