An ensemble is the representation of the rainfall field and its uncertainty through a collection of possible alternative rainfall fields, produced according to the observed errors, their spatial characteristics, and their probability distribution.
The method has recently been applied to clustering of a whole song of the GRW [27], where in this work, a collection of possible similarity measures is presented and their respective performances are evaluated and compared.
Theoretically, in a given environment, the mapping between any particular genotype and a set of phenotypes is determined by a probability function, which represents a collection of possible phenotypes around the most-likely phenotype for any given genotype [22].
The Bayesian information criterion selects a model from a collection of possible nonnested models by maximizing the likelihood but with a penalty for higher dimensional models.
This is important, as the prior information typically is a collection of possible regulatory interactions, of which only a subset might be relevant in a given dataset.
While BEST is only one of a collection of possible methods for estimating species trees using multilocus data, we expect that other methods will perform similarly.
