Nonhomogeneous Poisson model for volcanic eruptions |
| |
| Authors: | Chih-Hsiang Ho |
| |
| Institution: | (1) Department of Mathematical Sciences, University of Nevada-Las Vegas, 4505 Maryland Parkway, 89154 Las Vegas, Nevada |
| |
| Abstract: | A simple Poisson process is more specifically known as a homogeneous Poisson process since the rate was assumed independent of time t. The homogeneous Poisson model generally gives a good fit to many volcanoes for forecasting volcanic eruptions. If eruptions occur according to a homogeneous Poisson process, the repose times between consecutive eruptions are independent exponential variables with mean =1/. The exponential distribution is applicable when the eruptions occur  at random and are not due to aging, etc. It is interesting to note that a general population of volcanoes can be related to a nonhomogeneous Poisson process with intensity factor(t). In this paper, specifically, we consider a more general Weibull distribution, WEI (,  ), for volcanism. A Weibull process is appropriate for three types of volcanoes: increasing-eruption-rate (>1), decreasing-eruption-rate (<1), and constant-eruption-rate (=1). Statistical methods (parameter estimation, hypothesis testing, and prediction intervals) are provided to analyze the following five volcanoes: Also, Etna, Kilauea, St. Helens, and Yake-Dake. We conclude that the generalized model can be considered a goodness-of-fit test for a simple exponential model (a homogeneous Poisson model), and is preferable for practical use for some nonhomogeneous Poisson volcanoes with monotonic eruptive rates. |
| |
| Keywords: | prediction interval volcanism Weibull distribution |
| 本文献已被 SpringerLink 等数据库收录！ |
|
