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Full-Text Articles in Statistical Models
Mixture Model Cluster Analysis Under Different Covariance Structures Using Information Complexity, Bahar Erar
Mixture Model Cluster Analysis Under Different Covariance Structures Using Information Complexity, Bahar Erar
Masters Theses
In this thesis, a mixture-model cluster analysis technique under different covariance structures of the component densities is developed and presented, to capture the compactness, orientation, shape, and the volume of component clusters in one expert system to handle Gaussian high dimensional heterogeneous data sets to achieve flexibility in currently practiced cluster analysis techniques. Two approaches to parameter estimation are considered and compared; one using the Expectation-Maximization (EM) algorithm and another following a Bayesian framework using the Gibbs sampler. We develop and score several forms of the ICOMP criterion of Bozdogan (1994, 2004) as our fitness function; to choose the number …
A Study Of Missing Data Imputation And Predictive Modeling Of Strength Properties Of Wood Composites, Yan Zeng
A Study Of Missing Data Imputation And Predictive Modeling Of Strength Properties Of Wood Composites, Yan Zeng
Masters Theses
Problem: Real-time process and destructive test data were collected from a wood composite manufacturer in the U.S. to develop real-time predictive models of two key strength properties (Modulus of Rupture (MOR) and Internal Bound (IB)) of a wood composite manufacturing process. Sensor malfunction and data “send/retrieval” problems lead to null fields in the company’s data warehouse which resulted in information loss. Many manufacturers attempt to build accurate predictive models excluding entire records with null fields or using summary statistics such as mean or median in place of the null field. However, predictive model errors in validation may be higher …