4 papers
From Vector Autoregressions to AI-based Time Series Forecasting: A Review
Likai Chen, Weining Wang
Forecasting is a central goal of time-series analysis. This review centers on three major developments in recent AI-based time-series forecasting: transformers, large pretrained mo…
Estimation of High-dimensional Nonlinear Vector Autoregressive Models
Yuefeng Han, Likai Chen, Wei Biao Wu
High-dimensional vector autoregressive (VAR) models have numerous applications in fields such as econometrics, biology, climatology, among others. While prior research has mainly f…
Online simultaneous inference for quantiles via smoothed stochastic gradient descent
Likai Chen, Georg Keilbar, Wei Biao Wu
This paper considers the estimation of quantiles via a smoothed version of the stochastic gradient descent (SGD) algorithm. By smoothing the score function with a bandwidth tied to…
Central Limit Theorems for Stochastic Gradient Descent Quantile Estimators
Ziyang Wei, Jiaqi Li, Likai Chen +1
This paper develops asymptotic theory for quantile estimation via stochastic gradient descent (SGD) with a constant learning rate. The quantile loss function is neither smooth nor…