Global ETD Search
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Showing 1 to 8 of 8 for “"model selection criterion"”.
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High dimensional feature selection under interactive models
… the popularity of high dimensional feature selection. High dimensional feature selection aims to select relevant features from the suspected feature space by removing redundant features. Among high feature selection studies, a large number have considered main effects only, although …
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Stein Estimation and Model Selection
… to use Stein type estimators for statistical model selection purposes. First, a parameter truncation criterion developed in conjunction with the new Stein estimator (Stein, 1981) is used in an orthonormal linear statistical model setting, as a basis for simultaneously selecting the model and …
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l0 Sparse signal processing and model selection with applications
… algorithms. Next, two applications of sparse modeling are considered. In the first application the L0LS-CD algorithm is extended to recover a sparse transfer function in the presence of coloured noise. The second uses gL0LS-CD to recover the topology of a sparsely connected network of dynamic …
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Leveraging Statistical Process Control for continuous improvement of the manufacturing process
… criteria (AIC), a recognized statistical model selection criterion, for objective model selection for the purpose of establishing the most representative control limits in the application of SPC. The most representative control limits are instrumental in eliminating unnecessary use of …
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Model Selection with Information Criteria
This thesis is on model selection using information criteria. The information criteria include generalized information criterion and a family of Bayesian information criteria. The properties and improvement of the information criteria are investigated. We analyze nonasymptotic and asymptotic …
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A Theoretical Development and Simulation-Based Comparison of Four Parameter Estimation Methods for the Spatio-Temporal Autologistic Model with Emphasis on Maximum Generalized and Block Generalized Pseudolikelihood
… spatially dependent binary observations is often modeled using the autologistic model. It is well known that likelihood-based inference methods cannot be employed in the usual way to estimate the parameters of the autologistic model due to the intractability of the normalizing constant for the …
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A Theoretical Development and Simulation-Based Comparison of Four Parameter Estimation Methods for the Spatio-Temporal Autologistic Model with Emphasis on Maximum Generalized and Block Generalized Pseudolikelihood
… spatially dependent binary observations is often modeled using the autologistic model. It is well known that likelihood-based inference methods cannot be employed in the usual way to estimate the parameters of the autologistic model due to the intractability of the normalizing constant for the …
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An Economic Analysis of Evolving Health Hazards
… 2 develops a spatial filtering panel data count model to examine the factors that contributed to the high prevalence of human West Nile virus (WNV) in California and Colorado using county-level data from 2003 to 2007. An econometric analysis was performed using a random effects negative binomial …