Model selection: An integral part of inference

Biometrics

Volumn 53, Issue 2, 1997, Pages 603-618

  Buckland, S T ^a   Burnham, K P ^b   Augustin, N H ^a  

^a UNIVERSITY OF ST ANDREWS   (United Kingdom)

^b Colorado Coop Fish Wildl Res U ^*  (United States)

Author keywords

AIC; BIC; Information criteria; Model selection uncertainty; Simulated inference

Indexed keywords

AIC; BIC; INFORMATION CRITERION; INTEGRAL PART; MODEL CHOICE; MODEL SELECTION; MODEL SELECTION UNCERTAINTY; SIMULATED INFERENCE; STATISTICAL INFERENCE; UNCERTAINTY;

PHILOSOPHICAL ASPECTS;

ARTICLE; COVARIANCE; DATA ANALYSIS; STATISTICAL ANALYSIS; STATISTICAL MODEL;

AVES;

MODEL SELECTION; MODELLING; STATISTICAL INFERENCE; UNCERTAINTY;

EID: 0030613470     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.2307/2533961     Document Type: Article

References (36)

1. Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle. Second International Symposium on Information Theory, B. N. Petrov and F. Csaki (eds), 267-281. Budapest: Akademiai Kiado.
2. Akaike, H. (1978). A Bayesian analysis of the minimum AIC procedure. Annals of the Institute of Statistical Mathematics 30, 9-14.
3. Berger, J. O. and Pericchi, L. R. (1996). The intrinsic Bayes factor for model selection and prediction. Journal of the American Statistical Association 91, 109-122.
4. Berk, R. H. (1966). The limiting behavior of posterior distributions when the model is incorrect. Annals of Mathematical Statistics 37, 51-58.
5. Bozdogan, H. (1987). Model selection and Akaike's information criterion (AIC): The general theory and its analytical extensions. Psychometrika 52, 345-370.
6. Bravington, M. (1993). The effects of acidification on the population dynamics of brown trout in Norway. Ph.D. thesis, Imperial College, London.
7. Buckland, S. T. (1982). A note on the Fourier series model for analysing line transect data. Biometrics 38, 469-477.
8. Buckland, S. T. (1984). Monte Carlo confidence intervals. Biometrics 40, 811-817.
9. Buckland, S. T. (1992). Fitting density functions using polynomials. Applied Statistics 41, 63-76.
10. Buckland, S. T., Anderson, D. R., Burnham, K. P., and Laake, J. L. (1993). Distance Sampling: Estimating Abundance of Biological Populations. London: Chapman and Hall.
11. Burnham, K. P. and Anderson, D. R. (1992). Data-based selection of an appropriate biological model: The key to modern data analysis. In Wildlife 2001: Populations, D. R. McCullough and R. H. Barrett (eds), 16-30. London: Elsevier Science Publishers.
12. Burnham, K. P., Anderson, D. R., and White, G. C. (1994). Evaluation of the Kullback-Leibler discrepancy for model selection in open population capture-recapture models. Biometrical Journal 36, 299-315.
13. Chatfield, C. (1995). Model uncertainty, data mining and statistical inference. Journal of the Royal Statistical Society, Series A 158, 419-466.
14. Draper, D. (1995). Assessment and propagation of model uncertainty (with discussion). Journal of the Royal Statistical Society, Series B 57, 45-97.
15. Efron, B. (1979). Bootstrap methods: Another look at the jackknife. Annals of Statistics 7, 1-26b.
16. Efron, B. and Tibshirani, R. J. (1993). An Introduction to the Bootstrap. New York: Chapman and Hall.
17. Gates, C. E. (1979). Line transect and related issues. In Sampling Biological Populations, R. M. Cormack, G. P. Patil, and D. S. Robson (eds), 71-154. Fairland, Maryland: International Cooperative Publishing House.
18. Hjorth, J. S. U. (1994). Computer Intensive Statistical Methods: Validation, Model Selection and Bootstrap. London: Chapman and Hall.
19. Hook, E. B. and Regal, R. R. (1995). Capture-recapture methods in epidemiology - Methods and limitations. Epidemiologic Reviews 17, 243-264.
20. Hurvich, C. M. and Tsai, C. (1989). Regression and time series model selection in small samples. Biometrika 76, 297-307.
21. Hurvich, C. M. and Tsai, C. (1995). Model selection for extended quasi-likelihood models in small samples. Biometrics 51, 1077-1084.
22. Kass, R. E. and Raftery, A. E. (1995). Bayes factors. Journal of the American Statistical Association 90, 773-795.
23. Kishino, H. Kato, H., Kasamatsu, F., and Fujise, Y. (1991). Detection of heterogeneity and estimation of population characteristics from the field survey data: 1987/88 Japanese feasibility study of the Southern Hemisphere minke whales. Annals of the Institute of Statistical Mathematics 43, 435-453.
24. Laake, J. L., Buckland, S. T., Anderson, D. R., and Burnham, K. P. (1993). DISTANCE User's Guide Version 2.0. Fort Collins: Colorado Cooperative Fish and Wildlife Research Unit.
25. Madigan, D. M. and York, J. C. (1995). Bayesian graphical models for discrete data. International Statistical Review 63, 215-232.
26. Madigan, D. M., Raftery, A. E., York, J. C., Bradshaw, J. M., and Almond, R. G. (1994). Strategies for graphical model selection. In Selecting Models from Data: AI and Statistics IV, P. Cheeseman and R. W. Oldford (eds), Lecture Notes in Statistics 89, 91-100. New York: Springer-Verlag.
27. Norris, J. L., III and Pollock, K. H. (1996). Including model uncertainty in estimating variances in multiple capture studies. Environmental and Ecological Statistics, 3, 235-244.
28. Raftery, A. E. (1996). Approximate Bayes factors and accounting for model uncertainty in generalized linear models. Biometrika 83, 251-266.
29. Raftery, A. E., Madigan, D. M., and Hoeting, J. (1993). Model selection and accounting for model uncertainty in linear regression models. Technical Report 262, Department of Statistics, University of Washington, Seattle.
30. Rissanan, J. (1989). Stochastic Complexity in Statistical Inquiry, Series in Computer Science, Volume 15. London: World Scientific.
31. Sakamoto, Y., Ishiguro, M., and Kitagawa, G. (1986). Akaike Information Criterion Statistics. Tokyo: KTK Scientific Publishers.
32. Sauerbrei, W. and Schumacher, M. (1992). A bootstrap resampling procedure for model building: Application to the Cox regression model. Statistics in Medicine 11, 2093-2109.
33. Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics 6, 461-464.
34. Sclove, S. L. (1987). Application of model selection criteria to some problems in multivariate analysis. Psychometrika 52, 333-343.
35. Shibata, R. (1989). Statistical aspects of model selection. In From Data to Model, J. C. Willems (ed), 215-240. London: Springer-Verlag.
36. Silverman, B. W. (1982). Algorithm AS 176: Kernel density estimation using the fast Fourier transform. Applied Statistics 31, 93-99.