Data-driven smooth tests for the extreme value distribution

DOI10.1080/02331880410001692967zbMath1085.62049OpenAlexW2048337535MaRDI QIDQ4663085

Alicja Janic-Wróblewska

Publication date: 30 March 2005

Published in: Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331880410001692967

zbMATH Keywords

Monte Carlo studygoodness-of-fitWeibull distributionSchwarz's rulesmooth testNeyman testeffective score test

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Statistics of extreme values; tail inference (62G32)

Related Items (2)

Data-driven smooth tests for a location-scale family revisited ⋮ Review of testing issues in extremes: in honor of Professor Laurens de Haan

Cites Work

• A new class of random number generators
• Data driven smooth tests for composite hypotheses
• A men goodness-of-fit test for the two-parameter wetbull or extreme-value distribution with unknown parameters
• W-test for the weibull distribution
• On the asymptotic efficiency of certain correlation tests of fit
• A consistent correlation-type goodness-of-fit test;with application to the two-parameter weibull distribution
• Tests for departure from normality: Comparison of powers
• Goodness of fit for the extreme value distribution
• Data-Driven Version of Neyman's Smooth Test of Fit
• Data driven smooth tests for composite hypotheses comparison of powers
• Data-Driven Smooth Tests When the Hypothesis Is Composite

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