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 90 for “"Robust estimation"”.
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A contribution to adaptive robust estimation
… the possibility of constructing an adaptive robust estimation procedure for the standard linear regression model when the disturbance vector deviated from normality, however, after the initial success in that field it seemed only appropriate that the approach be extended to robust location …
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Aircraft attitude determination using robust estimation
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1997.
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Modern portfolio optimization using robust estimation techniques
… in some cases. In this dissertation various robust estimation techniques are investigated in an attempt to minimise the influence that outliers may have on the estimation and to better estimate the input parameters for the Markowitz and Sharpe portfolio models. The main goal is to ascertain …
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Image Segmentation and Robust Estimation Using Parzen Windows
… for segmentation of real images. The density estimation framework is extended to model more structured images, e.g., those containing structures representable using local or global linear parametric models. Algorithms for robust parameter estimation and segmentation are given. Convergence …
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Robust estimation and failure detection for linear systems
Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1995.
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Simulating Statistical Power Curves with the Bootstrap and Robust Estimation
… known that classical statistical tests are not robust with respect to power and type II error. However, relatively little attention has been paid in the psychological literature to the effect that non-normality and outliers have on the power of a given statistical test (Wilcox, 1998). Robust …
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Robust estimation, regression and ranking with applications in portfolio optimization
… are only approximations of reality, many robust statistical methods have been developed to produce estimators that are robust against the deviation from the model assumptions. Unfortunately, these techniques have very high computational complexity that prevents their application to large …
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Optimal thruster selection with robust estimation for formation flying applications
… spacecraft with various types of actuators. The estimation process must be compatible to the mapper and have a fast yet robust fault detection algorithm. A robust fault detection system must be sensitive to failures without raising any false alarms. The linear program (LP) mapping system …
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Robust Estimation Techniques for the Cosmological Analysis of Large Scale Structure
… from the large-scale structure while being robust against one of the leading sources of systematic uncertainties: Redshift-space distortions. By means of a bias relation, we extend the matter counts-in-cells statistic for the first time to neutral hydrogen. Neutral hydrogen is particularly …
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Robust estimation and failure detection for reentry vehicle attitude control systems
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1998.
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Dynamic and robust estimation of risk and return in modern portfolio theory
… shift significantly to the left. Using dynamic estimation through the Kalman filter, it is noticed that the beta coefficients are not constant and that the resulting efficient frontiers significantly outperform the Sharpe model. In order to deal with the problem of outlying observations in the …
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Reliable Robotic Perception: From Outlier-Robust Estimation to Task-Aware Runtime Monitoring
… presents a comprehensive exploration of outlier-robust estimation algorithms, perception monitoring, and risk assessment to enhance the robustness and safety of robots and autonomous vehicles. The first part of the thesis focuses on geometric perception, which is the task of estimating geometric …
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Robust Estimation of the Cross-Sections of United States Wages and Stock Returns
The purpose of the study of the cross-section of U.S. stock returns is to examine how the relationship between returns and a conventional measure of risk differs across the conditional distribution of returns. The conditional quartile functions show that the relationship is not constant across the …
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A robust estimation method of location and scale with application in monitoring process variability
… proposes the development of a new method for robust estimation of location and scale, in data concentration step (C-step), of the most widely used method known as fast minimum covariance determinant (FMCD). This new method is as effective as FMCD and minimum vector variance (MVV) but with …
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Improved Estimators Under Squared Error Loss (Stein Estimator, Decision Theory, Empirical Bayes, Quadratic, Robust Estimation)
Much work on the James-Stein (1964) estimator or an improved estimator under squared error loss has been done with the assumption of independently identically distributed normal errors.
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Three Essays on Robust Estimation of Key Factors Underlying the Changes to the U.S. Income Distribution
… of three chapters and mainly focuses on the robust estimation of different important factors contributing changes to the U.S. income inequality over the last two decades. The primary objective is to precisely estimate different labor market outcomes when the behaviors of the tails of the …
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Robust Statistical Modeling In Functional Linear Regression
… distributions in the data. Consequently, robust statistical analysis remains an underdeveloped practice in this area. The primary objective of this dissertation is to enhance the utilization of robust methods for modeling functional linear regression by primarily focusing on robust …
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An Investigation into the Relationship Between Economic Growth, Energy Consumption, and the Environment: Evidence from Nigeria
… analysis, and ordinary least square (OLS for robust estimation) techniques to empirically investigate the impact of economic growth and energy consumption on the environment in Nigeria from 1980 to 2020. The results of cointegration demonstrate a long-term link between the model's input …
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Hybrid And Hierarchical Image Registration Techniques
… computational complexity, generality, and robustness. They can be broadly classified into two categories: intensity-based and feature-based methods. The primary drawback of the intensity-based approaches is that it may fail unless the two images are misaligned by a moderate difference in …
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