Discussion of Prediction, Estimation, and Attribution by Bradley Efron
成果类型：
Editorial Material
署名作者：
Friedman, Jerome; Hastie, Trevor; Tibshirani, Robert
署名单位：
Stanford University; Stanford University
刊物名称：
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
ISSN/ISSBN：
0162-1459
DOI：
10.1080/01621459.2020.1762617
发表日期：
2020
页码：
665-666
关键词：
摘要：
Professor Efron has presented us with a thought-provoking paper on the relationship between prediction, estimation, and attribution in the modern era of data science. While we appreciate many of his arguments, we see more of a continuum between the old and new methodology, and the opportunity for both to improve through their synergy.
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