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 40 for “"Probability models"”.
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Probability Models for Targeted Borrowing of Information
… dissertation is devoted to building Bayesian models for complex data, which are geared toward specific inferential aspects of applied problems. This broad topic is explored via three methodological case-studies, unified by the use of latent variables to build structured yet flexible models. …
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Probability models for information retrieval based on divergence from randomness
This thesis devises a novel methodology based on probability theory, suitable for the construction of term-weighting models of Information Retrieval. Our term-weighting functions are created within a general framework made up of three components. Each of the three components is built independently …
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Generating aggregate sales response functions from household purchase probability models
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.
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Generative Models for Computer Vision
… build robust computer vision algorithms, scene models are necessary that are capable of capturing various aspects of the data at the same time. These models should be fairly simple, but capable of adapting to the data. Flexible models, as defined in the machine learning community, are minimally …
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The Doubly Inflated Poisson and Related Regression Models
… this thesis, two Doubly Inflated Poisson (DIP) probability models, DIP (<em>p</em>, λ) and DIP (<em> p</em>1, <em>p</em>2, λ), are discussed for situations where there is another inflated value <em>k</em> > 0 besides the inflated zeros. The distributional properties such as identifiability, …
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Analysis of Models for Longitudinal and Clustered Binary Data
… of this dissertation deals with two multivariate probability models, the first order Markov chain model and the multivariate probit model, that adhere to the feasible bounds on the correlation. For both the models we obtain maximum likelihood estimates for the regression and correlation …
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Some Probability Methods For DNA Sequence Analysis
Probability models are employed in the analysis of data emerging from DNA sequence studies. To sequence DNA sequences, one of the methods employed is to sequence overlapping fragments of the DNA. These overlapping fragments form a contig. In this thesis, probability methods to study the mean number …
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Uses of the Hypergeometric Distribution for Determining Survival or Complete Representation of Subpopulations in Sequential Sampling
<p>This thesis will explore the hypergeometric probability distribution by looking at many different aspects of the distribution. These include, and are not limited to: history and origin, derivation and elementary applications, properties, relationships to other probability models, kindred …
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QUANTITATIVE RELIABILITY ANALYSIS OF A HIGH VOLTAGE DIRECT CURRENT TRANSMISSION SYSTEM
… This thesis illustrates the application of probability techniques to the reliability evaluation of a three phase HVDC bridge composed of mercury arc valves. The approach is developed by which the number of spare valves required to achieve a predetermined reliability level can be obtained for …
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A quadrature-based technique for robust design with computer simulations
… the polynomial response is not separable, two probability models based on the effect hierarchy principle are used to generate a large number of polynomial response functions. The proposed method and alternative methods are applied to these polynomial response functions to investigate accuracy. …
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THE ASSOCIATION BETWEEN RECEIVING A MENTAL HEALTH DIAGNOSIS AND FIRST TERM ATTRITION (FTA) IN U.S. NAVY SAILORS: A 10-YEAR PANEL STUDY
… statistics with nested logistic regression models that refine mental health measures from an “all-inclusive” diagnostic category to broad categories and an individual diagnostic specification in a joint model. Linear probability models provide robustness checks. Results indicate …
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On The Maintenance Modeling and Optimization of Repairable Systems: Two Different Scenarios
… Because of the complexity of the underlying probability models, we use simulation modeling to estimate availability performance and meta-modeling to convert the reliability and maintainability parameters of the repairable system into an availability estimate without the simulation effort. As …
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Towards patient selection for cranial proton beam therapy – Assessment of current patient-individual treatment decision strategies
… this thesis. First, normal tissue complication probability models for early and late side effects were developed and validated in external cohorts based on data of patients treated with proton beam therapy. Acute erythema as well as acute and late alopecia were associated with high-dose …
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A controlled sensing approach to graph classification
… to maximize the decay of classification error probability with sample size by formulating the classification problem as a composite sequential hypothesis test with control. In contrast to prior work, posing the problem as a composite sequential hypothesis test with control provides provable …
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Stochastic availability analysis and modeling of longwall mining operations
… assessment and stochastic systems analysis, five probability models are formulated and solved with respect to different longwall operating logic. The implementation of these models is demonstrated with a number of case studies. Furthermore, three important applications of the results have been …
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One and Two-Step Estimation of Time Variant Parameters and Nonparametric Quantiles
… quantiles and time variant parameters from probability models. First, we investigate and develop nonparametric techniques for measuring extreme quantiles. The method involves aggregating data by an explanatory variable such as time and smoothing the resulting data with a nonparametric method …
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Nonlinear Dynamics, Stochastic Methods, And Predictive Modelling For Infectious Disease: Application To Public Health And Epidemic Forecasting
Statistical models must adapt to the evolving nature of many processes over time. This thesis introduces flexible models and statistical methods designed to infer data-generating processes that vary temporally. The primary objective is to develop frameworks for efficient estimation and prediction …
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Data Distribution Management In Large-scale Distributed Environments
… the input size of a simulation based on probability models. The optimum DDM performance is best approached by adapting the simulation running in a mode that is most appropriate to the size of the simulation.
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Stochastic modelling for the analysis of blowout risk in exploration drilling.
… has been secured through examinations of probability models and their influence on risk interpretation and overall analysis objectives; analyses of current physical causal mechanisms and deterministic coherences; and the decomposition of event sequences leading to blowout with subsequent …
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Cumulative Distribution Networks: Inference, Estimation and Applications of Graphical Models for Cumulative Distribution Functions
This thesis presents a class of graphical models for directly representing the joint cumulative distribution function (CDF) of many random variables, called cumulative distribution networks (CDNs). Unlike graphical models for probability density and mass functions, in a CDN, the marginal …
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