Computer Science
8 years ago

New test outperforms popular methods in detecting communication system noise.

IEEE Transactions on Signal Processing
Empirical Likelihood Ratio Test With Distribution Function Constraints
Yingxi Liu, A.H. Tewfik

Paper Summary

The article introduces a new test for detecting problems in data analysis. This test uses distribution function constraints to improve accuracy. It performs better than other popular tests like the Kolmogorov-Smirnov and Cramér-von Mises tests, especially when the null hypothesis is nested in the alternative hypothesis. Real-world examples show the test's effectiveness, highlighting the importance of considering noise uncertainty in data analysis.

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