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- W4312936317 abstract "Abstract This chapter is the core theoretical chapter on predictive modeling, forecast evaluation and model selection. The main problem in actuarial modeling is to forecast and price future claims. For this, we build predictive models, and this chapter deals with assessing and ranking these predictive models. We therefore introduce the mean squared error of prediction (MSEP) and, more generally, the expected generalization loss (GL) to assess predictive models. This chapter is complemented by a more decision-theoretic approach to forecast evaluation, it discusses deviance losses, proper scoring, elicitability, forecast dominance, cross-validation, Akaike’s information criterion (AIC) and we give an introduction to the bootstrap simulation method." @default.
- W4312936317 created "2023-01-05" @default.
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- W4312936317 date "2022-07-05" @default.
- W4312936317 modified "2023-10-01" @default.
- W4312936317 title "Predictive Modeling and Forecast Evaluation" @default.
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- W4312936317 doi "https://doi.org/10.1007/978-3-031-12409-9_4" @default.
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