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Showing 1 to 6 of 6 for “"Nonparametric Maximum Likelihood"”.
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Order Theory and Nonparametric Analysis for Interval Censored Data
… this characterization to provide bounds on the maximum number of minimal covers for an interval order with a given number of maximal antichains. Finally, we determine nonparametric maximum likelihood estimators (NPMLE) of the cumulative distribution function (CDF) on the set of maximal …
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Nonparametric Survival Analysis under Shape Restrictions
… associated with a parametric model, we resort to nonparametric methods for estimating a function. Although other nonparametric approaches, such as Kaplan-Meier, kernel-based, and roughness penalty methods, are popular tools for solving function estimation problems, they suffer from some …
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Maximum likelihood estimation of a multivariate log-concave density
… to calibrate, especially for multivariate data (nonparametric smoothing methods). We propose an alternative approach using maximum likelihood under a qualitative assumption on the shape of the density, specifically log-concavity. The class of log-concave densities includes many common parametric …
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Efficient learning of temporal dynamics with first-order methods
… the following aspects: • how to enable efficient nonparametric learning for large datasets? • how to learn positive-valued intensity functions for point processes? • how to learn from complex systems with implicit likelihood? • how to learn from aggregated observations of temporal dynamics? Our …
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Mixture Modeling for Multivariate Observations
In this thesis, nonparametric multivariate density estimation is studied. The kernel density estimation predominately used in the literature is known to be less than ideal in both computation and estimation efficiency, especially for multivariate observations. Mixtures, particularly nonparametric …
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Problems in large-scale estimation
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms