ABSTRACT: The usefulness of time-series simulation of daily rainfall for estimating large quantiles of the distribution of 10 d seasonal maximum rainfall is questioned. The emphasis is on rare 10 d ...
The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 49, No. 3 (September/septembre 2021), pp. 698-730 (33 pages) We propose a flexible Bayesian semiparametric quantile ...
By a News Reporter-Staff News Editor at CDC& FDA Daily-- Fresh data on risk management are presented in a new report. According to news reporting out of Stephenville, Texas, by NewsRx editors, ...
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...
is 1000 times the reciprocal absolute temperature. The lognormal (base e) distribution is also available. The following SAS statements fit the Arrhenius-lognormal model, and they display the fitted ...
In this paper, we present an easy-to-implement, fast and accurate method for approximating extreme quantiles of compound loss distributions (frequency + severity), which are commonly used in insurance ...
Quantiles and expectiles analyze the regression model not only at the mean but also in the tails. Financial losses, medical insurance, auction bids, insurance claims and toxicity limits are all areas ...
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