Gradient boosting for extreme quantile regression

Extreme quantile regression provides estimates of conditional quantiles outside the range of the data. Classical quantile regression performs poorly in such cases since data in the tail region are too scarce. Extreme value theory is used for extrapolation beyond the range of observed values and estimation of conditional extreme quantiles....

Are collision and crossing course surrogate safety indicators transferable?: A probability based approach using extreme value theory

In order to overcome the shortcomings of crash data a number of surrogate measures of safety have been developed and proposed by various researchers. One of the most widely used temporal indicators is time-to-collision (TTC) which requires the road users to be on a collision course. Road users that are strictly speaking not on a collision...

On the tails of the wind ramp distributions

We analyzed several multiyear wind speed datasets from 4 different geographical locations. The probability density functions of wind ramps from all these sites revealed remarkably similar shapes. The tails of the probability density functions are much heavier than a Gaussian distribution, and they also systematically depend on time increments....

Extreme value theory, Poisson-Dirichlet distributions, and first passage percolation on random networks

We study first passage percolation (FPP) on the configuration model (CM) having power-law degrees with exponent ? ? [1, 2) and exponential edge weights. We derive the distributional limit of the minimal weight of a path between typical vertices in the network and the number of edges on the minimal-weight path, both of which can be computed in...