rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    non sort: A
    title: Multivariate Claim Count Model for Applications in Insurance
  name:
    name part: Selch, Daniela Anna.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Scherer, Matthias.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2018
    edition: 1st ed. 2018.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 158 p. 29 illus. in color. online resource.
  abstract: This monograph presents a time-dynamic model for multivariate claim counts in actuarial applications. Inspired by real-world claim arrivals, the model balances interesting stylized facts (such as dependence across the components, over-dispersion and the clustering of claims) with a high level of mathematical tractability (including estimation, sampling and convergence results for large portfolios) and can thus be applied in various contexts (such as risk management and pricing of (re-)insurance contracts). The authors provide a detailed analysis of the proposed probabilistic model, discussing its relation to the existing literature, its statistical properties, different estimation strategies as well as possible applications and extensions. Actuaries and researchers working in risk management and premium pricing will find this book particularly interesting. Graduate-level probability theory, stochastic analysis and statistics are required.
  table of contents: 1 Motivation and Model -- 2 Properties of the Model -- 3 Estimation of the Parameters -- 4 Applications and Extensions -- 5 Appendix: Technical Background -- References -- Index.
  note: by Daniela Anna Selch, Matthias Scherer.
  subject:
    topic: Probabilities
  subject:
    topic: Actuarial science
  subject:
    topic: Statistics
  subject:
    topic: Economics, Mathematical
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Actuarial Sciences
  subject:
    topic: Statistics for Business, Management, Economics, Finance, Insurance
  subject:
    topic: Statistical Theory and Methods
  subject:
    topic: Quantitative Finance
  classification: QA273.A1-274.9
  classification: QA274-274.9
  classification: 519.2
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Actuarial
  identifier: 9783319928685
  identifier: https://doi.org/10.1007/978-3-319-92868-5
  record info:
    record creation date: 180831
    record change date: 20191220130829.0
    record identifier: 978-3-319-92868-5