Decision Sciences
2 years ago

New Big Data Test Faster and More Effective in Identifying Distribution Changes

arXiv (Cornell University)
A Stream-Suitable Kolmogorov-Smirnov-Type Test for Big Data Analysis
Hien D. Nguyen

Paper Summary

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Scientists have developed a new test called CAKS GoF to analyze Big Data streams. This test is based on the traditional Kolmogorov-Smirnov test but is more suitable for large datasets. The CAKS test can detect changes in distribution related to mean, variance, and shape faster than the KS test. It is effective for sample sizes of 10^9 and beyond, making it a valuable tool for analyzing Big Data.