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Expository supplement II to the paper “Asymptotic expansions for theestimators of Lagrange multipliers and associated parameters by the maximum likelihood and weighted score methods”

机译：本文的存储库补充II“通过最大似然法和加权分数法对拉格朗日乘数和相关参数的估计进行渐近展开”

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小笠原春彦; Ogasawara Haruhiko;
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年度 2016
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1. Asymptotic expansions for the estimators of Lagrange multipliers and associated parameters by the maximum likelihood and weighted score methods [J] . Ogasawara Haruhiko Journal of Multivariate Analysis: An International Journal . 2016,第Null期

机译：最大似然法和加权得分法的拉格朗日乘数和相关参数的估计的渐近展开
2. Stochastic unit root processes: Maximum likelihood estimation, and new Lagrange multiplier and likelihood ratio tests [J] . Yoon Gawon Economic modelling . 2016,第JANaPTaB期

机译：随机单位根过程：最大似然估计以及新的拉格朗日乘数和似然比检验
3. Valid asymptotic expansions for the maximum likelihood estimator of the parameter of a stationary, Gaussian, strongly dependent process [J] . Lieberman O., Rousseau J., Zucker DM. The Annals of Statistics: An Official Journal of the Institute of Mathematical Statistics . 2003,第2期

机译：平稳的高斯过程的参数的最大似然估计的有效渐近展开
4. Improving the performance of weighted Lagrange-multiplier methods for nonlinear constrained optimization [C] . Wah, B.W., Tao Wang . 1997

机译：改进用于非线性约束优化的加权Lagrange乘子方法的性能
5. Parameter estimation of Copula using maximum likelihood estimation (MLE) method [D] . Khadka, Mahesh S. 2008

机译：使用最大似然估计（MLE）方法估计Copula的参数
6. Robustness and power of the maximum-likelihood-binomial and maximum-likelihood-score methods in multipoint linkage analysis of affected-sibship data. [O] . L Abel, B Müller-Myhsok 1998

机译：最大似然二项式和最大似然比方法的稳健性和功效在受影响的受助人数据的多点关联分析中。
7. Expository supplement I to the paper“ Asymptotic expansions for the estimators of Lagrange multipliers and associated parameters by the maximum likelihood and weighted score methods” [O] . Ogasawara Haruhiko 2015

机译：本文的论文补充I“通过最大似然和加权分数方法对拉格朗日乘子和相关参数的估计的渐近展开”

Expository supplement II to the paper “Asymptotic expansions for theestimators of Lagrange multipliers and associated parameters by the maximum likelihood and weighted score methods”

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