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 9 of 9 for “"multiple change points"”.
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Bayesian Inference Based on Nonparametric Regression for Highly Correlated and High Dimensional Data
… studies, enabling flexible modeling of multiple covariate effects within strata and their complex interactions, denoted as fused kernel machine regression (Fused-KMR). Lastly, it presents a Bayesian hierarchical framework designed to identify multiple change points in the relationship …
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Detecting trend and abrupt changes in mean and extreme climate variables and assessing the impacts on agriculture
… management. To assess the impacts of climate change on human and natural environment, as well as to understand the causes of climate change, it is essential to investigate historic and current climate changes and predict potential future climate changes. This thesis is to develop a multiple …
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Some Aspects on Data Modelling
… rule mining from transaction data and structural change estimation in time-ordered sequence, are studied. Informative association rule mining is fundamental for knowledge discovery from transaction data, for which brute-force search algorithms, e.g., the well-known Apriori algorithm, were …
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Inference and Estimation in Change Point Models for Censored Data
<p>In general, the change point problem considers inference of a change in distribution for a set of time-ordered observations. This has applications in a large variety of fields and can also apply to survival data. With improvements to medical diagnoses and treatments, incidences and mortality …
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Detecting climate change and its impacts on crop yield in the continental United States
… critical roles in water resources management. Changes in climate have brought up concerns stationarity in climate, a fundamental assumption used in water resources planning and management, due to the change of climatic time series in mean and/or variance. Detecting of past changes is essential …
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Some Advanced Semiparametric Single-index Modeling for Spatially-Temporally Correlated Data
… the first is to propose a model for detecting change points simultaneously with estimating the unknown function; the second is to develop two models for spatially correlated data; and the third is to further develop two models for spatially-temporally correlated data. To address the first …
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Change point detection for high dimensional data and valid inference for Bayesian linear models
… statistical methodologies for high dimensional change point detection and inference for Bayesian linear models. In the first project, we propose a change point detection method testing mean shift for high dimensional observations with unknown heteroscedasticity. The proposed tests target a dense …
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High-dimensional change point detection for mean and location parameters
Change point inference refers to detection of structural breaks of a sequence observation, which may have one or more distributional shifts subject to models such as mean or covariance changes. In this dissertation, we consider the offline multiple change point problem that the sample size is fixed …
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Mehrdimensionale Change-Point-Schätzung mit U-Statistiken
Wir betrachten ein mehrdimensionales Change-Point-Problem. Seien X1;n; : : : ;Xn;n unabhängige Zufallselemente bei denen q, q 2 N, Verteilungswechsel auftreten. Dass heisst, es existiert ein Vektor µ = (µ1; : : : ; µq) 2 Rq mit 0 = µ0 < µ1 < ¢ ¢ ¢ < µq < µq+1 = 1 sowie Verteilungen …