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(Wiley, 2011-04)
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(Emerald, 2010-01)Ranked preference data arise when a set of judges rank, in order of their preference, a set of objects. Such data arise in preferential voting systems and market research surveys. Covariate data associated with the judges ...
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(Oxford University Press, 2010-11-01)In recent years, work has been carried out on clustering gene expression microarray data. Some approaches are developed from an algorithmic viewpoint whereas others are developed via the application of mixture models. In ...
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(Wiley, 2010-03)A new family of mixture models for the model-based clustering of longitudinal data is introduced. The covariance structures of eight members of this new family of models are given and the associated maximum likelihood ...
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(Springer, 2012-10-15)A cognitively plausible measure of semantic similarity between geographic concepts is valuable across several areas, including geographic information retrieval, data mining, and ontology alignment. Semantic similarity ...
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(R.T. Edwards, 2005)This paper looks at the role of experts from both a United Kingdom and North America perspective. The paper starts by pointing out the important role of expert evidence in assisting the tier of fact. The distinction between ...
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(Blackwell, 2000-04)This study examines the distributional properties of futures prices for contracts traded on LIFFE. A filtering process is employed to remove day of the week and holiday effects, a maturity effect, moving average effects ...
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(Institute of Mathematical Statistics, 2010-03)Food authenticity studies are concerned with determining if food samples have been correctly labelled or not. Discriminant analysis methods are an integral part of the methodology for food authentication. Motivated by food ...
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(Springer-Verlag, 2008-09-05)The integrated management of both spatial and temporal components of information is crucial in order to extract significant knowledge from datasets concerning phenomena of interest to a large variety of applications. ...
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(2013-04)Item response modelling is a well established method for analysing ordinal response data. Ordinal data are typically collected as responses to a number of questions or items. The observed data can be viewed as discrete ...