SGDinference {SGDinference}

SGDinference

Description

The 'SGDinference' package provides estimation and inference methods for large-scale mean and quantile regression models via stochastic (sub-)gradient descent (S-subGD) algorithms. The inference procedure handles cross-sectional data sequentially: (i) updating the parameter estimate with each incoming "new observation", (ii) aggregating it as a Polyak-Ruppert average, and (iii) computing an asymptotically pivotal statistic for inference through random scaling.

Author(s)

Sokbae Lee, Yuan Liao, Myung Hwan Seo, Youngki Shin