000			01677nam a2200253Ia 4500
001			40947
003			IN-BdCUP
005			20230421155107.0
008			230413s2023 000 0 eng
020			_a9781466583221
040			_beng _cIN-BdCUP
041			_aeng
082			_a519.535 _bJOE
100			_aJoe, Harry
245		0	_aDependence Modeling with Copulas / _cJoe, Harry
260			_aLondon : _bCRC Press, _c2014.
300			_a480 p. ; _c25 cm.
520			_aDependence Modeling with Copulas covers the substantial advances that have taken place in the field during the last 15 years, including vine copula modeling of high-dimensional data. Vine copula models are constructed from a sequence of bivariate copulas. The book develops generalizations of vine copula models, including common and structured factor models that extend from the Gaussian assumption to copulas. It also discusses other multivariate constructions and parametric copula families that have different tail properties and presents extensive material on dependence and tail properties to assist in copula model selection. The author shows how numerical methods and algorithms for inference and simulation are important in high-dimensional copula applications. He presents the algorithms as pseudocode, illustrating their implementation for high-dimensional copula models. He also incorporates results to determine dependence and tail properties of multivariate distributions for future constructions of copula models.
650			_aStatistics
650			_aProbabilities
650			_aDependence Modeling with Copulas
650			_aCopulas (Mathematical statistics)
942			_2ddc _cBK
999			_c30505 _d30505