Bayesian model-based cluster analysis for predicting macrofaunal communities

Ecological Modelling

Volumn 160, Issue 3, 2003, Pages 235-248

  Ter Braak, Cajo J F ^a   Hoijtink, Herbert ^b   Akkermans, Wies ^a   Verdonschot, Piet F M ^a  

^a WAGENINGEN UNIVERSITY   (Netherlands)

^b UTRECHT UNIVERSITY   (Netherlands)

Author keywords

Cluster analysis; Community composition; Gibbs sampling; Latent class analysis; Macrofauna; Species environment relationships

Indexed keywords

AQUATIC ECOSYSTEM; BAYESIAN ANALYSIS; CLUSTER ANALYSIS; COMMUNITY COMPOSITION; ECOLOGICAL MODELING; ENVIRONMENTAL FACTOR; FAUNA; PREDICTION;

EID: 0037442814     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0304-3800(02)00256-9     Document Type: Conference Paper

References (33)

1. Banfield, J.D., Raftery, A.E., 1993. Model-based Gaussian and non-Gaussian clustering. Biometrics 49, 803-821.
2. Bensmail, H., Celeux, G., Raftery, A.E., Robert, C.P., 1997. Inference in model-based cluster analysis. Statist. Comput. 7, 1-10.
3. Bezdek, J.C., 1974. Numerical taxonomy with fuzzy sets. J. Math. Biol. 1, 57-71.
4. Braukmann, U., 1984. Biologischer Beitrag zu einer allgemeiner regionalen Bachtypologie. Thesis, Justus Liebig Universität, 1-474, Giessen.
5. Celeux, G., Govaert, G., 1995. Gaussian parsimonious clustering models. Pattern Recog. 28, 781-793.
6. Dayton, C.M., Macready, G.B., 1988. Concomintant-variable latent-class models. J. Am. Statist. Ass. 83, 173-178.
7. Efron, B., 1975. The efficiency of logistic regression compared to normal discriminant analysis. J. Am. Statist. Ass. 70, 892-898.
8. Gelman, A., Carlin, J.B., Stern, H.S., Rubin, D.B., 1995. Bayesian Data Analysis. Chapman and Hall, London, p. 526.
9. Hastie, T., Tibshirani, R., 1990. Generalized Additive Models. Chapman and Hall, London, p. 335.
10. Hathaway, R.J., 1986. Another interpretation of the EM algorithm for mixture distributions. Statist. Prob. Let. 4, 53-56.
11. Heinen, T., 1996. Latent Class and Discrete Latent Trait Models. Similarities and Differences. Sage, London, p. 220.
12. Hill, M.O., 1979. TWINSPAN-a FORTRAN Program for detrended correspondence analysis and reciprocal averaging. Cornell University, Ithaca.
13. Hobert, J.P., Casella, G., 1996. The effect of improper priors on Gibbs sampling in hierarchical linear mixed models. J. Am. Statist. Ass. 91, 1461-1473.
14. Hoijtink, H., 1998. Constrained latent class analysis using the Gibbs sampler and posterior predictive P-values: applications to educational testing. Stat. Sinica 8, 691-711.
15. Johnson, R.K., Wiederholm, T., 1989. Classification and ordination of profundal macro-invertebrate communities in nutrient poor, oligo-mesohumic lakes in relation to environmental data. Freshwat. Biol. 21, 375-386.
16. Kansanen, P.K., Aho, J., Paasivirta, L., 1984. Testing the benthic lake type concept based on chironomid associations in some Finnish lakes using multivariate statistical methods. Ann. Zool. Fenn. 21, 55-76.
17. Kass, R.E., Raftery, A.E., 1995. Bayes factors. J. Am. Statist. Ass. 90, 773-795.
18. McLachlan, G., Peel, D., 2000. Finite Mixture Models. Wiley, New York, p. 419.
19. Moss, D., Wright, J.F., Furse, M.T., Clarke, R.T., 1999. A comparison of alternative techniques for prediction of the fauna of running-water sites in Great Britian. Freshwater Biology 41, 167-181.
20. Newton, M.A., Raftery, A.E., 1994. Approximate Bayesian inference by the weighted likelihood bootstrap (with discussion). J. R. Statist. Soc. Ser. B 56, 3-48.
21. Oksanen, J., Minchin, P.R., 1997. Instability of ordination results under changes in input data order: explanations and remedies. J. Veg. Sci. 8, 447-454.
22. Preston, F.W., 1962. The canonical distribution of commonness and rarity. Ecology 43, 185-215.
23. Richardson, S., Green, P.J., 1997. On Bayesian analysis of mixtures with an unknown number of components (with discussion). J. Roy. Statist. Soc. Ser. B59, 731-792.
24. Stephens, M., 2000. Bayesian analysis of mixture models with an unknown number of components - An alternative to reversible jump methods. Ann. Statist. 28, 40-74.
25. Tausch, R.J., Charlet, D.A., Weixelman, D.A., Zamudio, D.C., 1995. Patterns of ordination and classification instability resulting from changes in input order. J. Veg. Sci. 6, 897-902.
26. Ter Braak, C.J.F., 1995. Ordination. In: Jongman, R.H.G., ter Braak, C.J.F., van Tongeren, O.F.R. (Eds.), Data Analysis in Community and Landscape Ecology. Cambridge University Press, Cambridge, pp. 91-173.
27. Van Groenewoud, H., 1992. The robustness of correspondence, detrended correspondence, and TWINSPAN analysis. J. Veg. Sci. 3, 239-246.
28. Van Tongeren, O.F.R., 1995. Cluster analysis. In: Jongman, R.H.G., ter Braak, C.J.F., van Tongeren, O.F.R. (Eds.), Data analysis in Community and Landscape Ecology. Cambridge University Press, Cambridge, pp. 174-212.
29. Verdonschot, P.F.M., 1990. Ecological characterization of surface waters in the province of Overijssel (The Netherlands). Ph.D. thesis, Wageningen, 255 pp.
30. Vlassis, N., Likas, A, 2002. A greedy EM algorithm for Gaussian mixture learning. Neural Processing Letters 15, 77-87.
31. Vermunt, J.K., Magidson, J., 2000. Latent Gold User's Guide. Statistical Innovations, Belmont, p. 186.
32. Wright, J.F., Moss, D., Armitage, P.D., Furse, M.T., 1984. A preliminary classification of running water sites in Great Britain based on macro-invertebrate species and the prediction of community type using environmental data. Freshwat. Biol. 14, 221-256.
33. Zeger, S.L., Karim, M.R., 1991. Generalized linear models with random effects: a Gibbs sampling approach. J. Am. Statist. Ass. 86, 79-86.