Our paper A Pipeline for Variable Selection and False Discovery Rate Control with an Application in Labor Economics has been accepted for presentation at the 2020 Annual Congress of the Swiss Society of Economics and Statistics. Congratulations to Sophie-Charlotte Klose! Very impressive!
Author Archives: LedererLab
Ridge Regression Without Tuning Parameters
We have uploaded a paper on tuning-free ridge regression here. Well done, Shih-Ting and Fang!
High-dimensional Inference
Our paper Inference for high-dimensional instrumental variables regression has been accepted by the Journal of Econometrics. Wonderful work from my co-authors Jing (faculty at University of Washington) and David (former student at University of Washington)! ✈
Personalized Medicine
We have uploaded a new paper on prediction in personalized medicine here. Congratulations to Shih-Ting and Yannick, who are the student authors of this paper!
Mike completed Master’s thesis
Mike Laszkiewicz has completed his Master’s thesis about Graphical Models. Congratulations! 🎓
Tuning Parameters in Logistic Regression
Our paper “Tuning parameter calibration for
l1-regularized logistic regression” has now been published in the Journal of Statistical Planning and Inference.
Yunqi and Rui passed final exams
Yunqi Bu and Rui Zhuang passed their final doctoral exams and thereby earned their PhDs from University of Washington. Congratulations! 👩🎓👩🎓
FDR Control in Regression and Graphical Modeling
Prediction Guarantees for the TREX
Our paper “Prediction error bounds for linear regression with the TREX” has now been published in Test.
