Components of the two-sided Kolmogorov-Smirnov test in signal detection problems with Gaussian white noise

DOI10.1016/0378-3758(91)90007-2zbMath0747.62041OpenAlexW1966961941WikidataQ127497472 ScholiaQ127497472MaRDI QIDQ1193963

Holger Drees, Hartmut Milbrodt

Publication date: 27 September 1992

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(91)90007-2

zbMATH Keywords

Brownian motionGaussian white noisesignal detectioncurvature of the power functionL2- generated regression modelsprincipal components decompositiontwo-sided Kolmogorov-Smirnov test

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Survival analysis and censored data (62N99) Inference from stochastic processes (62M99)

Related Items (5)

Principal component decomposition of non-parametric tests ⋮ The one‐sided Kolmogorov‐Smirnov test in signal detection problems with Gaussian white noise ⋮ Regions of alternatives with high and low power for goodness-of-fit tests ⋮ Vanishing shortcoming and asymptotic relative efficiency. ⋮ Global power functions of goodness of fit tests.

Cites Work

• On the asymptotic power of the two-sided Kolmogorov-Smirnov test
• Gaussian measures in Banach spaces
• Asymptotic Theory of Certain "Goodness of Fit" Criteria Based on Stochastic Processes
• On Certain Confidence Contours for Distribution Functions
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