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 10 of 10 for “"Robust statistical methods"”.
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Robust Statistical Methods for Measurement Calibration in Large Electric Power Systems
… coefficients are estimated by means of highly robust estimator, namely the Least Median of Squares (LMS) estimator. The calibration method is applicable to large systems by means of network tearing and dynamic programming. The number of field calibrations can be decreased further whenever …
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Robust estimation, regression and ranking with applications in portfolio optimization
Classical methods of maximum likelihood and least squares rely a great deal on the correctness of the model assumptions. Since these assumptions are only approximations of reality, many robust statistical methods have been developed to produce estimators that are robust against the deviation from …
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Reasoning about quantities in natural language
… reasoning, and address the problem of developing robust statistical methods for these tasks. We show that standard NLP tools are not sufficient to obtain the abstraction needed for quantitative reasoning; the standard NLP pipeline needs to be extended in various ways. We propose several technical …
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Statistical methods for random rotations
… location model for orientation data is simple, statistical methods for estimation and inference for the location parameter, S are limited. In this dissertation we develop point estimation and confidence region methods for the central orientation.</p> <p>Both extrinsic and intrinsic approaches to …
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Rail Rebound: The Impact of Freight Rails on Regional Development in the United States, 1970-2010
… considers the spatial effects and produces more robust results. There are four broad major findings of this research. First, freight rail is a distributive force. Second, freight rail contributes to the urbanization and suburbanization process. Third, freight rail facilitates demographic and …
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Advanced Robust Statistical Learning Methods with Application in Healthcare and Manufacturing
… the development and validation of advanced robust statistical methods tailored for applications in healthcare and manufacturing. This work consists of three main parts, each addressing unique challenges and demonstrating the necessity of robust algorithms in statistical learning. In the …
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Statistical modeling of longitudinal survey data with binary outcomes
… arising due to repeated measurements. The statistical methods used for analyzing such data should account for stratification, clustering and unequal probability of selection as well as within-subject correlations due to repeated measurements. The complex multi-stage design approach has been …
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Statistical methods to improve understanding of the genetic basis of complex diseases
Robust statistical methods, utilising the vast amounts of genetic data that is now available, are required to resolve the genetic aetiology of complex human diseases including immune-mediated diseases. Essential to this process is firstly the use of genome-wide association studies (GWAS) to …
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Fast and Robust Automatic Segmentation Methods for MR Images of Injured and Cancerous Tissues
… segmentation techniques that make use of robust statistical methods allows for fast and unbiased analysis of MR images.</p><p>In this dissertation, I propose segmentation methods that fall into two classes---(a) segmentation via optimization of a parametric boundary, and: b) segmentation …
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The First Insights into the Phylogeny, Genomics, and Ecology of the Novel Bacterial Phylum Armatimonadetes
… be reliably associated across studies. Multiple robust statistical methods were used to arrive at a consensus on the partitioning of classes and neighbouring phyla. The process also helped to identify and exclude candidate phyla previously misattributed to Armatimonadetes, thus better defining …