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 896 for “"estimators"”.
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Realised volatility estimators
… an investigation into realised volatility (RV) estimators. Here, RV is defined as the sum-of-squared-returns (SSR) and is a proxy for integrated volatility (IV), which is unobservable. The study focuses on a subset of the universe of RV estimators. We examine three categories of estimators: …
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Finite Population Quantile Estimators
… on quantile regression, two new quantile based estimators are introduced and some of their properties are examined. A proof for consistency of the marginal quantile estimator and for Bahadur-Expansion validity of the conditional quantile estimator is included. Then, a look by means of the …
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Simulation study of frequency estimators
… performance compared to some Maximum Likelihood estimators available. In the static fading channel, diversity technique can be easily incorporated to improve the performance of the proposed frequency estimator.
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Kernel Estimators in Complex Data Analysis
Kernel estimators, including kernel density estimators and kernel regression estimators, have drawn great research interests in terms of both theoretical studies and applications since invention, due to their easy interpretation and flexibility to model data with complicated density …
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Selecting tuning parameters in minimum distance estimators
Many minimum distance estimators have the potential to provide parameter estimates which are both robust and efficient and yet, despite these highly desirable theoretical properties, they are rarely used in practice. This is because the performance of these estimators is rarely guaranteed per se …
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A study of estimators in linear models
This thesis is a study of Estimators, particularly in Linear Models. The newest technology of Bootstrap Methodology is employed in the estimation procedure. We present a survey of the Bootstrap Methodology in the beginning and move on to some serious problems in Linear Model estimation procedure. …
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Sequential nonparametric estimation via Hermite series estimators
… settings based on Hermite series density estimators. In the univariate context we apply Hermite series based distribution function estimators to sequential cumulative distribution function estimation. These distribution function estimators are particularly useful because they allow the …
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Learning Refinement Cost Estimators for Bilevel Planning
Bilevel planning is an effective approach for solving complex task and motion planning (TAMP) problems with continuous state and action spaces, that involves first searching for a high-level abstract plan and then refining it into a sequence of lowlevel actions. Although the low-level refinement …
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On error estimators in finite element analysis
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2000.
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Equivariant estimators and a special group structure
… G, we characterize the form of G-equivariant estimators. In fact, corresponding to each G-equivariant estimator is an appropriate G-invariant function and conversely. In the course of characterizing the G-equivariant estimators, we obtain two maximal invariant functions. Some properties of …
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Bayesian Estimators, Error Bounds, and Applications to Imaging
… us in evaluating the performance of sub-optimal estimators. A widely used lower bound on the MMSE is the Ziv-Zakai lower bound, which bounds the MMSE via the minimum probability of error (MPE) of a binary hypothesis testing problem. Extensions of the Ziv-Zakai lower bound and some computationally …
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Transformers as Empirical Bayes Estimators The Poisson Model
… transformers are implementing Robbin’s or NPMLE estimators in context.
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A comparison of digital beacon receiver frequency estimators
… measurements provided by one of two frequency estimators. One of the frequency estimation algorithms, a refinement of the DFT-automatic frequency control technique, uses the Chirp-Transform algorithm in its aim for the maximum likelihood estimate of frequency and power. The averaged periodogram …
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Robust Analysis of M-Estimators of Nonlinear Models
… analysis of the tolerance of nonlinear model estimators to deviations from assumptions and normality. We focus on analyzing the robustness properties of M-estimators of nonlinear models by studying the effects of deviations from assumptions and normality on these estimators. We discuss St. …
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Functional Brain Connectivity Estimators: Understanding and Developing New Methodologies
The objective of the proposed research is to develop a framework to unify the different methodologies that are used for constructing a specific part of the brain functional networks (i.e., functional connectivity or the relationship between different parts of the functional networks). In addition, …
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Investigating 'optimal' kriging variance estimation :analytic and bootstrap estimators
Kriging is a widely used group of techniques for predicting unobserved responses at specified locations using a set of observations obtained from known locations. Kriging predictors are best linear unbiased predictors (BLUPs) and the precision of predictions obtained from them are assessed by the …
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Conditional dependence via Shannon capacity: axioms, estimators and applications
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2017-02-28 without embargo terms
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Techniques for Approximating Optimal Linear Estimators of Multidimensional Data
This framework is used to create estimators for four distinct applications. First, we create a blind estimator for hyperspectral and multispectral data that improves the average channel signal-to-noise ratio of a 0 dB observation by 16 dB. Second, we consider the problem of estimating a time-series …
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