Identification and forecasting in mortality models (Q904608)
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scientific article; zbMATH DE number 6529675
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Identification and forecasting in mortality models |
scientific article; zbMATH DE number 6529675 |
Statements
Identification and forecasting in mortality models (English)
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13 January 2016
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Summary: Mortality models often have inbuilt identification issues challenging the statistician. The statistician can choose to work with well-defined freely varying parameters, derived as maximal invariants in this paper, or with ad hoc identified parameters which at first glance seem more intuitive, but which can introduce a number of unnecessary challenges. In this paper, we describe the methodological advantages from using the maximal invariant parameterisation and we go through the extra methodological challenges a statistician has to deal with when insisting on working with ad hoc identifications. These challenges are broadly similar in frequentist and in Bayesian setups. We also go through a number of examples from the literature where ad hoc identifications have been preferred in the statistical analyses.
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