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Updated: Jun 11, 2025

A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM
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A Workflow for Lipid Nanoparticle LNP Formulation Optimization using Designed Mixture-Process Experiments and Self-Validated Ensemble Models SVEM

Published on: August 18, 2023

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一个统一的EM框架用于估计和推断正常的ogive项目响应模型

Xiangbin Meng1, Gongjun Xu2

  • 1KLAS, Key Laboratory of Big Data Analysis of Jilin Province, School of Mathematics and Statistics, Northeast Normal University, Changchun, China.

The British journal of mathematical and statistical psychology
|October 10, 2024
PubMed
概括

本研究介绍了一种高效的预期最大化 (EM) 算法,用于在物品响应理论 (IRT) 中估计正常导向 (NO) 模型. 新方法提高了教育和心理测量的计算效率和可靠性.

关键词:
预期-最大化算法项目响应理论是物品响应理论.通常的Ogive模型.参数估计的参数估计.

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