Extreme Value Theory Applied to r Largest Order Statistics Under the Bayesian Approach
نویسندگان
چکیده
منابع مشابه
Automated selection of r for the r largest order statistics approach with adjustment for sequential testing
The r largest order statistics approach is widely used in extreme value analysis because itmay usemore information from the data than just the block maxima. In practice, the choice of r is critical. If r is too large, bias can occur; if too small, the variance of the estimator can be high. The limiting distribution of the r largest order statistics, denoted byGEVr , extends that of the block ma...
متن کاملHitting Time Statistics and Extreme Value Theory
We consider discrete time dynamical system and show the link between Hitting Time Statistics (the distribution of the first time points land in asymptotically small sets) and Extreme Value Theory (distribution properties of the partial maximum of stochastic processes). This relation allows to study Hitting Time Statistics with tools from Extreme Value Theory, and vice versa. We apply these resu...
متن کامل"Slip and fall" theory--extreme order statistics.
Classical "slip and fall" analysis was reformulated in this paper to account for the stochastic nature of friction. As it turned out, the new theory, arising from this analysis, was a precise statement of the distribution function for the smallest value among n independent observations. This made it possible to invoke an important result from the asymptotic theory of extreme order statistics th...
متن کاملThe extreme value theory approach to safety estimation.
Crash-based safety analysis is hampered by several shortcomings, such as randomness and rarity of crash occurrences, lack of timeliness, and inconsistency in crash reporting. Safety analysis based on observable traffic characteristics more frequent than crashes is one promising alternative. In this research, we proposed a novel application of the extreme value theory to estimate safety. The met...
متن کاملA semiparametric Bayesian approach to extreme value estimation
This paper is concerned with extreme value density estimation. The generalized Pareto distribution (GPD) beyond a given threshold is combined with a nonparametric estimation approach below the threshold. This semiparametric setup is shown to generalize a few existing approaches and enables density estimation over the complete sample space. Estimation is performed via the Bayesian paradigm, whic...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Revista Colombiana de Estadística
سال: 2019
ISSN: 2389-8976,0120-1751
DOI: 10.15446/rce.v42n2.70271