2 citations · 3 across the 3 of their papers we have counts for
5 papers
Doubly Robust Estimation of Direct and Indirect Quantile Treatment Effects with Machine Learning
Yu-Chin Hsu, Martin Huber, Yu-Min Yen
We suggest double/debiased machine learning estimators of direct and indirect quantile treatment effects under a selection-on-observables assumption. This permits disentangling the…
Estimations of the Local Conditional Tail Average Treatment Effect
Le-Yu Chen, Yu-Min Yen
The conditional tail average treatment effect (CTATE) is defined as a difference between the conditional tail expectations of potential outcomes, which can capture heterogeneity an…
Testing Forecast Accuracy of Expectiles and Quantiles with the Extremal Consistent Loss Functions
Yu-Min Yen, Tso-Jung Yen
Forecast evaluations aim to choose an accurate forecast for making decisions by using loss functions. However, different loss functions often generate different ranking results for…
Grouped Variable Selection via Nested Spike and Slab Priors
Tso-Jung Yen, Yu-Min Yen
In this paper we study grouped variable selection problems by proposing a specified prior, called the nested spike and slab prior, to model collective behavior of regression coeffi…
A Note on Sparse Minimum Variance Portfolios and Coordinate-Wise Descent Algorithms
Yu-Min Yen
In this short report, we discuss how coordinate-wise descent algorithms can be used to solve minimum variance portfolio (MVP) problems in which the portfolio weights are constraine…