ebook img

Elements of Copula Modeling with R PDF

274 Pages·2018·65.43 MB·English
Save to my drive
Quick download
Download
Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.

Preview Elements of Copula Modeling with R

UseR! Marius Hofert · Ivan Kojadinovic  Martin Mächler · Jun Yan Elements of Copula Modeling with R Use R! Serieseditors RobertGentleman KurtHornik GiovanniParmigiani Moreinformationaboutthisseriesathttp://www.springer.com/series/6991 Marius Hofert • Ivan Kojadinovic (cid:129) ¨ Martin Machler (cid:129) Jun Yan Elements of Copula Modeling with R 123 MariusHofert IvanKojadinovic DepartmentofStatisticsandActuarial LaboratoryofMathematicsandits Science Applications UniversityofWaterloo UniversityofPauandPaysdel’Adour Waterloo,Ontario,Canada Pau,France MartinMa¨chler JunYan SeminarforStatistics DepartmentofStatistics ETHZurich UniversityofConnecticut Zurich,Switzerland Storrs,Connecticut,USA ISSN2197-5736 ISSN2197-5744 (electronic) UseR! ISBN978-3-319-89634-2 ISBN978-3-319-89635-9 (eBook) https://doi.org/10.1007/978-3-319-89635-9 LibraryofCongressControlNumber:2018940269 MathematicsSubjectClassification(2010):62H05,65C10,62H12,62H15,62P05,62P12,65C60 ©SpringerInternationalPublishingAG,partofSpringerNature2018 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpartof thematerialisconcerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation, broadcasting,reproductiononmicrofilmsorinanyotherphysicalway,andtransmissionorinformation storageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilarmethodology nowknownorhereafterdeveloped. Theuseofgeneraldescriptivenames,registerednames,trademarks,servicemarks,etc.inthispublication doesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevant protectivelawsandregulationsandthereforefreeforgeneraluse. Thepublisher,theauthorsandtheeditorsaresafetoassumethattheadviceandinformationinthisbook arebelievedtobetrueandaccurateatthedateofpublication.Neitherthepublishernortheauthorsor theeditorsgiveawarranty,expressorimplied,withrespecttothematerialcontainedhereinorforany errorsoromissionsthatmayhavebeenmade.Thepublisherremainsneutralwithregardtojurisdictional claimsinpublishedmapsandinstitutionalaffiliations. ThisSpringerimprintispublishedbytheregisteredcompanySpringerNatureSwitzerlandAG Theregisteredcompanyaddressis:Gewerbestrasse11,6330Cham,Switzerland To Saisai Nireemaztearieta haurrei,maitasunez To Liselotte,withthanksformanyhoursof waiting To Jiafeng,Bohan,andJolin,withlove Preface Theaimofthisbookistoshowhowsomeofthemainstepsinvolvedinthestatistical modelingofcontinuousmultivariatedistributionsusingcopulascanbecarriedout intheRstatisticalenvironment(RCoreTeam,2017)withtheRpackagecopula. The R package copula originally emerged from the authors’ research interests; it has been available on the Comprehensive R Archive Network (CRAN) since 2005 and has been under constant development ever since. Judging from users’ feedback,thepackageisappliedinareassuchashydrology,environmentalsciences, quantitativeriskmanagement,insurance,andfinance. Comparedto existingmonographsoncopulas,the originalityofthisbookis to illustrate how theoretical concepts can be applied in practice with the R package copula. To this end, numerousstand-alone examples are provided. This is both of pedagogical and of practical interest as the R source code and reproduced outputssuchasfiguresnotonlyallowonetobetterunderstandthesubtletiesofthe theoreticalnotionsbutalso enableonetosolvereal-worldproblemsinthevarious fieldsofinterest. Thebooktargets(possiblyfuture)statisticiansand(financial,hydrological,and other) engineers alike who would like to understand how theoretical notions and practical computations around copula modeling can be applied in R without an overwhelmingamountofmathematics.Readersarenonethelessexpectedtohavea basicknowledgeof(multivariate)probabilityandstatistics,inparticularofrandom vectors,simulationalgorithms,estimationmethods,andstatisticaltests. Althoughthebookaddressesmostofthepracticalissuesarisingwhenmodeling multivariatedatawithcopulas,itonlycoversamodestpartofthefield.Inparticular, important aspects such as dynamic copula models, vine copulas, and copula modelingfor censoredor discontinuousdata are notdealtwith. Thisis partly due toaselectionbias:ConceptsthatarenotimplementedintheRpackagecopulaat the time ofwritingare notpresentedin the book.Manyof these morespecialized notionsare,however,availablein other R packages.For an up-to-datedescription of the functionalities of other packages dealing with copulas, see, for example, the CRAN View “Distributions” available at https://cran.r-project.org/web/views/ Distributions.html. vii viii Preface AstheRstatisticalenvironment,andmostfreesoftware,theRpackagecopula comeswithnowarranty.Itisdistributedwiththehopethatitcanbeusefultoothers. Waterloo,ON,Canada MariusHofert Pau,France IvanKojadinovic Zürich,Switzerland MartinMächler Storrs,CT,USA JunYan November2017 Reference RCoreTeam.(2017).R:ALanguageandEnvironmentforStatisticalComputing.RFoundation forStatisticalComputing,Vienna,Austria.https://www.R-project.org. Contents 1 Introduction .................................................................. 1 1.1 AMotivatingExample.................................................. 1 1.2 ProbabilityandQuantileTransformations............................. 3 1.3 Copulas.................................................................. 5 1.4 StructureandPhilosophyoftheBook ................................. 6 1.5 AdditionalReading ..................................................... 7 References..................................................................... 8 2 Copulas........................................................................ 9 2.1 DefinitionandCharacterization........................................ 9 2.2 TheFréchet–HoeffdingBounds........................................ 18 2.3 Sklar’sTheorem......................................................... 22 2.4 TheInvariancePrinciple................................................ 35 2.5 SurvivalCopulasandCopulaSymmetries............................. 40 2.6 MeasuresofAssociation................................................ 45 2.6.1 FallaciesRelatedtotheCorrelationCoefficient............... 46 2.6.2 RankCorrelationMeasures .................................... 51 2.6.3 TailDependenceCoefficients.................................. 58 2.7 RosenblattTransformandConditionalSampling ..................... 68 References..................................................................... 77 3 ClassesandFamilies......................................................... 81 3.1 EllipticalDistributionsandCopulas ................................... 81 3.1.1 EllipticalDistributions.......................................... 82 3.1.2 EllipticalCopulas............................................... 85 3.2 ArchimedeanCopulas .................................................. 97 3.3 Extreme-ValueCopulas................................................. 112 3.4 SelectedCopulaTransformationsandConstructions ................. 117 3.4.1 RotatedCopulas ................................................ 117 3.4.2 Khoudraji’sDevice ............................................. 120 3.4.3 MixturesofCopulas............................................ 127 References..................................................................... 130 ix x Contents 4 Estimation .................................................................... 133 4.1 EstimationUnderaParametricAssumptionontheCopula........... 133 4.1.1 ParametricallyEstimatedMargins............................. 134 4.1.2 NonparametricallyEstimatedMargins ........................ 139 4.1.3 EstimatorsofEllipticalCopulaParameters ................... 148 4.1.4 OtherSemi-parametricEstimators............................. 152 4.1.5 EstimationofCopulaModelswithPartlyFixed Parameters....................................................... 153 4.2 NonparametricEstimationoftheCopula.............................. 157 4.2.1 TheEmpiricalCopula .......................................... 158 4.2.2 UnderExtreme-ValueDependence............................ 161 References..................................................................... 163 5 GraphicalDiagnostics,Tests,andModelSelection ...................... 167 5.1 BasicGraphicalDiagnostics............................................ 168 5.2 HypothesisTests ........................................................ 173 5.2.1 TestsofIndependence.......................................... 173 5.2.2 TestsofExchangeability ....................................... 176 5.2.3 ATestofRadialSymmetry .................................... 178 5.2.4 TestsofExtreme-ValueDependence .......................... 179 5.2.5 Goodness-of-FitTests .......................................... 181 5.2.6 AMixtureofGraphicalandFormalGoodness-of-Fit Tests............................................................. 188 5.3 ModelSelection......................................................... 191 References..................................................................... 195 6 Ties,TimeSeries,andRegression.......................................... 197 6.1 Ties ...................................................................... 198 6.2 SelectedCopulaTestsandModelsforTimeSeries ................... 216 6.2.1 TestsofStationarity............................................. 216 6.2.2 TestsofSerialIndependence................................... 226 6.2.3 Models for Multivariate Time Series Based on ConditionalCopulas............................................ 230 6.3 Regression............................................................... 238 References..................................................................... 252 A RandPackageVersions..................................................... 255 Index............................................................................... 259

Description:
This book introduces the main theoretical findings related to copulas and shows how statistical modeling of multivariate continuous distributions using copulas can be carried out in the R statistical environment with the package copula (among others). Copulas are multivariate distribution functions
See more

The list of books you might like

Most books are stored in the elastic cloud where traffic is expensive. For this reason, we have a limit on daily download.