Model-based clustering consists of fitting a mixture model to data and identifying each cluster with one of its components. Multivariate normal distributions are typically used. The number of clusters is usually determined from the data, often using BIC. In practice, however, individual clusters can be poorly fitted by Gaussian distributions, and in that case model-based clustering tends to rep...

this paper deals with the suitability of agricultural and municipal organic wastes as growing media components for ornamental plants. nine growing media prepared by mixing the main components of peat (p), hazelnut husk (h) and maize straw (m) with the fertilizer sources of municipal solid waste compost (c), bio-solid (b) and poultry manure (pm) were compared against soil-based (c1) and peat-bas...

Wheat (Triticum aestivum L.) variety mixtures represent a relatively unexplored avenue for maintaining yield and improving flour quality. A field experiment was conducted to examine the responses of three spring wheat varieties in pure variety and in variety mixtures under continuous cropping in Northeast China. Three modern spring wheat varieties, along with a three-variety mixture and a t...

Observing natural phenomena at several levels of detail results in multiresolution data. Extending models and algorithms to cope with multiresolution data is a prerequisite for wide-spread exploitation of the data represented in the multiple resolutions. Mixture models are widely used probabilistic models, however, the mixture models in their standard form can be used to analyze the data repres...