Computational Statistics & Data Analysis
Asymptotics for estimation and testing procedures under loss of identifiability
Journal of Multivariate Analysis
Nonparametric fixed-interval smoothing with vector splines
IEEE Transactions on Signal Processing
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A new approach to species distribution modelling based on unsupervised classification via a finite mixture of GAMs incorporating habitat suitability curves is proposed. A tailored EM algorithm is outlined for computing maximum likelihood estimates. Several submodels incorporating various parameter constraints are explored. Simulation studies confirm that under certain constraints, the habitat suitability curves are recovered with good precision. The method is also applied to a set of real data concerning presence/absence of observable small mammal indices collected on the Tibetan plateau. The resulting classification was found to correspond to species level differences in habitat preference described in the previous ecological work.