1 citations · 1 across the 6 of their papers we have counts for
6 papers
Varying coefficient model for longitudinal data with informative observation times
Yu Gu, Yangjianchen Xu, Peijun Sang
Varying coefficient models are widely used to characterize dynamic associations between longitudinal outcomes and covariates. Existing work on varying coefficient models, however,…
Debiased Inference for High-Dimensional Regression Models Based on Profile M-Estimation
Yuhao Deng, Yi Wang, Yu Gu +2
Debiased inference for high-dimensional regression models has received substantial recent attention to ensure regularized estimators have valid inference. Many existing methods foc…
Distribution-free inference for LightGBM and GLM with Tweedie loss
Alokesh Manna, Aditya Vikram Sett, Dipak K. Dey +3
Prediction uncertainty quantification is a key research topic in recent years scientific and business problems. In insurance industries (\cite{parodi2023pricing}), assessing the ra…
Interval Estimation of Coefficients in Penalized Regression Models of Insurance Data
Alokesh Manna, Zijian Huang, Dipak K. Dey +2
The Tweedie exponential dispersion family is a popular choice among many to model insurance losses that consist of zero-inflated semicontinuous data. In such data, it is often impo…
fastkqr: A Fast Algorithm for Kernel Quantile Regression
Qian Tang, Yuwen Gu, Boxiang Wang
Quantile regression is a powerful tool for robust and heterogeneous learning that has seen applications in a diverse range of applied areas. However, its broader application is oft…
Dispersion Modeling in Zero-inflated Tweedie Models with Applications to Insurance Claim Data Analysis
Yuwen Gu
The Tweedie generalized linear models are commonly applied in the insurance industry to analyze semicontinuous claim data. For better prediction of the aggregated claim size, the m…