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 8 of 8 for “"Non-Homogeneous Poisson Process"”.
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Decision Support Tool for Optimal Replacement of Plumbing Systems
… plumbing pipes is presented. The deterioration process is grouped into early, normal and late stages. Because available data reflects late stage process, an optimization, neural network and curve fitting models are developed to infer early and normal stage behavior of the plumbing system. …
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Sequential Modelling and Inference of High-frequency Limit Order Book with State-space Models and Monte Carlo Algorithms
… state-space models from the field of signal processing as well as a number of Bayesian inference algorithms such as particle filtering, Markov chain Monte Carlo and variational inference algorithms, this thesis presents my extensive research into the high-frequency limit order book covering a …
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Index-linked catastrophe instrument valuation
… estimate the parameters for the underlying loss process and simulate the instrument prices. Chapters 3 to 5 of this thesis loosely follow this process. In Chapter 3 we propose an index-linked catastrophe bond pricing model, which pervades in subsequent chapters. We furthermore show how, under …
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Software Reliability Models
<p>The problem considered here is the building of Non-homogeneous Poisson Process (NHPP) model. Currently existing popular NHPP process models like Goel-Okumoto (G-O) and Yamada <em>et al</em> models suffer from the drawback that the probability density function of the inter-failure times is an …
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Statistical Methods For Two Problems In Cancer Research: Analysis of Rna-Seq Data From Archival Samples and Characterization of Onset of Multiple Primary Cancers
… a Bayesian recurrent event model based on a non-homogeneous Poisson process in order to estimate a set of penetrance for MPC related to LFS. Toward the associated inference, we employed the familywise likelihood that allows for utilizing genetic information inherited through the family. The …
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Recurrent-Event Models for Change-Points Detection
… finite mixture model; the third part develops a non-parametric Bayesian model with a Dirichlet process prior. In the first part, two recurrent-event change-point models to detect the time of change in driving risks are developed. The models are based on a non-homogeneous Poisson process with …
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Some contributions to modeling usage sensitive warranty servicing strategies and their analyses
… explored in this research. A Bayesian updating process used in this context combines expert opinions with market data to improve the accuracy of the parameter estimates. The expected profit model investigated here captures the impact of juggling decision variables of 2-D pro-rated warranty and …
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A continuous-time formulation for spatial capture-recapture models
… physically hold them. Some examples of these new non-invasive sampling methods include scat or hair collection for genetic analysis, acoustic detection and camera trapping. In traditional capture-recapture (CR) and SCR studies populations are sampled at discrete points in time leading to clear and …