Evaluation and Comparison of Computational Models

作者: Jay I. Myung , Yun Tang , Mark A. Pitt

DOI: 10.1016/S0076-6879(08)03811-1

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摘要: Computational models are powerful tools that can enhance the understanding of scientific phenomena. The enterprise modeling is most productive when reasons underlying adequacy a model, and possibly its superiority to other models, understood. This chapter begins with an overview main criteria must be considered in model evaluation selection, particular explaining why generalizability preferred criterion for selection. followed by review measures generalizability. final section demonstrates use five versatile easy-to-use selection methods choosing between two mathematical protein folding.

参考文章(40)
M. Stone, Cross-Validatory Choice and Assessment of Statistical Predictions (With Discussion) Journal of the Royal Statistical Society: Series B (Methodological). ,vol. 38, pp. 102- 102 ,(1976) , 10.1111/J.2517-6161.1976.TB01573.X
M. Stone, An Asymptotic Equivalence of Choice of Model by Cross-Validation and Akaike's Criterion Journal of the Royal Statistical Society: Series B (Methodological). ,vol. 39, pp. 44- 47 ,(1977) , 10.1111/J.2517-6161.1977.TB01603.X
Francis Ysidro Edgeworth, Charles R. McCann, The theory of statistics E. Elgar. ,(1996)
Peter D. Grünwald, In Jae Myung, Mark A. Pitt, Advances in Minimum Description Length: Theory and Applications MIT Press. ,(2005)
Nariaki Sugiura, Further analysts of the data by akaike' s information criterion and the finite corrections Communications in Statistics-theory and Methods. ,vol. 7, pp. 13- 26 ,(1978) , 10.1080/03610927808827599
Norma J. Greenfield, Analysis of Circular Dichroism Data Methods in Enzymology. ,vol. 383, pp. 282- 317 ,(2004) , 10.1016/S0076-6879(04)83012-X
Mark A. Pitt, Jay I. Myung, Nicholas Altieri, Modeling the word recognition data of Vitevitch and Luce (1998): is it ARTful? Psychonomic Bulletin & Review. ,vol. 14, pp. 442- 448 ,(2007) , 10.3758/BF03194086
Mark A. Pitt, Woojae Kim, Daniel J. Navarro, Jay I. Myung, Global model analysis by parameter space partitioning. Psychological Review. ,vol. 113, pp. 57- 83 ,(2006) , 10.1037/0033-295X.113.1.57
Michael W. Browne, Robert Cudeck, Alternative Ways of Assessing Model Fit Sociological Methods & Research. ,vol. 21, pp. 230- 258 ,(1992) , 10.1177/0049124192021002005
Peter Müller, Bruno Sansó, Maria De Iorio, Optimal Bayesian Design by Inhomogeneous Markov Chain Simulation Journal of the American Statistical Association. ,vol. 99, pp. 788- 798 ,(2004) , 10.1198/016214504000001123