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 12 of 12 for “"Hellinger distance"”.
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Robust Efficient Estimation of Semiparametric Covariate Models based on Minimum Hellinger Distance
… models. For this purpose, we employ the minimum distance approach which in general is automatically robust with respect to the stability of the quantity being estimated. In particular, the minimum Hellinger distance estimation (MHDE) introduced by Beran (1977) for parametric models produces …
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A Differential Geometry-Based Algorithm for Solving the Minimum Hellinger Distance Estimator
… and efficiency. This thesis examines the Minimum Hellinger Distance Estimator (MHDE), which is known to have desirable robustness properties as well as desirable efficiency properties. This thesis confirms that the MHDE is simultaneously robust against outliers and asymptotically efficient in the …
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Mean Hellinger Distance as an Error Criterion in Univariate and Multivariate Kernel Density Estimation
… this study we define a weighted version of the Hellinger distance for multivariate densities and show that it has an asymptotic form, which is one-fourth the asymptotic MISE under weak smoothness conditions on the multivariate density f. In addition the proposed criteria give rise to a new …
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Statistical Inferences for Two-Component Semiparametric Location-Scale Mixture Models
… this thesis explores the use of Minimum Hellinger Distance Estimation (MHDE), a robust alternative estimation which offers a balance between efficiency and robustness, meaning that while MHDE may not be as efficient as MLE in perfectly specified models (i.e., when the model exactly fits …
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Density Estimation for Robust Financial Econometrics
… robust parametric inference which minimizes the Hellinger distance between two nonparametrically smoothed density estimates: the simulated model density and corresponding observed density. This approach generalizes work of Beran (1977) and Basu and Lindsay (1994) so that dependent data and …
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Three Statistical Problems With Imprecisely or Incompletely Observed Data
… study is concerned with an approximate minimum Hellinger distance estimator (AMHDE) under appropriate grouping of data from a continuous variable. The estimator is shown to be asymptotically normal with good efficiency and robustness.
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Comparative Analysis of Discrimination and Calibration Accuracy of Discrete Survival, Random Forests, and Neural Networks in Health-Related Survival Prediction Models
… cancer. The discrete-time random forest with hellinger distance had the overall prediction performance on the age at first alcohol intake. The discrete-time survival model outperformed the rest of the models in predicting survival of bleeding trauma patients from the CRASH-2 data .
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Semiparametric mixture models
… In Part I, we construct the minimum profile Hellinger distance (MPHD) estimator for a class of semiparametric mixture models where one component has known distribution with possibly unknown parameters while the other component density and the mixing proportion are unknown. Such semiparametric …
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Effects of NAL-R amplification on consonant speech perception in hearing-impaired listeners
… a large variety of tokens. A method based on the Hellinger Distance (HD) was introduced that enabled comparison of rows of confusion matrices and to calculate distances between responses. With this method, the highly individual problems of the 15.1% of the TEPs were further investigated and …
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Topics in shape-constrained inference
… rates of convergence (with respect to squared Hellinger distance or Kullback-Leibler divergence) that are strictly faster than the global minimax convergence rate. We illustrate three different types of adaptive behaviour in dimensions 2 and 3 through sharp oracle inequalities. Our approach …
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Feature selection for cancer classification using microarray gene expression data
… classification problem, the Bhattacharyya distance is proposed to measure the dissimilarity in gene expression levels between the two groups. For any particular gene, we calculate the Bhattacharrya distance between the two groups based on the expression levels of that particular gene. We …
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Study on impacts of aviation emissions and related dynamics and chemistry
… observations in the region of UTLS. Using the Hellinger distance, vertical profiles of probability density functions (PDFs) of chemical tracers simulated by the MOZART-3.1 are quantitatively compared with satellite data from the Microwave Limb Sounder (MLS) instrument in the tropopause relative …