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 10 of 10 for “"Self-normalization"”.
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Statistical inference with complex datasets: from self normalization to machine learning
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms
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Semantic modeling of the natural language of Wikipedia annotations
… We show that the isotropy property leads to self-normalization allowing for the design of an efficient parameter estimation algorithm that we christen wiki2vec. The self-normalization property of IBOE is validated empirically on the Wikipedia corpus and is also of independent mathematical …
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Statistical inference for dependent data
… data. Specifically, in Chapter 1, we develop a self-normalization based test to test the structural stability of temporally dependent functional observations. We propose new tests to detect the differences of the covariance operators and their associated characteristics of two functional time …
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Photoelectron holography of metal adsorbates on semiconductor surfaces
… effects of certain experimental variations in a self-normalization of the photoemission data. Angle resolved photoemission from a monolayer of Bi adsorbed on Si(lll) shows fine-structure oscillations in the branching ratio of the Bi 5d core level due to diffraction effects. These oscillations are …
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Statistical issues and developments in time series analysis and educational measurement
… arbitrary tuning parameter. By adopting a self-normalization idea, we modify the subsampling procedure of Hall et al.(1998) and the resulting procedure does not require consistent variance estimation. The modi ed subsampling procedure only involves the choice of the subsampling widow width, …
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Change point detection for high dimensional data and valid inference for Bayesian linear models
… in real-time. Unlike existing work based on self-normalization, we introduce a class of estimators for $q$-norm of the covariance matrix and prove their ratio consistency. To facilitate fast computation, we further develop recursive algorithms to improve the computational efficiency of the …
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Statistical inference for high-dimensional data
… the trimming technique and utilizing the self-normalization principle. Under the fixed-b asymptotics, where we fix the proportion of trimming parameter over the sample size, we derive the limiting distributions of our test statistic under both the null and local alternatives of a single …
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Inference of time series regression models with weakly dependent errors
In this thesis we develop inferential methods for time series models with weakly dependent errors in the following three aspects. The first aspect concerns the issue of the size-distortion in the presence of strong temporal dependence, which is well-known in the literature. There are recently …
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Likelihood Ratio Combination of Multiple Biomarkers and Change Point Detection in Functional Time Series
… functions. In our study, we propose a novel self-normalized test for functional time series implemented via a non-overlapping block bootstrap to circumvent reliance on FPCA. The SN factor ensures both monotonic power and adaptability for detecting diverse change functions on complex data. We …