Model Construction (Parameter Estimation)

Steven Finlay

Chapter 7 in Credit Scoring, Response Modelling and Insurance Rating, 2010, pp 160-196 from Palgrave Macmillan

Abstract: Abstract In this chapter, some of the ways of deriving the parameter coefficients of a model are discussed — a process I shall refer to as model construction, parameter estimation or modelling. Many different methods of model construction exist, and there are many theoretical arguments why one method is better than another, or why such and such a method is/is not appropriate in a given set of circumstances. However, for predictive modelling the method used to derive a model is arguably unimportant, as long as the final model is a good predictor of behaviour and satisfies any business requirements about the properties of the model. To some extent, the ends justify the means. There is no reason why you can’t just make up a model’s parameters based on your expert opinion, and in situations where data is scarce this is exactly what industry experts sometimes do. However, under normal conditions, where a good quality sample of data is available, modelling techniques that apply mechanical procedures (statistical or mathematical processes) nearly always generate models that are superior, in terms of predictive ability, than models created using more judgemental/subjective means.

Keywords: Logistic Regression; Predictor Variable; Hide Layer; Model Construction; Insurance Rate (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:pal:palchp:978-0-230-29898-9_7

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DOI: 10.1057/9780230298989_7

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