Non-Life Insurance Mathematics An Introduction with Stochastic Processes. Authors: Mikosch, Thomas Show next edition Free Preview. Buy this book eBook 67,40 € price for Spain (gross) Buy eBook ISBN 978-3-540-44889-1; Digitally watermarked, DRM-free; Included format: PDF ...
The second edition contains various new chapters that illustrate the use of point process techniques in non-life insurance mathematics. Poisson processes play a central role. Detailed discussions show how Poisson processes can be used to describe complex aspects in an insurance business such as delays in reporting, the settlement of claims and claims …
Thomas Mikosch has been professor at the Laboratory of Actuarial Mathematics of the University of Copenhagen since January 2001. Before this, he held positions in Dresden (Germany), Wellington (New Zealand) and Groningen (Netherlands). His special interests are applied probability theory and stochastic processes. Over the last few years his research has …
The volume offers a mathematical introduction to non-life insurance and, at the same time, to a multitude of applied stochastic processes. It includes detailed discussions of the fundamental models regarding claim sizes, claim arrivals, the total …
Non-Life Insurance Mathematics Thomas Mikosch No preview available - 2014. Non-Life Insurance Mathematics: An Introduction with the Poisson Process Thomas Mikosch No preview available - 2009. Common terms and phrases. assume asymptotic Bayes estimator Borel sets calculate central limit theorem characteristic function claim amount process claim arrival …
This book offers a mathematical introduction to non-life insurance and, at the same time, to a multitude of applied stochastic processes. It gives detailed discussions of the fundamental models for claim sizes, claim arrivals, the total claim amount, and their probabilistic properties. Throughout the book the language of stochastic processes is used for describing the dynamics of an insurance ...
Most of us know how to say nothing, but few of us know when.
‹ | › | |||||
Mo | Tu | We | Th | Fr | St | Su |