The residual adjustment function and weighted likelihood: a graphical interpretation of robustness of minimum disparity estimators.
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Publication:1608620
DOI10.1016/S0167-9473(01)00047-0zbMath1119.62302OpenAlexW2057412823MaRDI QIDQ1608620
Ayanendranath Basu, Bruce G. Lindsay, Chanseok Park
Publication date: 8 August 2002
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/s0167-9473(01)00047-0
Point estimation (62F10) Robustness and adaptive procedures (parametric inference) (62F35) Graphical methods in statistics (62A09)
Related Items (8)
Robust estimation for multivariate wrapped models ⋮ Robust fitting of mixtures of GLMs by weighted likelihood ⋮ Notes on Pearson residuals and weighted likelihood estimating equations ⋮ Some variants of minimum disparity estimation ⋮ A weighted strategy to handle likelihood uncertainty in Bayesian inference ⋮ Weighted likelihood estimation of multivariate location and scatter ⋮ Robust estimation for circular data ⋮ Discussion of: ``The power of monitoring: how to make the most of a contaminated multivariate sample
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- Minimum Hellinger Distance Estimation for the Analysis of Count Data
- Weighted Likelihood Equations with Bootstrap Root Search
- The generalized kullback-leibler divergence and robust inference
- Robust minimum distance inference based on combined distances
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