Research
Research Fields
Data science, Statistics, Time series
Current Topics
High-dimensional statistics and its around, such as:
Variable selection and FDR control
Estimation and inference for sparse and/or low-rank models
Estimation and inference for non-sparse models
Applications with a large data set in economics and finance
Publications
Dai, R., Y. Uematsu and Y. Matsuda (2024). "Estimation of large covariance matrices with mixed factor structures," Econometrics Journal, 27, 62-83.
Uematsu, Y. and T. Yamagata (2023). "Inference in sparsity-induced weak factor models," Journal of Business & Economic Statistics, 41, 126-139. (Working Paper)
Uematsu, Y. and T. Yamagata (2023). "Estimation of sparsity-induced weak factor models," Journal of Business & Economic Statistics, 41, 213-227. (Working Paper, Core part of R code, Slides on sWF models)
Fan, Y., J. Lv, M. Sharifvaghefi and Y. Uematsu (2020). "IPAD: stable interpretable forecasting with knockoffs inference," Journal of the American Statistical Association, 115, 1822-1834. (Supplementary materials are available from the link.)
Uematsu, Y., Y. Fan, K. Chen, J. Lv and W. Lin (2019). "SOFAR: large-scale association network learning," IEEE Transactions on Information Theory, 65, 4924-4939. (Supplementary materials are available from the link.)
Uematsu, Y. and S. Tanaka (2019). "High-dimensional macroeconomic forecasting and variable selection via penalized regression," Econometrics Journal, 22, 34-56. (Supplementary materials are available from the link.) Selected to be Editors' Choice of this issue. Top Downloaded Paper 2018-2019.
Uematsu, Y. (2019). "Nonstationary nonlinear quantile regression," Econometric Reviews, 38, 386-416.
Uematsu, Y. (2016). "Asymptotic efficiency of the OLS estimator with singular limiting sample moment matrices," Statistics & Probability Letters, 114, 104-110.
Uematsu, Y. and S. Tanaka (2016). "Regularization parameter selection via cross-validation in the presence of dependent regressors: a simulation study," Economics Bulletin, 36, 313-319.
Papers Under Review or Revision
Toyoda, M. and Y. Uematsu (2024). "Robust Reproducible Network Exploration," arXiv:2405.17117.
Sawaya, K., Y. Uematsu and M. Imaizumi (2024). "High-dimensional single-index models: Link estimation and marginal inference," arXiv:2404.17812.
Jiang, P., Y. Uematsu and T. Yamagata (2023). "Revisiting asymptotic theory for principal component estimators of approximate factor models,'' arXiv:2311.00625. (Slides)
Uematsu, Y. and T. Yamagata (2024). "Discovering the network Granger causality in large vector autoregressive models," arXiv:2303.15158.
Sawaya, K., Y. Uematsu and M. Imaizumi (2023). "Moment-based adjustments of statistical inference in high-dimensional generalized linear models," arXiv:2305.17731.