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We consider the tting of normal mixture models to multivariate data, using maximum likelihood via the EM algorithm. This approach requires the initial speciication of an initial estimate of the vector of unknown parameters, or equivalently, of an initial clas-siication of the data with respect to the components of the mixture model under t. We describe an(More)
In this paper use consider the problem of providing standard errors of the component means in normal mixture models tted to univariate or multi-variate data by maximumlikelihood via the EM algorithm. Two methods of estimation of the standard errors are considered: the standard information-based method and the computationally-intensive bootstrap method. They(More)
Vaccine research is a combinatorial science requiring computational analysis of vaccine components, formulations and optimization. We have developed a framework that combines computational tools for the study of immune function and vaccine development. This framework, named ImmunoGrid combines conceptual models of the immune system, models of antigen(More)
We consider the tting of normal mixture models to multivariate data, using maximum likelihood via the EM algorithm. This approach requires the initial speciication of an initial estimate of the vector of unknown parameters, or equivalently, of an initial clas-siication of the data with respect to the components of the mixture model under t. We describe an(More)
Izenman and Sommer (1988) used a nonparametric kernel density estimation technique to t a seven component model to the paper thickness of the 1872 Hidalgo Stamp issue of Mexico. They observed an apparent connict when tting a normal mixture model with three components with unequal variances. This connict is examined further by investigating the most(More)
Clinical success of fixed prosthodontic procedures is dependent in part upon the dimensional accuracy of elastomeric impression materials and impression procedures. Three elastomeric impression materials were used in custom and stock trays to determine the accuracy of impressions taken from an experimental stainless steel model representing premolar and(More)
We consider the classification of microarray gene-expression data. First, attention is given to the supervised case, where the tissue samples are classified with respect to a number of predefined classes and the intent is to assign a new unclassified tissue to one of these classes. The problems of forming a classifier and estimating its error rate are(More)
The Dental Aesthetic (DAI) was devised as a measure of dental appearance and based on lay opinions as opposed to professional assessments of need. The DAI is calculated from the weighted scores of ten occlusal variables. These same variables have been used in other malocclusion indices intended to measure morphological deviations from normality. It is,(More)
A genomic selection index (GSI) is a linear combination of genomic estimated breeding values that uses genomic markers to predict the net genetic merit and select parents from a nonphenotyped testing population. Some authors have proposed a GSI; however, they have not used simulated or real data to validate the GSI theory and have not explained how to(More)