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Rozprawy doktorskie na temat „Bayelsa State”

Autor: Grafiati

Data publikacji: 2 czerwca 2025

Data aktualizacji: 31 lipca 2025

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Eguruze, Ebikinei Stanley. "A study of what young people and community organisations perceive as their support needs in Bayelsa State of Nigeria in 'tackling poverty' and 'How to sway policy makers, using social marketing techniques'." Thesis, Cardiff Metropolitan University, 2015. http://hdl.handle.net/10369/7834.

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This study investigates what young people and community organisations see as their support needs in Bayelsa State of Nigeria in “tackling poverty. It also examines the process of influencing policy makers, using social marketing techniques. It seeks to expand understanding of the poverty elimination processes: not only within a developing country’s rural environmental context, but also endeavours to generalize the findings more broadly. It seeks an inclusive approach to policy determination driven by involving grassroots levels. A mixed-methods research design was adopted engaging a quantitati

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Frühwirth-Schnatter, Sylvia. "Bayesian Model Discrimination and Bayes Factors for Normal Linear State Space Models." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1993. http://epub.wu.ac.at/108/1/document.pdf.

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It is suggested to discriminate between different state space models for a given time series by means of a Bayesian approach which chooses the model that minimizes the expected loss. Practical implementation of this procedures requires a fully Bayesian analysis for both the state vector and the unknown hyperparameters which is carried out by Markov chain Monte Carlo methods. Application to some non-standard situations such as testing hypotheses on the boundary of the parameter space, discriminating non-nested models and discrimination of more than two models is discussed in detail. (author's a

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Ravet, Alexandre. "Introducing contextual awareness within the state estimation process : Bayes filters with context-dependent time-heterogeneous distributions." Thesis, Toulouse, INSA, 2015. http://www.theses.fr/2015ISAT0045/document.

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Ces travaux se focalisent sur une problématique fondamentale de la robotique autonome: l'estimation d'état. En effet, la plupart des approches actuelles permettant à un robot autonome de réaliser une tâche requièrent tout d'abord l'extraction d'une information d'état à partir de mesures capteurs bruitées. Ce vecteur d'état contient un ensemble de variables caractérisant le système à un instant t, comme la position du robot, sa vitesse, etc. En robotique comme dans de nombreux autres domaines, le filtrage bayésien est devenu la solution la plus populaire pour estimer l'état d'un système de faço

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Yin, Jiani. "Bayesian Nonparametric Models for Multi-Stage Sample Surveys." Digital WPI, 2016. https://digitalcommons.wpi.edu/etd-dissertations/197.

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It is a standard practice in small area estimation (SAE) to use a model-based approach to borrow information from neighboring areas or from areas with similar characteristics. However, survey data tend to have gaps, ties and outliers, and parametric models may be problematic because statistical inference is sensitive to parametric assumptions. We propose nonparametric hierarchical Bayesian models for multi-stage finite population sampling to robustify the inference and allow for heterogeneity, outliers, skewness, etc. Bayesian predictive inference for SAE is studied by embedding a parametric

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Frühwirth-Schnatter, Sylvia. "Recursive Residuals and Model Diagnostics for Normal and Non-Normal State Space Models." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1994. http://epub.wu.ac.at/1540/1/document.pdf.

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Model diagnostics for normal and non-normal state space models is based on recursive residuals which are defined from the one-step ahead predictive distribution. Routine calculation of these residuals is discussed in detail. Various tools of diagnostics are suggested to check e.g. for wrong observation distributions and for autocorrelation. The paper also covers such topics as model diagnostics for discrete time series, model diagnostics for generalized linear models, and model discrimination via Bayes factors. (author's abstract)<br>Series: Forschungsberichte / Institut für Statistik

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Westerfield, Jane R. "An investigation of the life styles and performance of three singer-comediennes of American vaudeville : Eva Tanguay, Nora Bayes and Sophie Tucker." Virtual Press, 1987. http://liblink.bsu.edu/uhtbin/catkey/515977.

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In the early days of the twentieth century when vaudeville was the most popular theatrical entertainment in America, there were a number of female singers who became its star performers. In the process of conducting preliminary research for a dissertation topic on female singers of this era, it quickly became evident that while much has been written about opera singers of that era, only limited material was available on female vaudeville singers. Furthermore, the small amount of information which was available was so randomly scattered among various sources that it was difficult to perceive a

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Aboalela, Rania Anwar. "An Assessment of Knowledge by Pedagogical Computation on Cognitive Level mapped Concept Graphs." Kent State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=kent1496941747313396.

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Yu, Xue Qin. "Comparing survival from cancer using population-based cancer registry data - methods and applications." Thesis, The University of Sydney, 2007. http://hdl.handle.net/2123/1774.

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Over the past decade, population-based cancer registry data have been used increasingly worldwide to evaluate and improve the quality of cancer care. The utility of the conclusions from such studies relies heavily on the data quality and the methods used to analyse the data. Interpretation of comparative survival from such data, examining either temporal trends or geographical differences, is generally not easy. The observed differences could be due to methodological and statistical approaches or to real effects. For example, geographical differences in cancer survival could be due to a number

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Yu, Xue Qin. "Comparing survival from cancer using population-based cancer registry data - methods and applications." University of Sydney, 2007. http://hdl.handle.net/2123/1774.

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Doctor of Philosophy<br>Over the past decade, population-based cancer registry data have been used increasingly worldwide to evaluate and improve the quality of cancer care. The utility of the conclusions from such studies relies heavily on the data quality and the methods used to analyse the data. Interpretation of comparative survival from such data, examining either temporal trends or geographical differences, is generally not easy. The observed differences could be due to methodological and statistical approaches or to real effects. For example, geographical differences in cancer survival

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Jüngel, Matthias. "The memory-based paradigm for vision-based robot localization." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2012. http://dx.doi.org/10.18452/16593.

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Für mobile autonome Roboter ist ein solides Modell der Umwelt eine wichtige Voraussetzung um die richtigen Entscheidungen zu treffen. Die gängigen existierenden Verfahren zur Weltmodellierung basieren auf dem Bayes-Filter und verarbeiten Informationen mit Hidden Markov Modellen. Dabei wird der geschätzte Zustand der Welt (Belief) iterativ aktualisiert, indem abwechselnd Sensordaten und das Wissen über die ausgeführten Aktionen des Roboters integriert werden; alle Informationen aus der Vergangenheit sind im Belief integriert. Wenn Sensordaten nur einen geringen Informationsgehalt haben, wie zum

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Liley, Albert James. "Statistical co-analysis of high-dimensional association studies." Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/270628.

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Modern medical practice and science involve complex phenotypic definitions. Understanding patterns of association across this range of phenotypes requires co-analysis of high-dimensional association studies in order to characterise shared and distinct elements. In this thesis I address several problems in this area, with a general linking aim of making more efficient use of available data. The main application of these methods is in the analysis of genome-wide association studies (GWAS) and similar studies. Firstly, I developed methodology for a Bayesian conditional false discovery rate (cFDR)

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Hee, Sonke. "Computational Bayesian techniques applied to cosmology." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/273346.

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This thesis presents work around 3 themes: dark energy, gravitational waves and Bayesian inference. Both dark energy and gravitational wave physics are not yet well constrained. They present interesting challenges for Bayesian inference, which attempts to quantify our knowledge of the universe given our astrophysical data. A dark energy equation of state reconstruction analysis finds that the data favours the vacuum dark energy equation of state $w {=} -1$ model. Deviations from vacuum dark energy are shown to favour the super-negative ‘phantom’ dark energy regime of $w {< } -1$, but at low st

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"Bayesian Model Discrimination and Bayes Factors for Normal Linear State Space Models." Department of Statistics and Mathematics, 1993. http://epub.wu-wien.ac.at/dyn/dl/wp/epub-wu-01_a1f.

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Yang, Kung-Han, and 楊恭漢. "Two-Stage Approach to Bayes Sequential Estimation in the Poisson Process." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/59949492230347091889.

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碩士<br>淡江大學<br>數學學系<br>87<br>We consider {N(t); t \ge 0} be a homogeneous Poisson process with the unknown intensity parameter λ, where λ is gamma distribution. It is desired to estimate λ, subject to the error measured by a loss function and the sampling cost. The Bayes sequential estimation problem is to seek an optimal sequential procedure which includes an optimal stopping time and a Bayes estimator. The problem of determining optimal stopping rules is usually more formidable, and although such stopping rules exist under fairly general conditions, their exact determination is usually very d

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Hwang, Bang-Hwang, and 黃榜煌. "Two Stage Approach to Bayes Sequential Estimation in the Exponential Distribution." Thesis, 1998. http://ndltd.ncl.edu.tw/handle/03593077172527607183.

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碩士<br>淡江大學<br>數學學系<br>86<br>The Bayes sequential estimation problem is to seek an optimal sequential procedure Which includes an optimal stopping time and a Bayes estimator. (i.e. the posterior mean of θ for square error loss.) The problem of determining optimal stopping rules is usually more formidable, and although such stopping rules exist under fairly general conditions, their exact determination is usually very difficult. There are many papers that discussed the optimal stopping time.

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Wu, Yung-Tung, and 吳永通. "A two-stage approach to Bayes sequential estimation without using the prior information." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/68104736857777340356.

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碩士<br>淡江大學<br>數學學系<br>90<br>The Bayes sequential estimation problem is to seek an optimal sequential procedure which includes an optimal stopping time and a Bayes estimator. The Bayes estimator is always obtained in the problem, and the optimal stopping time exists, but the exact determination of the optimal stopping time appears to be a formidable task, in practice. There are many papers that discussed the asymptotic efficiency for the proposed stopping time, and its Bayes risk compare to Bayes risk of optimal stopping time.In the classical non-Bayesian sequential estimation problem, Robbins

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Sadil, Patrick. "Visual Recollection for Non-Declarative Representations." 2019. https://scholarworks.umass.edu/masters_theses_2/751.

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Recollection is a pattern completion process that enables retrieval of arbitrarily associated information following minimal study. These attributes enable recollection to support retrieval of many kinds of mnemonic representations, from highly associative contextual information to very specific low-level representations. However, recollection is typically studied in the context of declarative memory tasks, in which participants exhibit recollection by explicitly reporting on the recollected information. Is it the case that recollection is limited to declarable representations, or is it a more

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Liu, Miao. "Efficient Bayesian Nonparametric Methods for Model-Free Reinforcement Learning in Centralized and Decentralized Sequential Environments." Diss., 2014. http://hdl.handle.net/10161/9043.

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<p>As a growing number of agents are deployed in complex environments for scientific research and human well-being, there are increasing demands for designing efficient learning algorithms for these agents to improve their control polices. Such policies must account for uncertainties, including those caused by environmental stochasticity, sensor noise and communication restrictions. These challenges exist in missions such as planetary navigation, forest firefighting, and underwater exploration. Ideally, good control policies should allow the agents to deal with all the situations in an environ

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Zhang, Pengyue. "Study designs and statistical methods for pharmacogenomics and drug interaction studies." Diss., 2016. http://hdl.handle.net/1805/11300.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>Adverse drug events (ADEs) are injuries resulting from drug-related medical interventions. ADEs can be either induced by a single drug or a drug-drug interaction (DDI). In order to prevent unnecessary ADEs, many regulatory agencies in public health maintain pharmacovigilance databases for detecting novel drug-ADE associations. However, pharmacovigilance databases usually contain a significant portion of false associations due to their nature structure (i.e. false drug-ADE associations caused by co-medications). Besides ph

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Zhong, Jianling. "Computational Inference of Genome-Wide Protein-DNA Interactions Using High-Throughput Genomic Data." Diss., 2015. http://hdl.handle.net/10161/11368.

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<p>Transcriptional regulation has been studied intensively in recent decades. One important aspect of this regulation is the interaction between regulatory proteins, such as transcription factors (TF) and nucleosomes, and the genome. Different high-throughput techniques have been invented to map these interactions genome-wide, including ChIP-based methods (ChIP-chip, ChIP-seq, etc.), nuclease digestion methods (DNase-seq, MNase-seq, etc.), and others. However, a single experimental technique often only provides partial and noisy information about the whole picture of protein-DNA interac

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