期刊
AMERICAN STATISTICIAN
卷 56, 期 1, 页码 29-38出版社
AMER STATISTICAL ASSOC
DOI: 10.1198/000313002753631330
关键词
asymptotic variance; central limit theorem; estimating equations; large-sample inference; maple; M-estimator
Since the seminal papers by Huber in the 1960s, M-estimation methods (also known as estimating equation methods) have been increasingly important for asymptotic analysis and approximate inference. This article illustrates the breadth and generality of the M-estimation approach, thereby facilitating its use in practice and in the classroom as a unifying approach to the study of large-sample inference.
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