A PARADOXICAL EFFECT OF NUISANCE PARAMETERS ON EFFICIENCY OF ESTIMATORS

スポンサーリンク

概要

• 論文の詳細を見る

• This paper is concerned with parameter estimation in the presence of nuisance parameters. Usually, an estimator with known nuisance parameters is better than that with unknown nuisance parameters in reference to the asymptotic variance. However, it has been noted that the opposite can occur in some situations. In this paper we elucidate when and how this phenomenon occurs using the orthogonal decomposition of estimating functions. Most of the examples of this phenomenon are found in the case of semiparametric models, but this phenomenon can also occur in parametric models. As an example, we consider the estimation of the dispersion parameter in a generalized linear model.

• 一般社団法人日本統計学会の論文

著者

• Henmi Masayuki

  Department Of Statistical Science The Graduate University For Advanced Studies

関連論文

• A PARADOXICAL EFFECT OF NUISANCE PARAMETERS ON EFFICIENCY OF ESTIMATORS

スポンサーリンク