利用R包autovi与Shiny应用autovi.web自动评估残差图 / Automated Residual Plot Assessment With the R Package autovi and the Shiny Application autovi.web
1️⃣ 一句话总结
该论文介绍了一个名为autovi的R包及其配套的Shiny网页应用,能够利用计算机视觉模型自动分析残差图、输出视觉信号强度并给出辅助信息,从而替代传统费时且主观的人工评估,提升线性模型诊断的效率和一致性。
Visual assessment of residual plots is a common approach for diagnosing linear models, but it relies on manual evaluation, which does not scale well and can lead to inconsistent decisions across analysts. The lineup protocol, which embeds the observed plot among null plots, can reduce subjectivity but requires even more human effort. In today's data-driven world, such tasks are well suited for automation. We present a new R package that uses a computer vision model to automate the evaluation of residual plots. An accompanying Shiny application is provided for ease of use. Given a sample of residuals, the model predicts a visual signal strength (VSS) and offers supporting information to help analysts assess model fit.
利用R包autovi与Shiny应用autovi.web自动评估残差图 / Automated Residual Plot Assessment With the R Package autovi and the Shiny Application autovi.web
该论文介绍了一个名为autovi的R包及其配套的Shiny网页应用,能够利用计算机视觉模型自动分析残差图、输出视觉信号强度并给出辅助信息,从而替代传统费时且主观的人工评估,提升线性模型诊断的效率和一致性。
源自 arXiv: 2606.24236