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Updated: Jun 27, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

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假设薄伪造测试的速度双强度的双机器学习估计器的假设薄伪造测试

Lin Liu1, Rajarshi Mukherjee2, James M Robins3

  • 1Institute of Natural Sciences, MOE-LSC, School of Mathematical Sciences, CMA-Shanghai, SJTU-Yale Joint Center for Biostatistics and Data Science, Shanghai Jiao Tong University; Shanghai Artificial Intelligence Laboratory.

Journal of econometrics
|April 29, 2024
PubMed
概括

本研究引入了对双强度 (DR) 函数的"率双强度"的假设薄弱测试,这对于经济学和生物统计学至关重要. 这些测试可以伪造依赖于限制性假设的沃尔德置信区间的证明.

关键词:
具有双重强度的功能函数计量经济学和机器学习高级U-统计的高阶统计.

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