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Using Reversible Jump MCMC to Account for Model Uncertainty
Using Reversible Jump MCMC to Account for Model Uncertainty When fitting a model to any data, there is some uncertainty about which model is best. Green [1995] quantifies this uncertainty through ...- Authors: Brian Hartman, Jeff R Hart
- Date: Nov 2008
- Competency: Technical Skills & Analytical Problem Solving>Incorporate risk management
- Topics: Modeling & Statistical Methods>Markov Chain
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Predicting Return to Work with Data Mining
Predicting Return to Work with Data Mining One of the first projects undertaken by Claim Analytics was to create a model to predict return to work for group insurance claimants with long term ...- Authors: Barry D Senensky,
- Date: Jan 2004
- Competency: External Forces & Industry Knowledge>Actuarial methods in business operations; External Forces & Industry Knowledge>External forces and business performance
- Topics: Health & Disability>Chronic health management - Health & Disability; Health & Disability>Disability insurance; Health & Disability>Disability tables; Modeling & Statistical Methods>Dynamic simulation models; Modeling & Statistical Methods>Markov Chain; Modeling & Statistical Methods>Modeling efficiency; Modeling & Statistical Methods>Simulation
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On the Probability of Ruin in a Markov-modulated Risk Model
On the Probability of Ruin in a Markov-modulated Risk Model This paper endeavors to obtain the explicit formulas of the probability of ruin in a Markov-modulated model where claim intensities, ...- Authors: Yi Lu, Shuanming Li
- Date: Jan 2005
- Competency: Technical Skills & Analytical Problem Solving>Process and technique refinement
- Topics: Modeling & Statistical Methods>Markov Chain