5 papers
Invariant quantile regression for heterogeneous environments
Bo Fu, Dandan Jiang
In this paper, we propose an invariant quantile regression (IQR) framework specifically designed for multi-environment datasets, which captures the invariance across different envi…
Transfer learning for high-dimensional Factor-augmented sparse linear model
Bo Fu, Dandan Jiang
In this paper, we study transfer learning for high-dimensional factor-augmented sparse linear models, motivated by applications in economics and finance where strongly correlated p…
Unifiedly Efficient Inference on All-Dimensional Targets for Large-Scale GLMs
Bo Fu, Dandan Jiang
The scalability of Generalized Linear Models (GLMs) for large-scale, high-dimensional data often forces a trade-off between computational feasibility and statistical accuracy, part…
Accelerating Randomized Algorithms for Low-Rank Matrix Approximation
Dandan Jiang, Bo Fu, Weiwei Xu
Randomized algorithms are overwhelming methods for low-rank approximation that can alleviate the computational expenditure with great reliability compared to deterministic algorith…
Fair coins tend to land on the same side they started: Evidence from 350,757 flips
František Bartoš, Alexandra Sarafoglou, Henrik R. Godmann +47
Many people have flipped coins but few have stopped to ponder the statistical and physical intricacies of the process. We collected coin flips to test the counterintuit…