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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 12 of 12 for “"Risk Function"”.
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The Risk Function of The Preliminary Test Estimator in a Simultaneous Regression Equations Model
Made available in DSpace on 2014-12-11T17:13:14Z (GMT). No. of bitstreams: 1 7405539.pdf: 2265448 bytes, checksum: c6f9bdfd2b0237155850da5fdcff93e5 (MD5) Previous issue date: 1973
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Kernel Estimators in Complex Data Analysis
… density regions. We consider a different loss function from the one used in classical bandwidth selection problem and derive an asymptotic approximation to the corresponding risk function. A multi-stage plug-in bandwidth selection procedure is proposed to estimate the unknown quantity in the …
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Adaptive optimization problems under uncertainty with limited feedback
… destination when the objective is to minimize a risk function of the lateness. To capture distributional ambiguity, we assume that the arc travel times are only known through confidence intervals on some statistics and we design efficient algorithms minimizing the worst-case risk function. …
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Indirect Maternal Mortality Due to Malaria: A Systematic Review and Meta-Analysis
… and quantify the impact of pregnancy on the risk of malaria-associated death and the impact of malaria infection on the risk of pregnancy-associated mortality. Methods: A systematic review and meta-analysis were conducted using articles identified from PubMed database. A total of 10 studies …
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Lateral and Posterior Dynamic Bending of the Mid-Shaft Femur: Fracture Risk Curves for the Adult Population
The purpose of this study was to develop injury risk functions for dynamic bending of the human femur in the lateral-to-medial and posterior-to-anterior loading directions. A total of 45 experiments were performed on human cadaver femurs using a dynamic three-point drop test setup. All 45 tests …
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Tools for Multi-Objective and Multi-Disciplinary Optimization in Naval Ship Design
… Overall Measure of Effectiveness (OMOE) model or function is an essential prerequisite for optimization and design trade-off. This effectiveness can be limited to individual ship missions or extend to missions within a task group or larger context. A method is presented that uses the Analytic …
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Smallest Simultaneous Confidence Sets, Using Sufficiency and Invariance, With Applications to Manova and Gmanova
… of a randomized set estimator as a function (phi) : x (GAMMA) (--->) {0, 1}. Sufficiency is defined in terms of the family {P(,(theta),(gamma)):((theta), (gamma)) (epsilon) (THETA) x (GAMMA)} of distributions on x (GAMMA), where P(,(theta),(gamma)) is P(,(theta)) supported on x …
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Quantifying Postural Control, Concussion Risk, and Helmet Performance in Youth Football
… football as it relates to concussion. Balance dysfunction is often cited as one of the most common symptoms associated with a concussion. Several postural control assessments were assessed in order to develop a youth-specific testing protocol. A cognitive, dual-task assessment was presented for …
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The Development and Validation of a Biofidelic Synthetic Eye for the Facial and Ocular CountermeasUre Safety (FOCUS) Headform
… eye and orbit and corresponding eye injury risk criteria.
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Learning with structured decision constraints
… is based on minimizing estimated conditional risk functions. With this approach, we first estimate the conditional expected loss (i.e., conditional risk) function by regression, and then minimize it to predict an output. We analyze statistical and computational properties of this approach, and …
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Nonparametric Statistical Approaches for Benchmark Dose Estimation in Quantitative Risk Assessment
A major component of quantitative risk assessment involves dose-response modeling. Therein, an appropriate statistical model that approximately quantifies the relationship between exposure level (dose) and response (adverse endpoint) is fit to experimental data. The objective of this dissertation …
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Data Driven Nonparametric Detection
… algorithm are developed to solve the risk minimization problem, which is non-convex, and both algorithms are shown to converge to critical points.</p> <p>The other major topic of this thesis is composite outlier detection in centralized scenarios. The goal is to detect the existence of …