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Showing 1 to 4 of 4 for “"Minimum Hellinger Distance"”.

  1. Robust Efficient Estimation of Semiparametric Covariate Models based on Minimum Hellinger Distance

    … class of 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 …

    calgary Repository record for Robust Efficient Estimation of Semiparametric Covariate Models based on Minimum Hellinger Distance (opens in a new tab)

  2. 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 …

    vt Repository record for A Differential Geometry-Based Algorithm for Solving the Minimum Hellinger Distance Estimator (opens in a new tab)

  3. Three Statistical Problems With Imprecisely or Incompletely Observed Data

    … The third 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.

    uiuc Repository record for Three Statistical Problems With Imprecisely or Incompletely Observed Data (opens in a new tab)

  4. Statistical Inferences for Two-Component Semiparametric Location-Scale Mixture Models

    … limitations, 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 …

    calgary Repository record for Statistical Inferences for Two-Component Semiparametric Location-Scale Mixture Models (opens in a new tab)