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Showing 1 to 15 of 15 for “"U-statistics"”.
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Maximum empirical likelihood estimation in U-statistics based general estimating equations
… empirical likelihood estimates (MELE's) in U-statistics based general estimating equations (UGEE's). Our technical maneuver is the jackknife empirical likelihood (JEL) approach. We give the local uniform asymptotic normality condition for the log-JEL for UGEE's. We derive the estimating …
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A Jackknife Empirical Likelihood Approach To Goodness Of Fit U-Statistic Testing With Side Information
<p>Motivated by applications to goodness of fit U-statistics testing, the jackknife empirical likelihood of Jing, <em>et al.</em> (2009) is justified with an alternative approach, and the Wilks theorem for vector U-statistics is proved. This generalizes Owen's empirical likelihood theorem for a …
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Essays on Cross-Sectional and Network Dependence
… for both non-degenerate and degenerate U-statistics with cross-sectionally dependent underlying processes in the Wasserstein metric. We show that the convergence rates depend on the mixing rates, the sparsity of the cross-sectional dependence, and the moments of the kernel functions. …
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A day in the PARC: an interactive qualitative analysis of school climate and teacher effectiveness through professional action research collaboratives
… Analysis and non-parametric Mann Whitney U statistics were used to explore these effects. PARC participation was found to have no significant effect on school climate or teacher effectiveness; however, PARC Schools demonstrated higher school effectiveness scores than Comparison Schools. This …
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Statistical inference for high-dimensional data via U-statistcs
The student, Runmin Wang, submitted this Dissertation for approval on 2020-07-10 at 14:17.
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Statistical uncertainty quantification for machine learning models and training acceleration for graph neural networks
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01
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Model-Based Measures of Interrater Agreement
… of Lehmann's theory of two-sample U-statistics (1951). Standard errors are defined using this asymptotic approximation, Owen's pigeonhole bootstrap (2007) and a counting statistics approach. Simulation studies suggest that the new estimation methods have negligible bias and with the …
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Random survival forests: quantifying uncertainties and other extensions
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms
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Dependence testing in high dimension
"The study of dependence for high dimensional data originates in many different areas of contemporary research. While a lot of existing work focuses on measuring the linear dependence and monotone dependence for fixed dimensional data, comparatively less is concerned for more complex dependence …
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Three Essays on Testing for Cross-Sectional Dependence and Specification in Large Panel Data Models
… Chen, Zhang and Zhong (2010) who</p> <p>use $U$-statistics to test for sphericity of the variance-covariance matrix</p> <p>in statistics. Since the errors are unobservable, the residuals from the</p> <p>fixed effects regression are used. The limiting distribution of the proposed</p> <p>test …
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Empirical Likelihood With Applications
… However, when treating with nonlinear statistics via the empirical likelihood method, the computation burden is quite heavy. The Jackknife Empirical Likelihood method, brought out by Jing et al. (2009), is surprisingly easy to cope with nonlinear statistics and largely relieves …
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High-dimensional change point detection for mean and location parameters
… first part, we consider cumulative sum (CUSUM) statistics that are widely used in the change point inference and identification. We study two problems for high-dimensional mean vectors based on the $\ell^{\infty}$-norm of the CUSUM statistics. For the problem of testing for the existence of a …
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Statistical inference in high dimensional data and machine learning
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-05-01
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Statistical inference for high-dimensional data
… three important problems in high-dimensional statistics and develop some new methods and theory, which show the limitation of some existing approaches and motivate the use of our proposed methods. In the first chapter, we study distance covariance, Hilbert-Schmidt covariance (aka …
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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 …