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The robustness of the quasilikelihood estimator
Author(s) -
Lee Y.,
Nelder John A.
Publication year - 1999
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.2307/3315642
Subject(s) - estimator , robustness (evolution) , maximum likelihood , m estimator , likelihood function , mathematics , minimum variance unbiased estimator , statistics , cumulant , quadratic equation , econometrics , biochemistry , chemistry , geometry , gene
Abstract The quasilikelihood estimator is widely used in data analysis where a likelihood is not available. We illustrate that with a given variance function it is not only conservative, in minimizing a maximum risk, but also robust against a possible misspecification of either the likelihood or cumulants of the model. In examples it is compared with estimators based on maximum likelihood and quadratic estimating functions.