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Statistical Models Commons

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Full-Text Articles in Statistical Models

Adjusted Tornado Probabilities, Holly M. Widen, James B. Elsner, Cameron Amrine, Rizalino B. Cruz, Erik Fraza, Laura Michaels, Loury Migliorelli, Brendan Mulholland, Michael Patterson, Sarah Strazzo, Guang Xing Dec 2013

Adjusted Tornado Probabilities, Holly M. Widen, James B. Elsner, Cameron Amrine, Rizalino B. Cruz, Erik Fraza, Laura Michaels, Loury Migliorelli, Brendan Mulholland, Michael Patterson, Sarah Strazzo, Guang Xing

Publications

Tornado occurrence rates computed from the available reports are biased low relative to the unknown true rates. To correct for this low bias, the authors demonstrate a method to estimate the annual probability of being struck by a tornado that uses the average report density estimated as a function of distance from nearest city/town center. The method is demonstrated on Kansas and then applied to 15 other tornado-prone states from Nebraska to Tennessee. States are ranked according to their adjusted tornado rate and comparisons are made with raw rates published elsewhere. The adjusted rates, expressed as return periods, arestates, including …


Pricing And Hedging Index Options With A Dominant Constituent Stock, Helen Cheyne Aug 2013

Pricing And Hedging Index Options With A Dominant Constituent Stock, Helen Cheyne

Electronic Thesis and Dissertation Repository

In this paper, we examine the pricing and hedging of an index option where one constituents stock plays an overly dominant role in the index. Under a Geometric Brownian Motion assumption we compare the distribution of the relative value of the index if the dominant stock is modeled separately from the rest of the index, or not. The former is equivalent to the relative index value being distributed as the sum of two lognormal random variables and the latter is distributed as a single lognormal random variable. Since these are not equal in distribution, we compare the two models. The …


Automating Large-Scale Simulation Calibration To Real-World Sensor Data, Richard Everett Edwards May 2013

Automating Large-Scale Simulation Calibration To Real-World Sensor Data, Richard Everett Edwards

Doctoral Dissertations

Many key decisions and design policies are made using sophisticated computer simulations. However, these sophisticated computer simulations have several major problems. The two main issues are 1) gaps between the simulation model and the actual structure, and 2) limitations of the modeling engine's capabilities. This dissertation's goal is to address these simulation deficiencies by presenting a general automated process for tuning simulation inputs such that simulation output matches real world measured data. The automated process involves the following key components -- 1) Identify a model that accurately estimates the real world simulation calibration target from measured sensor data; 2) Identify …


A Superposed Log-Linear Failure Intensity Model For Repairable Artillery Systems, Byeong Min Mun, Suk Joo Bae, Paul Kvam Jan 2013

A Superposed Log-Linear Failure Intensity Model For Repairable Artillery Systems, Byeong Min Mun, Suk Joo Bae, Paul Kvam

Department of Math & Statistics Faculty Publications

This article investigates complex repairable artillery systems that include several failure modes. We derive a superposed process based on a mixture of nonhomogeneous Poisson processes in a minimal repair model. This allows for a bathtub-shaped failure intensity that models artillery data better than currently used methods. The method of maximum likelihood is used to estimate model parameters and construct confidence intervals for the cumulative intensity of the superposed process. Finally, we propose an optimal maintenance policy for repairable systems with bathtub-shaped intensity and apply it to the artillery-failure data.