具有未知模式試驗誤差之群組試驗的穩健參數估計法(2/2)

Project Details

Description

Group testing plays an important role in estimating the prevalence of a rare disease or the proportion of a particular trait. However, test errors often occur and the error rates may vary with the group size. In this project, we will build a new robust prevalence estimator based on γ‐divergence. The minimum γ‐divergence estimator is expected to be consistent without modeling the test error rates, and also reduces the variation by not involving additional parameters in the test error mechanism. We will investigate the asymptotic properties of this prevalence estimation, and study the corresponding optimal design problems. We will also compare the finite sample performance of the obtained designs and that of some commonly-used group testing designs.
StatusFinished
Effective start/end date1/08/2231/08/23

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):

  • SDG 11 - Sustainable Cities and Communities
  • SDG 17 - Partnerships for the Goals

Keywords

  • γ‐divergence
  • group testing
  • prevalence
  • robust estimation
  • sensitivity
  • specificity

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