Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/119422
Authors: 
Burdejova, P.
Härdle, W. K.
Kokoszka, Piotr
Xiong, Q.
Year of Publication: 
2015
Series/Report no.: 
SFB 649 Discussion Paper 2015-029
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.
Subjects: 
change point
trend test
tropical storms
expectiles
functional data analysis
JEL: 
C12
C15
C32
Q54
Document Type: 
Working Paper

Files in This Item:
File
Size
839.93 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.