Hostname: page-component-848d4c4894-4hhp2 Total loading time: 0 Render date: 2024-05-01T21:15:44.044Z Has data issue: false hasContentIssue false
  • English
  • Français

MIXING IT UP: NEW METHODS FOR FINITE MIXTURE MODELLING OF MULTI-SPECIES DATA IN ECOLOGY

Part of: Applications Multivariate analysis Parametric inference

Published online by Cambridge University Press:  12 November 2015

FRANCIS K. C. HUI
FRANCIS K. C. HUI*
Affiliation:
School of Mathematics and Statistics, Faculty of Science, CSIRO Digital Productivity Flagship, University of New South Wales, Sydney, NSW 2052, Australia email fhui28@gmail.com
Rights & Permissions [Opens in a new window]

Abstract

An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'

Keywords

statisticsparametric inferencemultivariate analysis

MSC classification

Primary: 62P12: Applications to environmental and related topics
Secondary: 62F07: Ranking and selection 62H86: Multivariate analysis and fuzziness
Type
Abstracts of Australasian PhD Theses
Information
Bulletin of the Australian Mathematical Society , Volume 93 , Issue 1 , February 2016 , pp. 167 - 168
Copyright
© 2015 Australian Mathematical Publishing Association Inc. 

References

Hui, F. K. C., Taskinen, S., Pledger, S., Foster, S. D. and Warton, D. I., ‘Model-based approaches to unconstrained ordination’, Methods Ecol. Evol. 6 (2015), 399–411.CrossRefGoogle Scholar
Hui, F. K. C., Warton, D. I. and Foster, S. D., ‘Tuning parameter selection for the adaptive lasso using ERIC’, J. Amer. Statist. Assoc. 110 (2015), 262–269.CrossRefGoogle Scholar
Hui, F. K. C., Warton, D. I. and Foster, S. D., ‘Order selection in finite mixture models: complete or observed likelihood information criteria?’, Biometrika (2015), doi:10.1093/biomet/asv027.CrossRefGoogle Scholar
Hui, F. K. C., Warton, D. I. and Foster, S. D., ‘Multi-species distribution modeling using penalized mixture of regressions’, Ann. Appl. Stat. 9(2) (2015), 866–882.CrossRefGoogle Scholar
Hui, F. K. C., Warton, D. I., Foster, S. D. and Dunstan, P. K., ‘To mix or not to mix: comparing the predictive performance of mixture models versus separate species distribution models’, Ecology 94 (2013), 1913–1919.CrossRefGoogle ScholarPubMed