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Tornado damage ratings estimated with cumulative logistic regression

Tornado damage ratings estimated with cumulative logistic regression

This is a Preprint and has not been peer reviewed. This is version 2 of this Preprint.

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Authors

James B Elsner, Zoe Schroder Searcy 

Abstract

Empirical studies have led to improvements in evaluating and quantifying the tornado threat. However more work is needed to put the research onto a solid statistical foundation. Here the authors begin to build this foundation by introducing and then demonstrating a statistical model to estimate damage rating probabilities. A goal is to alert researchers to available statistical technology for improving severe weather warnings. The model is cumulative logistic regression and the parameters are determined using Bayesian inference. The model is demonstrated by estimating damage rating probabilities from values of known environmental factors on d...  more

DOI

https://doi.org/10.31223/osf.io/k9wv6

Subjects

Meteorology, Oceanography and Atmospheric Sciences and Meteorology, Physical Sciences and Mathematics, Statistics and Probability

Keywords

Bayesian inference, Atmospheric Environments, Cumulative logistic regression, Tornadoes

Dates

Published: 2019-07-18 22:13

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License

GNU Lesser General Public License (LGPL) 2.1