 Model Construction (Parameter Estimation)Steven Finlay Chapter 7 in Credit Scoring, Response Modeling, and Insurance Rating, 2012, pp 165-202 from Palgrave Macmillan Abstract: Abstract In this chapter, ways of deriving the parameter coefficients of a model are discussed — a process referred to as model construction, parameter estimation or modeling. Many different methods of model construction exist and there are many 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 modeling the method used to derive a model is arguably unimportant if the final model is a good predictor of behavior and satisfies any business requirements. To a greater or lesser 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 some industry experts will do. However, under normal conditions, where a good quality sample of data is available, modeling techniques that apply mechanical procedures (statistical or mathematical processes) usually generate models that are superior, in terms of predictive ability, to models created using more judgemental/subjective means. Keywords: Logistic Regression; Predictor Variable; Hide Layer; Model Construction; Insurance Rate (search for similar items in EconPapers) There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:pal:palchp:978-1-137-03169-3_7 Ordering information: This item can be ordered from Access Statistics for this chapter More chapters in Palgrave Macmillan Books from Palgrave Macmillan |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.