Copula Modeling explores the copula approach for econometrics modeling of joint parametric distributions. Copula Modeling demonstrates that practical implementation and estimation is relatively straightforward despite the complexity of its theoretical foundations. An attractive feature of parametrically specific copulas is that estimation and inference are based on standard maximum likelihood procedures. Thus, copulas can be estimated using desktop econometric software. This offers a substantial advantage of copulas over recently proposed simulation-based approaches to joint modeling. Copulas are useful in a variety of modeling situations including financial markets, actuarial science, and microeconometrics modeling. Copula Modeling provides practitioners and scholars with a useful guide to copula modeling with a focus on estimation and misspecification. The authors cover important theoretical foundations. Throughout, the authors use Monte Carlo experiments and simulations to demonstrate copula properties
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Copula Modeling explores the copula approach for econometrics modeling of joint parametric distributions. Copula Modeling demonstrates that practical implementation and estimation is relatively straightforward despite the complexity of its theoretical foundations. An attractive feature of parametrically specific copulas is that estimation and inference are based on standard maximum likelihood procedures. Thus, copulas can be estimated using desktop econometric software. This offers a substantial advantage of copulas over recently proposed simulation-based approaches to joint modeling. Copulas are useful in a variety of modeling situations including financial markets, actuarial science, and microeconometrics modeling. Copula Modeling provides practitioners and scholars with a useful guide to copula modeling with a focus on estimation and misspecification. The authors cover important theoretical foundations. Throughout, the authors use Monte Carlo experiments and simulations to demonstrate copula properties
Pravin K. Trivedi is Distinguished Professor and J. H. Rudy Professor of Economics at Indiana University, Bloomington. His research and teaching interests are in microeconometrics and health economics. He served as co-editor of the Econometrics Journal from 2000 to 2007 and has been on the board of Journal of Applied Econometrics since 1988. He is coauthor (with A. Colin Cameron) of the first edition of Regression Analysis of Count Data (Cambridge, 1998) and of Microeconometrics: Methods and Applications (Cambridge, 2005).
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
EUR 23,04 für den Versand von Vereinigtes Königreich nach USA
Versandziele, Kosten & DauerEUR 5,93 für den Versand innerhalb von/der USA
Versandziele, Kosten & DauerAnbieter: Hay-on-Wye Booksellers, Hay-on-Wye, HEREF, Vereinigtes Königreich
Zustand: Very Good. UNUSED - Some outer edges have minor scuffs. Cover has light scratches. Book content is in new unread condition. Bestandsnummer des Verkäufers 104021-4
Anzahl: 1 verfügbar
Anbieter: BennettBooksLtd, North Las Vegas, NV, USA
paperback. Zustand: New. In shrink wrap. Looks like an interesting title! Bestandsnummer des Verkäufers Q-1601980205
Anzahl: 1 verfügbar
Anbieter: Books Puddle, New York, NY, USA
Zustand: New. pp. 128. Bestandsnummer des Verkäufers 263590295
Anzahl: 4 verfügbar
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
Zustand: New. Print on Demand pp. 128 Illus. Bestandsnummer des Verkäufers 4290376
Anzahl: 4 verfügbar
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. PRINT ON DEMAND pp. 128. Bestandsnummer des Verkäufers 183590301
Anzahl: 4 verfügbar