TY - JOUR
T1 - Minimum disparity estimation
T2 - Improved efficiency through inlier modification
AU - Mandal, Abhijit
AU - Basu, Ayanendranath
PY - 2013/4/2
Y1 - 2013/4/2
N2 - Inference procedures based on density based minimum distance techniques provide attractive alternatives to likelihood based methods for the statistician. The minimum disparity estimators are asymptotically efficient under the model; several members of this family also have strong robustness properties under model misspecification. Similarly, the disparity difference tests have the same asymptotic null distribution as the likelihood ratio test but are often superior than the latter in terms of robustness properties. However, many disparities put large weights on the inliers, cells with fewer data than expected under the model, which appears to be responsible for a somewhat poor efficiency of the corresponding methods in small samples. Here we consider several techniques which control the inliers without significantly affecting the robustness properties of the estimators and the corresponding tests. Extensive numerical studies involving simulated data illustrate the performance of the methods.
AB - Inference procedures based on density based minimum distance techniques provide attractive alternatives to likelihood based methods for the statistician. The minimum disparity estimators are asymptotically efficient under the model; several members of this family also have strong robustness properties under model misspecification. Similarly, the disparity difference tests have the same asymptotic null distribution as the likelihood ratio test but are often superior than the latter in terms of robustness properties. However, many disparities put large weights on the inliers, cells with fewer data than expected under the model, which appears to be responsible for a somewhat poor efficiency of the corresponding methods in small samples. Here we consider several techniques which control the inliers without significantly affecting the robustness properties of the estimators and the corresponding tests. Extensive numerical studies involving simulated data illustrate the performance of the methods.
KW - Disparity Inliers Power divergence Small sample studies
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U2 - 10.1016/j.csda.2013.02.030
DO - 10.1016/j.csda.2013.02.030
M3 - Article
AN - SCOPUS:84875418772
VL - 64
SP - 71
EP - 86
JO - Computational Statistics and Data Analysis
JF - Computational Statistics and Data Analysis
SN - 0167-9473
ER -