A5102808653- Statistical Methods and Bayesian Inference
- Statistical Methods and Inference
- Landslides and related hazards
- Cryospheric studies and observations
- Remote Sensing and Land Use
- Advanced Statistical Methods and Models
- Climate change and permafrost
- Bayesian Methods and Mixture Models
- Distributed Sensor Networks and Detection Algorithms
Nantong University
2015-2021
Distributed and parallel computing is becoming more important with the availability of extremely large data sets. In this article, we consider problem for high-dimensional linear quantile regression. We work under assumption that coefficients in regression model are sparse; therefore, a LASSO penalty naturally used estimation. first extend debiasing procedure, which previously proposed smooth parametric models to The technical challenges include dealing nondifferentiability loss function...
In many data analytic problems, repeated measurements with a large number of covariates are collected and conditional quantile modeling for such correlated often significant interest, especially in medical applications. We propose quadratic inference functions based approach to take into account the correlations within clusters use smoothing make objective function amenable computation. show that asymptotic properties estimators same whether or not is applied, established “diverging p, n”...