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

Arbeitspapier

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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: SFB 649 Discussion Paper ; No. 2015-029

Classification and Topics

• Classification: Wirtschaft ; Hypothesis Testing: General ; Statistical Simulation Methods: General ; Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models ; Climate; Natural Disasters and Their Management; Global Warming
• Subject: change point ; trend test ; tropical storms ; expectiles ; functional data analysis

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Burdejova, Petra ; Härdle, Wolfgang Karl ; Kokoszka, Piotr ; Xiong, Q.
• Event: Veröffentlichung
• (who): Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
• (where): Berlin
• (when): 2015

Further information

• Handle: http://hdl.handle.net/10419/119422
• Last update: 10.03.2025, 11:45 AM CET