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

Author

Listed:
  • Burdejova, P.
  • Härdle, W.
  • Kokoszka, P.
  • Xiong, Q.

Abstract

Motivated by the conjectured existence of trends in the intensity of tropical storms, new inferential methodology to detect a trend in the annual pattern of environmental data is developed. It can be applied to any data which form a time series of functions. Other examples include annual temperature or daily pollution curves at specific locations. Within a framework of a functional regression model, two tests of significance of the slope function are derived. 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.

Suggested Citation

  • Burdejova, P. & Härdle, W. & Kokoszka, P. & Xiong, Q., 2017. "Change point and trend analyses of annual expectile curves of tropical storms," Econometrics and Statistics, Elsevier, vol. 1(C), pages 101-117.
    • Handle: RePEc:eee:ecosta:v:1:y:2017:i:c:p:101-117
    DOI: 10.1016/j.ecosta.2016.09.002
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    1. Gromenko, Oleksandr & Kokoszka, Piotr, 2013. "Nonparametric inference in small data sets of spatially indexed curves with application to ionospheric trend determination," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 82-94.
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    6. Schnabel, Sabine K. & Eilers, Paul H.C., 2009. "Optimal expectile smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4168-4177, October.
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    Cited by:

    1. Petra Burdejová & Wolfgang K. Härdle, 2019. "Dynamic semi-parametric factor model for functional expectiles," Computational Statistics, Springer, vol. 34(2), pages 489-502, June.
    2. repec:hum:wpaper:sfb649dp2017-027 is not listed on IDEAS
    3. Tran, Ngoc M. & Burdejová, Petra & Ospienko, Maria & Härdle, Wolfgang K., 2019. "Principal component analysis in an asymmetric norm," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 1-21.
    4. Kokoszka, Piotr & Oja, Hanny & Park, Byeong & Sangalli, Laura, 2017. "Special issue on functional data analysis," Econometrics and Statistics, Elsevier, vol. 1(C), pages 99-100.
    5. repec:hum:wpaper:sfb649dp2016-040 is not listed on IDEAS

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    Keywords

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    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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