Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 65 for “"kernel density estimation"”.
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Mean Hellinger Distance as an Error Criterion in Univariate and Multivariate Kernel Density Estimation
… choosing the bandwidth matrix for multivariate kernel density estimation. More recently other criteria have been advocated as competitors to the MISE, such as the mean absolute error. In this study we define a weighted version of the Hellinger distance for multivariate densities and show that it …
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Spatial Analysis of Fatal Automobile Crashes in Kentucky
… points and average daily traffic flow; 2) planar kernel density estimation of FARS crash events based on temporal and demographic attributes within the data; and 3) two case studies using network kernel density estimation along roadways to determine hot spots fatal crashes in Jefferson County and …
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A Probabilistic Approach To Multiple-Instance Learning
… of instances. In the second approach, embedded kernel density estimation (ekde), bags are represented in an instance induced (very high dimensional) space. A parametric stochastic neighbor embedding method is applied to learn a mapping that projects bags into a 2-d or 1-d space. Class …
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Nonlinear dynamic process monitoring using kernel methods
The application of kernel methods in process monitoring is well established. How- ever, there is need to extend existing techniques using novel implementation strate- gies in order to improve process monitoring performance. For example, process monitoring using kernel principal component analysis …
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Novel methods of supernova classification and type probability estimation
… from their contaminating counterparts, kernel density estimation and boosting. In the second half of this thesis we shift focus from classification to the related problem of type probability estimation, and ask how best to use type probabilities.
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Graphical tools for the examination of high-dimensional functions obtained as the result of Bayesian analysis
… – especially Projection Pursuit methods – and Kernel Density Estimation (KDE). During the course of this work acceptable prior technology was found for MCMC and, once the decision for it had been made, Projection Pursuit. However, the current state of KDE gave rise to several objections. Not …
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Practical methods for data mining with massive data sets
… data sets. Advanced techniques such as binned kernel density estimation, tours, and mode-based projection pursuit will be explored. Mean-centered binning will be introduced as an improved method for binned density estimation. The density grand tour will be demonstrated as a means of exploring …
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Using information theoretic measures to evaluate support vector machine kernels
… in the input data to evaluate the ability of a kernel to successfully separate a class in some feature space. This method is built on the fundamental idea that kernel density estimation in some input space is equivalent to an inner product on some Hilbert space. Estimators of Renyi's generalized …
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Motor Vehicle Collisions in London, Ontario: Estimating the influence of the built environment and children’s potential exposure
… and identifies hotspots using a network kernel density estimation method within a GIS. Logistic regression analysis revealed that bike lanes were negatively associated with hotspots, while sidewalks were positively associated. Study #2 estimated children’s risk of being exposed to a motor …
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From Biology to Algorithms
… abstracted model is shown to have connections to Kernel Density Estimation, through developing these connections the Receptor Density Algorithm is developed. By design, the algorithm has application in tracking probability distributions. Finally, the thesis demonstrates the algorithm on a related …
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Geovisual methods and techniques for the development of three-dimensional tactical intelligence assessments
… further geovisual analysis, for instance, estimations of urban risks exposure. Specific methods and workflows are developed to facilitate the integration of spatio-temporal crime scene analysis results into 3D tactical intelligence assessments. Analysis comprises hotspot identification with …
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Spatial Distributions of Domestic and Non-Domestic Violence by Firearm Involvement
… and 2021 (n = 5,727) were used for the study. Kernel density estimation maps were produced for each of the relevant subgroups, and compared pairwise using spatial point pattern testing to establish if significant differences exist between subgroup crime occurrence rates for each of the census …
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Problems related to efficacy measurement and analyses
… objectively compared to the earlier approaches. Kernel density estimation is a useful non-parametric method that has not been well utilized as an applied statistical tool, mainly due to its computational complexity. The current study shows that this method is robust even under correlation …
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Anomaly detection methods for unmanned underwater vehicle performance data
… focus on two anomaly detection techniques: (1) Kernel Density Estimation (KDE) Anomaly Detection and (2) Local Outlier Factor. Results are presented for selected UUV systems and data features, and initial findings provide insight into the effectiveness of these algorithms. Lastly, we explore …
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Core Selection by Wolf Packs in a Human-Dominated Landscape: A Case Study in the Mountains of Southern Poland
… data. Core areas were then defined using fixed-kernel density estimation techniques and 50% isopleths. Habitat variables were then compared between core plots and non-core plots. Scat marking of both packs resembled the Hot Spots pattern of marking proposed by Zub et al. (2003), rather than the …
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Core Selection by Wolf Packs in a Human-Dominated Landscape: A Case Study in the Mountains of Southern Poland
… data. Core areas were then defined using fixed-kernel density estimation techniques and 50% isopleths. Habitat variables were then compared between core plots and non-core plots. Scat marking of both packs resembled the Hot Spots pattern of marking proposed by Zub et al. (2003), rather than the …
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Modeling trustworthy opinion using an uncertainty-aware approach
… and categorical opinion. The model uses a Kernel Density Estimation based uncertainty-aware approach to estimate its probability distribution, and summarize trustworthy information based on this distribution. Experiments indicate that TOM not only has outstanding performance on the …
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Investigating the Spatial and Statistical Dimensions of Mortuary Choice in the Historical-Period Old City Cemetery in Roslyn, Washington
… analysis (Ripley’s <em>K</em>-Function), spatial density analysis (Kernel Density Estimation), and non-spatial statistical significance assessments (Factor analysis and Pearson’s R), and identified several demographic-based mortuary trends. Similarities in some ages and nationalities were …
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