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Titlebook: Bayesian Statistics in Actuarial Science; with Emphasis on Cre Stuart A. Klugman Book 1992 Springer Science+Business Media New York 1992 ac

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The Nikkei Stock Average Prediction by SVMIn this Chapter one more restriction to the normal model of Chapter 6 will be imposed: linearity in the parameters. Within this model most all standard situations involving severity, pure premiums, or loss ratios can be handled. The only reasonable case that cannot be handled is the Poisson model for frequency. This will be covered in Chapter 9.
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Lecture Notes in Computer ScienceIn this Chapter a number of data sets will be introduced. Then the credibility models from the previous Chapter will be analyzed.
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Examples,In this Chapter a number of data sets will be introduced. Then the credibility models from the previous Chapter will be analyzed.
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https://doi.org/10.1007/978-94-017-0845-6actuarial science; algorithm; bayesian statistics; calculus; rating; statistical analysis; statistics
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978-90-481-5790-7Springer Science+Business Media New York 1992
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Prediction with Parameter Uncertainty,l form, but unknown parameters. Of interest is the value of a future observation whose distribution also depends on these parameters. Of course, this is the traditional actuarial problem. The observations are the benefits paid in the past to policyholders and we desire to predict the payments that will be made in the future.
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