Jiawei Yao

Jiawei Yao
Are you Jiawei Yao?

Claim your profile, edit publications, add additional information:

Contact Details

Name
Jiawei Yao
Affiliation
Location

Pubs By Year

Pub Categories

 
Statistics - Methodology (3)
 
Statistics - Theory (2)
 
Statistics - Machine Learning (2)
 
Mathematics - Statistics (2)
 
Statistics - Applications (1)

Publications Authored By Jiawei Yao

We consider forecasting a single time series using high-dimensional predictors in the presence of a possible nonlinear forecast function. The sufficient forecasting (Fan et al., 2016) used sliced inverse regression to estimate lower-dimensional sufficient indices for nonparametric forecasting using factor models. Read More

We consider forecasting a single time series when there is a large number of predictors and a possible nonlinear effect. The dimensionality was first reduced via a high-dimensional (approximate) factor model implemented by the principal component analysis. Using the extracted factors, we develop a novel forecasting method called the sufficient forecasting, which provides a set of sufficient predictive indices, inferred from high-dimensional predictors, to deliver additional predictive power. Read More

We propose a novel technique to boost the power of testing a high-dimensional vector $H:\btheta=0$ against sparse alternatives where the null hypothesis is violated only by a couple of components. Existing tests based on quadratic forms such as the Wald statistic often suffer from low powers due to the accumulation of errors in estimating high-dimensional parameters. More powerful tests for sparse alternatives such as thresholding and extreme-value tests, on the other hand, require either stringent conditions or bootstrap to derive the null distribution and often suffer from size distortions due to the slow convergence. Read More