日時
2021年12月9日10:00 - 11:00 (JST)
講演者
下平 英寿 (京都大学 大学院情報学研究科 教授 / 理化学研究所 革新知能統合研究センター (AIP) 数理統計学チーム チームリーダー)
会場
via Zoom
言語
英語

Bootstrap resampling is quite useful for computing “confidence values” or “p-values” of trees and edges. However, they are biased and may lead to false positives (too many wrong discoveries) or false negatives (too few correct discoveries) depending on the “curvature” of the boundary surface of a hypothesis region in the data space. In addition, we face the issue of selection bias because we tend to use the dataset twice for hypothesis selection and its evaluation. I will explain these two types of bias and show methods to adjust the confidence values.

Reference

  1. Hidetoshi Shimodaira and Yoshikazu Terada, Selective Inference for Testing Trees and Edges in Phylogenetics, Front. Ecol. Evol., 24 (2019), doi: 10.3389/fevo.2019.00174