Factor copula approaches for assessing spatially dependent high-dimensional risks

<?xml version="1.0" encoding="UTF-8"?><modsCollection xmlns="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-8.xsd">
<mods version="3.8">
<titleInfo>
<title>Factor copula approaches for assessing spatially dependent high-dimensional risks</title>
</titleInfo>
<name type="personal" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20170005513">
<namePart>Xia, Míchelle</namePart>
<nameIdentifier>MAPA20170005513</nameIdentifier>
</name>
<typeOfResource>text</typeOfResource>
<genre authority="marcgt">periodical</genre>
<originInfo>
<place>
<placeTerm type="code" authority="marccountry">esp</placeTerm>
</place>
<dateIssued encoding="marc">2017</dateIssued>
<issuance>serial</issuance>
</originInfo>
<language>
<languageTerm type="code" authority="iso639-2b">spa</languageTerm>
</language>
<physicalDescription>
<form authority="marcform">print</form>
</physicalDescription>
<abstract displayLabel="Summary">In this article, we propose an innovative approach for modeling spatial dependence among losses fromvarious geographical locations.
The proposed model converts the challenging task of modeling complex spatial dependence structures into a relatively easier task of
estimating a continuous function, of which the arguments can be the coordinates of the locations. The approach is based on factor copula
models, which can capture various linear and nonlinear dependence.We use radial basis functions as the kernel smoother for estimating
the key function that models all the spatial dependence structures. A case study on a thunderstorm wind loss dataset demonstrates the
analysis and the usefulness of the proposed approach. Extensions to spatiotemporal models and to models for discrete data are briefly
introduced, with an example given for modeling loss frequency with excess zeros.</abstract>
<note type="statement of responsibility">Leí Hua, Míchelle Xia, and Sanjíb Basu</note>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20090035034">
<topic>Modelización mediante cópulas</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080591182">
<topic>Gerencia de riesgos</topic>
</subject>
<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080579258">
<topic>Cálculo actuarial</topic>
</subject>
<classification authority="">6</classification>
<relatedItem type="host">
<titleInfo>
<title>North American actuarial journal</title>
</titleInfo>
<originInfo>
<publisher>Schaumburg : Society of Actuaries, 1997-</publisher>
</originInfo>
<identifier type="issn">1092-0277</identifier>
<identifier type="local">MAP20077000239</identifier>
<part>
<text>01/03/2017 Tomo 21 Número 1 - 2017 , p. 147-160</text>
</part>
</relatedItem>
<recordInfo>
<recordContentSource authority="marcorg">MAP</recordContentSource>
<recordCreationDate encoding="marc">170511</recordCreationDate>
<recordChangeDate encoding="iso8601">20170517163341.0</recordChangeDate>
<recordIdentifier source="MAP">MAP20170014478</recordIdentifier>
<languageOfCataloging>
<languageTerm type="code" authority="iso639-2b">spa</languageTerm>
</languageOfCataloging>
</recordInfo>
</mods>
</modsCollection>