dc.contributor.author | Velupillai, K. Vela | en |
dc.date.accessioned | 2010-05-10T13:58:13Z | en |
dc.date.available | 2010-05-10T13:58:13Z | en |
dc.date.issued | 2007 | en |
dc.identifier.citation | Velupillai, K. V., (2007) "A Stochastic Complexity Perspective of Induction in Economics and Inference in Dynamics" (Working Paper No. 0127) Department of Economics, National University of Ireland, Galway. | en |
dc.identifier.uri | http://hdl.handle.net/10379/984 | en |
dc.description.abstract | Rissanen's fertile and pioneering minimum description length principle (MDL) has been viewed from the point of view of statistical estimation theory, information theory, as stochastic complexity theory - i.e., a computable approximation of Kolomogorov Complexity - or Solomonoff's recursion theoretic induction principle or as analogous to Kolmogorov's sufficient statistics. All these - and many more - interpretations are valid, interesting and fertile. In this paper I view it from two points of view: those of an algorithmic economist and a dynamical system theorist. From these points of view I suggest, first, a recasting of Jevon's sceptical vision of induction in the light of MDL; and a complexity interpretation of an undecidable question in dynamics. | en |
dc.format | application/pdf | en |
dc.language.iso | en | en |
dc.publisher | National University of Ireland, Galway | en |
dc.relation.ispartofseries | working papers;0127 | en |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Ireland | |
dc.rights.uri | https://creativecommons.org/licenses/by-nc-nd/3.0/ie/ | |
dc.subject | Economics | en |
dc.title | A Stochastic Complexity Perspective of Induction in Economics and Inference in Dynamics | en |
dc.type | Working Paper | en |
dc.description.peer-reviewed | peer-reviewed | en |
nui.item.downloads | 512 | |