A note on robust estimation in logistic regression model
Discussiones Mathematicae. Probability and Statistics, Tome 36 (2016) no. 1-2, pp. 43-51
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Computationally attractive Fisher consistent robust estimation methods based on adaptive explanatory variables trimming are proposed for the logistic regression model. Results of a Monte Carlo experiment and a real data analysis show its good behavior for moderate sample sizes. The method is applicable when some distributional information about explanatory variables is available.
Keywords:
logistic model, robust estimation
@article{DMPS_2016_36_1-2_a2,
author = {Bednarski, Tadeusz},
title = {A note on robust estimation in logistic regression model},
journal = {Discussiones Mathematicae. Probability and Statistics},
pages = {43--51},
publisher = {mathdoc},
volume = {36},
number = {1-2},
year = {2016},
language = {en},
url = {http://geodesic.mathdoc.fr/item/DMPS_2016_36_1-2_a2/}
}
TY - JOUR AU - Bednarski, Tadeusz TI - A note on robust estimation in logistic regression model JO - Discussiones Mathematicae. Probability and Statistics PY - 2016 SP - 43 EP - 51 VL - 36 IS - 1-2 PB - mathdoc UR - http://geodesic.mathdoc.fr/item/DMPS_2016_36_1-2_a2/ LA - en ID - DMPS_2016_36_1-2_a2 ER -
Bednarski, Tadeusz. A note on robust estimation in logistic regression model. Discussiones Mathematicae. Probability and Statistics, Tome 36 (2016) no. 1-2, pp. 43-51. http://geodesic.mathdoc.fr/item/DMPS_2016_36_1-2_a2/