Simplicity, Inference and Modelling Keeping it Sophisticatedly Simple [Paperback]

An inter-disciplinary perspective on the role of simplicity in modelling and inference, first published in 2002.The idea that simplicity matters in science is as old as science itself, with the much cited example of Ockham's Razor, 'entia non sunt multiplicanda praeter necessitatem': entities are not to be multiplied beyond necessity. Using a multidisciplinary perspective this monograph asks six questions: What is meant by simplicity?, How is simplicity measured? Is there an optimum trade-off between simplicity and goodness-of-fit? What is is the relation between simplicity and empirical modelling? What is the relation between simplicity and prediction? What is the connection between simplicity and convenience?The idea that simplicity matters in science is as old as science itself, with the much cited example of Ockham's Razor, 'entia non sunt multiplicanda praeter necessitatem': entities are not to be multiplied beyond necessity. Using a multidisciplinary perspective this monograph asks six questions: What is meant by simplicity?, How is simplicity measured? Is there an optimum trade-off between simplicity and goodness-of-fit? What is is the relation between simplicity and empirical modelling? What is the relation between simplicity and prediction? What is the connection between simplicity and convenience?The idea that simplicity matters in science is as old as science itself, with the much cited example of Ockham's Razor. A problem with Ockham's Razor is that nearly everybody seems to accept it, but few are able to define its exact meaning and to make it operational in a non-arbitrary way. Using a multidisciplinary perspective including philosophers, mathematicians, econometricians and economists, this monograph examines simplicity by asking six questions: What is meant by simplicity? How is simplicity measured? Is there an optimum trade-off between simplicity and goodness-of-fit? What is the relation between simplicity and empirical modelling? What is the relatiolƒ|