Regression Modeling with Actuarial and Financial Applications (International Series on Actuarial Science)

Edward W. Frees

ISBN 10: 0521135966 / ISBN 13: 9780521135962

Edité par Cambridge University Press, 2010

A propos de cet article

1st edition. 584 pages. 4.96x1.89x0.87 inches. In Stock.

N° de réf. du vendeur x-0521135966

Détails bibliographiques

• Titre: Regression Modeling with Actuarial and Financial Applications (International Series on Actuarial Science)
• Éditeur: Cambridge University Press
• Date de parution: 2010
• Langue: anglais
• ISBN à 10 chiffres: 0521135966
• ISBN à 13 chiffres: 9780521135962
• Reliure: Paperback
• État de l'article: Brand New

A propos de ce titre

Synopsis

This text gives budding actuaries and financial analysts a foundation in multiple regression and time series. They will learn about these statistical techniques using data on the demand for insurance, lottery sales, foreign exchange rates, and other applications. Although no specific knowledge of risk management or finance is presumed, the approach introduces applications in which statistical techniques can be used to analyze real data of interest. In addition to the fundamentals, this book describes several advanced statistical topics that are particularly relevant to actuarial and financial practice, including the analysis of longitudinal, two-part (frequency/severity), and fat-tailed data. Datasets with detailed descriptions, sample statistical software scripts in 'R' and 'SAS', and tips on writing a statistical report, including sample projects, can be found on the book's Web site: http://research.bus.wisc.edu/RegActuaries.

À propos de l?auteur

Edward W. (Jed) Frees is a Professor of Business at the University of Wisconsin, Madison and is holder of the Assurant Health Insurance Professorship of Actuarial Science. He is a Fellow of both the Society of Actuaries (SoA) and the American Statistical Association (ASA). Professor Frees is the author of Longitudinal and Panel Data (2004) and has published more than fifty articles in leading refereed academic journals.