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Showing 1 to 8 of 8 for “"M-estimator"”.
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Robust speech filtering in impulsive noise environments
… is identified by means of a robust nonlinear estimator known as the Schweppe-type Huber GM-estimator. Simulation results are presented that demonstrate the effectiveness of the filter. Another contribution of the work is the development of a robust version of the Kalman filter based on the …
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Comparing Predictive Values of Two diagnostic tests
… by series of logistic regressions and derive estimator and test statistics based on likelihood method. However, it is often the case that gold standard is not observed on every patient because it may be invasive. If we only consider those who have observed gold standard, the estimator may not …
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Essays in semiparametric and nonparametric estimation with application to growth accounting
… are established for the problems. Using an M-estimator based on the efficient score, the feasible form of the semiparametric efficient estimators is worked out for several explicit assumptions regarding the degree of dependence between the predetermined variables and the disturbances of the …
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Robust methods for analyzing multivariate responses with application to time-course data
… well-known Rao's score test based on Huber's M estimator. The test statistic is asymptotically normal, and the simulation study suggests that the test has higher power in the presence of outliers than the score test based on the least squares. In the second part of the dissertation, we propose a …
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Iterative Memoryless Non-linear Estimators of Correlation for Complex-Valued Gaussian Processes that Exhibit Robustness to Impulsive Noise
… which often occurs in practice, can bias this estimator, rendering classical time series analysis methods ineffective. This work examines the robustness of two estimators of correlation based on memoryless nonlinear functions of observations, the Phase-Phase Correlator (PPC) and the Median- …
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Automated Detection of Surface Defects on Barked Hardwood Logs and Stems Using 3-D Laser Scanned Data
… non-additive errors, a new robust generalized M-estimator has been developed that is different from the ones proposed in the statistical literature for linear regression. Circle fitting is performed by standardizing the residuals via scale estimates calculated by means of projection statistics …
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Robust Wireless Communications with Applications to Reconfigurable Intelligent Surfaces
… I designed a Bayesian minimum mean square error estimator for decoding high-dimensional JSCC codes achieving 99.96% accuracy. With the recent introduction of electromagnetic reconfigurable intelligent surfaces (RIS), a paradigm shift is currently taking place in the world of wireless …
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Symmetry and Other Structures: Topics in Nonparametric Regression
… a fixed η > 0 grows exponentially in d for all estimators fˆ_n in many usual problem contexts. To overcome this, we often seek to find structure within the function f we can exploit. The two main structures that have been previously studied are Sparsity, where f depends only on s < d of the …