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Change point and trend analyses of annual expectile curves of tropical storms

By Petra Burdejova, Wolfgang Karl Härdle, Piotr Kokoszka and Qian Xiong

Abstract

Motivated by the conjectured existence of trends in the intensity of tropical storms, this paper proposes new inferential methodology to detect a trend in the annual pattern of environmental data. The new methodology can be applied to data which can be represented as annual curves which evolve from year to year. Other examples include annual temperature or log–precipitation curves at specific locations. Within a framework of a functional regression model, we derive two tests of significance of the slope function, which can be viewed as the slope coefficient in the regression of the annual curves on year. One of the tests relies on a Monte Carlo distribution to compute the critical values, the other is pivotal with the chi– square limit distribution. Full asymptotic justification of both tests is provided. Their finite sample properties are investigated by a simulation study. Applied to tropical storm data, these tests show that there is a significant trend in the shape of the annual pattern of upper wind speed levels of hurricanes

Topics: change point, trend test, tropical storms, expectiles, functional data analysis, 310 Statistik, 330 Wirtschaft, ddc:310, ddc:330
Publisher: Humboldt-Universität zu Berlin, IRI THESys
Year: 2015
OAI identifier: oai:edoc.hu-berlin.de:18452/3782
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