Barnard, Roger W. Perera, Chamila Surles, James G. Trindade, A. Alexandre
Published in
Journal of Statistical Distributions and Applications

Motivated by an engineering pullout test applied to a steel strip embedded in earth, we show how the resulting linearly decreasing force leads naturally to a new distribution, if the force under constant stress is modeled via a three-parameter Weibull. We term this the LDSWeibull distribution, and show that inference on the parameters of the underl...

Acero, F. J. Vaquero, J. M. Gallego, M. C. García, J. A.
Published in
Solar Physics

Extreme Value Theory, a statistical tool widely used to study extreme events in time series corresponding to a broad range of fields, is here used to study the solar radio flux at 10.7 cm at a daily scale for the period 1948 – 2018. The peaks-over-threshold approach is taken to study the parameters of the distribution of the extreme values over a h...

Daouia, Abdelaati Girard, Stéphane Stupfler, Gilles

The class of quantiles lies at the heart of extreme-value theory and is one of the basic tools in risk management. The alternative family of expectiles is based on squared rather than absolute error loss minimization. It has recently been receiving a lot of attention in actuarial science, econometrics and statistical finance. Both quantiles and exp...

Schellander, Harald Hell, Tobias
Published in
Natural Hazards

Maps of extreme snow depths are important for structural design and general risk assessment in mountainous countries like Austria. The smooth modeling approach is commonly accepted to provide more accurate margins than max-stable processes. In contrast, max-stable models allow for risk estimation due to explicitly available spatial extremal depende...

Benhadi-Marín, Jacinto
Published in
Biodiversity and Conservation

Research on ecology commonly involves the need to face datasets that contain extreme or unusual observations. The presence of outliers during data analysis has been of concern for researchers generating a lot of discussion on different methods and strategies on how to deal with them and became a recurrent issue of interest in debate forums. Systema...

Okorie, I. E. Akpanta, A. C. Ohakwe, J. Chikezie, D. C. Onyemachi, C. U. Ugwu, M. C.
Published in
Annals of Data Science

The Lagos annual maximum rainfall is modeled by the generalized extreme value distribution. Hydrologic risk measures like the probability of exceedance or recurrence, return period, and return level is given.

Rabier, Charles-Elie Delmas, Céline

We introduce a new variable selection method, suitable when the correlation between regressors is known. It is appropriate in genomics since once the genetic map has been built, the correlation is perfectly known. Our method, based on the LASSO , is original since the number of selected variables is bounded by the number of predictors, instead of b...

Daouia, Abdelaati Girard, Stéphane Stupfler, Gilles

We use tail expectiles to estimate alternative measures to the Value at Risk (VaR) and Marginal Expected Shortfall (MES), two instruments of risk protection of utmost importance in actuarial science and statistical finance. The concept of expectiles isa least squares analogue of quantiles. Both are M-quanti les as the minimizers of an asymmetric co...

Bhattacharya, A. (Ayan)

We consider discrete time branching random walk on real line where the displacements of particles coming from the same parent are allowed to be dependent and jointly regularly varying. Using the one large bunch asymptotics, we derive large deviation for the extremal processes associated to the suitably scaled positions of particles in the nth gener...

Cancelliere, Antonino
Published in
Water Resources Management

Traditional approaches to the analysis of extreme hydrological series are based on the stationarity assumption for the underlying processes, namely that the probability distribution of the hydrological variable does not change with time. Over the last decade however, a growing interest has arisen both from a scientific as well as engineering point ...