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 29 for “"finite sample performance"”.
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Robust Efficient Estimation of Semiparametric Covariate Models based on Minimum Hellinger Distance
… models, prove its consistency, and examine its finite-sample performance and robustness properties via Monte Carlo simulation studies and real data analysis. We further extend the MPHDE to the general covariate models, in which we prove the consistency and asymptotic normality of the proposed …
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Bayesian empirical likelihood for quantile regression
… directly maximizing empirical likelihoods. The finite sample performance of the proposed method is investigated empirically, where substantial efficiency gains are demonstrated with informative priors on common features across quantile levels.
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TESTING THE EQUALITY OF SEVERAL COVARIANCE FUNCTIONS FOR FUNCTIONAL DATA
… test and the quasi F-type tests, for the multi-sample equal-covariance function testing problem. The asymptotic null distributions of the tests are derived and methods based on Welch-Satterthwaite moment-matching or random permutation are proposed to approximate the null distributions. The …
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New approaches to modern statistical classification problems
… simulation study, which reveals its excellent finite-sample performance. Chapter 3 focuses on the k-nearest neighbour classifier. We first derive a new global asymptotic expansion for its excess risk, which elucidates conditions under which the dominant contribution to the risk comes from the …
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Essays on Optimal Transport Theory and Causal Inference: A Theoretical and Empirical Approach
… under primitive conditions. We investigate the finite sample performance of our estimator and Wald inference via simulation.
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Identification and estimation in panel models with overspecified number of groups
… Carlo simulations are conducted to examine the finite sample performance of our proposed method. Findings in the simulation confirm our theoretical results in the paper. Application to labor force participation also highlights the necessity to take into account of individual heterogeneity and …
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Adaptive Functional Data Analysis
… regression, where challenges arise from the infinite-dimensionality of their underlying spaces. For adaptive representation, the notion of mixture inner product spaces (MIPS) is developed, featuring an infinite-dimensional mixture of finite-dimensional subspaces. We show that MIPS provides a …
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Variable screening and graphical modeling for ultra-high dimensional longitudinal data
… scale which is similar to or smaller than the sample size. In chapter 2, we provide two types of SIS, and their iterative extensions (iterative SIS) to enhance the finite sample performance. An upper bound on the number of variables to be included is derived and assumptions are given under …
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Poisson regression with Laplace measurement error
… of that latent variable is unknown. Large sample properties of the proposed estimator, including the consistency and the asymptotic normality, are discussed. The finite sample performance of the proposed estimation procedure is evaluated by simulation studies, showing that the proposed …
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Memory Properties Of Transformations Of Linear Processes And Symmetric Gini Correlation
… Gini, and the proposed measure ρg shows superior finite sample performance, which makes it attractive in applications.
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Binary classification with training under both classes
… present a new result on the case of countably infinite alphabet. The goal of binary hypothesis testing is to decide between the two underlying probabilistic processes. Asymptotic optimality of binary hypothesis testing can be achieved with the knowledge of only one of the processes. It is also …
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Functional Linear Regression in High Dimensions
… encountered simultaneously when observations are sampled from random processes and a potentially large number of scalar covariates. It is difficult to apply existing methods for model selection and estimation. We propose a new class of partially functional linear models to characterize the …
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Modeling longitudinal data with interval censored anchoring events
… was interval censored. For the purpose of large-sample statistical inference in both models, we studied the asymptotic properties of the proposed functional estimator using empirical process theory. Theoretically, our method provided a general approach to study semiparametric maximum …
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Sparse selection in Cox models with functional predictors
… In this thesis, to study these large sample properties of the estimators, the fractional Brownian motion assumption is posed for the trajectories for mathematical tractability. Simulations are conducted to evaluate the finite sample performance of the methods, and a way to construct …
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On testing the change-point in the longitudinal bent line quantile regression model
… in previous works and thus is more reliable in finite sample performance. Furthermore, we demonstrate, through a series of simulations, that the proposed methods also outperform the extensively used bootstrap methods by providing more accurate and computationally efficient confidence intervals. …
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Hypothesis testing procedures for non-nested regression models
… asymptotic distributional properties, simulated finite sample performance and computational ease. A modification to the Fisher and McAleer JA-test was proposed and its properties investigated. As a compromise between the JA-test and the Orthodox F-test, it was shown to have an exact non-null …
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A covariate-adjusted classification model for multiple biomarkers in disease screening and diagnosis
… simulation study is conducted to evaluate the performance of this proposed method in finite sample sizes. The data of colorectal cancer and pancreatic cancer are used to illustrate the proposed methodology for multiple cross-sectional biomarkers. We further extend our classification method to …
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Decision-making under statistical uncertainty
… about the alternate distribution to improve finite-sample performance over the Hoeffding test. Although the Hoeffding test is universally optimal in an asymptotic sense, we show that it suffers from high bias and variance which leads to a poor performance over finite observation lengths. The …
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Highly Robust and Efficient Estimators of Multivariate Location and Covariance with Applications to Array Processing and Financial Portfolio Optimization
… demonstrates the diverse applicability and performance benefits of the Sq-estimator through theoretical analysis, empirical simulation, and the processing of real-world data. Through analytical and empirical means, the Sq-estimator is shown to generally provide higher maximum efficiency than …
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Statistical Inferences for Two-Component Semiparametric Location-Scale Mixture Models
… unknown component distributions. To assess the performance of SEMIMHDE, we conducted a series of simulation studies, evaluating its efficiency, robustness, and sensitivity to model misspecification compared to other parametric estimation methods. Finally, we applied SEMIMHDE to the Old Faithful …
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