Masters Theses

Author

Tobias Merk

Abstract

"Insurance claims caused by natural disasters exhibit spatial dependence with the strength of dependence being based on factors such as physical distance and population density, to name a few. Accounting for spatial dependence is therefore of crucial importance when modeling these types of claims. In this work, we present an approach to assess spatially dependent insurance risks using a combination of linear regression and factor copula models. Specifically, in loss modeling, observed dependence patterns are highly nonlinear, thus copula-based models seem appropriate since they can handle both linear and nonlinear dependence. The factor copula approach for estimating the spatial dependence reduces a complex dependence structure into a relatively easier task of estimating a spatial dependence parameter. Hence, we use a weighted sum of radial basis functions to model a spatial dependence parameter that determines the influence of each location. The methodology is illustrated using a thunderstorm wind loss dataset of Texas. Extensions to Matérn covariance functions and spatiotemporal models are briefly discussed"--Abstract, page iii.

Advisor(s)

Adekpedjou, Akim

Committee Member(s)

Olbricht, Gayla R.
Samaranayake, V. A.

Department(s)

Mathematics and Statistics

Degree Name

M.S. in Applied Mathematics

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2018

Pagination

viii, 69 pages

Note about bibliography

Includes bibliographic references (pages 65-68).

Geographic Coverage

Texas

Rights

© 2018 Tobias Merk, All rights reserved.

Document Type

Thesis - Open Access

File Type

text

Language

English

Thesis Number

T 11299

Electronic OCLC #

1041858592

Share

Thesis Location

 
COinS