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Modeling loss data using mixtures of distributions
9 references·8 citing·33 second hop
Modeling loss data using mixtures of distributions (2016)Modeling loss data using mixtures of dist…Modeling loss data using composite models (2014)Modeling loss data using comp…New composite models for the Danish fire insurance data (2012)New composite models for the …Modeling and Evaluating Insurance Losses Via Mixtures of Erlang Distributions (2010)Modeling and Evaluating Insur…On composite lognormal-Pareto models (2007)On composite lognormal-Pareto…Modeling actuarial data with a composite lognormal-Pareto model (2005)Modeling actuarial data with …Loss Models: From Data to Decisions (1999)Loss Models: From Data to Dec…Estimating the Tails of Loss Severity Distributions Using Extreme Value Theory (1997)Estimating the Tails of Loss …Discussion of the Danish Data on Large Fire Insurance Losses (1997)Discussion of the Danish Data…Concomitant-Variable Latent-Class Models (1988)Concomitant-Variable Latent-C…Recent Challenges in Actuarial Science (2021)Recent Challenges in Actuaria…A class of claim distributions: Properties, characterizations and applications to insurance claim data (2020)A class of claim distribution…Extending composite loss models using a general framework of advanced computational tools (2019)Extending composite loss mode…A class of mixture of experts models for general insurance: Theoretical developments (2019)A class of mixture of experts…On generalized log-Moyal distribution: A new heavy tailed size distribution (2018)On generalized log-Moyal dist…Modelling censored losses using splicing: A global fit strategy with mixed Erlang and extreme value distributions (2017)Modelling censored losses usi…Data breaches: Goodness of fit, pricing, and risk measurement (2017)Data breaches: Goodness of fi…Non-Life Insurance: Mathematics & Statistics (2013)Non-Life Insurance: Mathemati…Understanding Relationships Using Copulas (1998)Heavy-Tail Phenomena: Probabilistic and Statistical Modeling (2006)Compound unimodal distributions for insurance losses (2017)Modelling of extremal events in insurance and finance (1994)Fitting insurance claims to skewed distributions: Are the skew-normal and skew-student good models? (2012)Loss Models: From Data to Decisions (2006)Modeling with Weibull-Pareto Models (2012)Simulation Modeling and Analysis. (1983)Empirical Model Building and Response Surfaces (1988)A new class of models for heavy tailed distributions in finance and insurance risk (2012)Multivariate distribution defined with Farlie–Gumbel–Morgenstern copula and mixed Erlang marginals: Aggregation and capital allocation (2013)Extreme Values, Regular Variation and Point Processes (1987)Modelling Extremal Events (1997)Composite Lognormal–Pareto model with random threshold (2010)Latent Structure Analysis. (1969)Exploratory Latent Structure Analysis Using Both Identifiable and Unidentifiable Models (1974)Latent Variable Regression for Multiple Discrete Outcomes (1997)Second-generation structural equation modeling with a combination of categorical and continuous latent variables: New opportunities for latent class–latent growth modeling. (2001)7. Multilevel Latent Class Models (2003)Latent Structure Analysis (2014)Models for Exceedances Over High Thresholds (1990)Heavy tail modeling and teletraffic data: special invited paper (1997)Extreme Value Theory as a Risk Management Tool (1999)Extreme value theory and Value-at-Risk: Relative performance in emerging markets (2004)Modern Actuarial Risk Theory (2008)National Conference of State Legislatures (2011)Insurability of Cyber Risk: An Empirical Analysis (2014)Copula approaches for modeling cross-sectional dependence of data breach losses (2018)Multivariate Hawkes process for cyber insurance (2020)Cyber claim analysis using Generalized Pareto regression trees with applications to insurance (2021)A Class of Distortion Operators for Pricing Financial and Insurance Risks (2000)Actuarial Theory for Dependent Risks: Measures, Orders and Models (2005)Modeling claims data with composite Stoppa models (2015)
this work references cited by second hop

References

  • 1999Loss Models: From Data to Decisions1,232 cited
  • 1997Estimating the Tails of Loss Severity Distributions Using Extreme Value Theory543 cited
  • 1988Concomitant-Variable Latent-Class Models496 cited
  • 2005Modeling actuarial data with a composite lognormal-Pareto model219 cited
  • 2007On composite lognormal-Pareto models177 cited
  • 1997Discussion of the Danish Data on Large Fire Insurance Losses147 cited
  • 2010Modeling and Evaluating Insurance Losses Via Mixtures of Erlang Distributions129 cited
  • 2014Modeling loss data using composite models119 cited
  • 2012New composite models for the Danish fire insurance data102 cited

Cited by

  • 2017Data breaches: Goodness of fit, pricing, and risk measurement97 cited
  • 2018On generalized log-Moyal distribution: A new heavy tailed size distribution74 cited
  • 2017Modelling censored losses using splicing: A global fit strategy with mixed Erlang and extreme value distributions62 cited
  • 2019Extending composite loss models using a general framework of advanced computational tools58 cited
  • 2021Recent Challenges in Actuarial Science41 cited
  • 2020A class of claim distributions: Properties, characterizations and applications to insurance claim data

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38 cited
  • 2013Non-Life Insurance: Mathematics & Statistics36 cited
  • 2019A class of mixture of experts models for general insurance: Theoretical developments30 cited