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Maximum Likelihood Estimate for Logistic Errors-in-Variables Regression Models.

机译：Logistic变量回归模型的极大似然估计。

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摘要

Maximum likelihood estimates for errors-in-variables models are not always root-N consistent. We provide an example of this for logistic regression. (Author)

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作者
Carroll, R. J.;
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年度 1983
页码 1-12
总页数 12
原文格式 PDF
正文语种 eng
中图分类工业技术;
关键词
Probability; Regression analysis; Logistics planning; Theorems; Logistic regression; Binary regression; Maximum likelihood estimates;

机译：概率;回归分析;物流规划;定理;逻辑回归;二元回归;最大似然估计;

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1. Straight line fitting and predictions: on a marginal likelihood approach to linear regression and errors-in-variables models. [J] . Christiansen. B Journal of Climate . 2014,第5期

机译：直线拟合和预测：采用边际似然法进行线性回归和变量误差模型。
2. Effects of Random Sampling Methods on Maximum Likelihood Estimates of a Simple Logistic Regression Model [J] . Oshada Senaweera, Prasanna S. Haddela, Gayan Dharmarathne American Journal of Applied Mathematics and Statistics . 2021,第1期

机译：随机抽样方法对简单逻辑回归模型的最大似然估计的影响
3. The Maximum Likelihood Estimates with Wrong Logistic Regression Model and Covariate Assumptions are Violated [J] . Nuri H. Salem Badi, Mohamed M. Shakandli American Journal of Mathematics and Statistics . 2021,第1期

机译：违反了错误的逻辑回归模型和协变量假设的最大可能性估计
4. The Effect of High Leverage Points on the Maximum Estimated Likelihood for Separation in Logistic Regression [C] . Syaiba Balqish Ariffin, Habshah Midi, Jayanthi Arasan, ISM International Statistical Conference . 2015

机译：高杠杆点对逻辑回归分离的最大估计可能性的影响
5. New Methods for Solving Maximum Likelihood Estimating Equations of Logistic and Probit Regression Models [D] . Wang, Haoyu 2011

机译：Logistic和Probit回归模型的最大似然估计方程的求解新方法
6. On the correspondence of deviances and maximum-likelihood and interval estimates from log-linear to logistic regression modelling [O] . W. Jing, M. Papathomas 2020

机译：从线性回归到逻辑回归建模的偏差和最大似然和区间估计的对应关系
7. Logistic Regression Using Maximum Estimated Likelihood Description [O] . Original S-plus, Peter J. Rousseeuw, Andreas Christmann, 2014

机译：使用最大估计似然描述的Logistic回归

Maximum Likelihood Estimate for Logistic Errors-in-Variables Regression Models.

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