Consistency and Asymptotic Normality of the Minimum Logit Chi-Squared Estimator When the Number of Design Points is Large
Davis, Linda June
Ann. Statist., Tome 13 (1985) no. 1, p. 947-957 / Harvested from Project Euclid
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When the number of design points goes to infinity, we show that the minimum logit chi-squared estimator of the parameter in a linear logistic regression model for binomial response data is asymptotically normal. We also give conditions under which it is consistent.
Publié le : 1985-09-14
Classification:  Binomial response data,  logistic regression model,  62F12,  62F10 
@article{1176349648,
     author = {Davis, Linda June},
     title = {Consistency and Asymptotic Normality of the Minimum Logit Chi-Squared Estimator When the Number of Design Points is Large},
     journal = {Ann. Statist.},
     volume = {13},
     number = {1},
     year = {1985},
     pages = { 947-957},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1176349648}
}

Davis, Linda June. Consistency and Asymptotic Normality of the Minimum Logit Chi-Squared Estimator When the Number of Design Points is Large. Ann. Statist., Tome 13 (1985) no. 1, pp.  947-957. http://gdmltest.u-ga.fr/item/1176349648/