Selected publication
Statistical metholody
Hu, H. and Qiu, Y. (2022). Inference for Nonparanormal Partial Correlation via Regularized Rank-based Nodewise Regression. Biometrics. Code
Qiu, Y. and Zhou, X. H. (2021). Inference on Multi-level Brain Connectivities based on fMRI Data. The Journal of the American Statistical Association: Theory and Methods. Code
Qiu, Y., Tao, J. and Zhou, X. H. (2021). Inference for Heterogeneous Treatment Effects for Observational Data with High-Dimensional Covariates. Journal of the Royal Statistical Society: Series B, 83 1016-1043. Code
Li, Y., Xu, Y. and Qiu, Y. (2021). From multivariate to functional data analysis: fundamentals, recent developments, and emerging areas. Journal of Multivariate Analysis, 188 104806.
Xu, Y., Li, Y. and Qiu, Y. (2021). Growth dynamics and heritability for plant high-throughput phenotyping studies using hierarchical functional data analysis. Biometrical Journal, 63 1325-1341.
Qiu, Y. and Zhou, X. H. (2020). Estimating c-Level Partial Correlation Graphs with Application to Brain Imaging. Biostatistics, 21 641-658. Code
Qiu, Y. and Liyanage, J. (2019). Threshold Selection for Covariance Estimation. Biometrics, 75 985-905. Code
Chang, J., Qiu, Y., Yao, Q. and Zou, T. (2018). Confidence regions for entries of a large precision matrix. Journal of Econometrics, 206 57-82. Code
Qiu, Y., Chen, S. and Nettleton, D. (2018). Detecting Rare and Faint Signals via Thresholding Maximum Likelihood Estimators. The Annals of Statistics, 46 895-923.
Qiu, Y. and Chen, S. (2015). Band Width Selection for High-dimensional Covariance Matrix Estimation. The Journal of the American Statistical Association: Theory and Methods, 110 1160-1174. Code and “bandcov” R package
Qiu, Y. and Chen, S. (2012). Test for Bandedness of High-dimensional Covariance Matrices and Bandwidth Estimation. The Annals of Statistics, 40 1285-1314. Matlab code, “bandcov” R package
Plant science
Guo, X., Qiu, Y., Nettleton, D., Yeh, C.-T., Zheng, Z., Hey, S. and Schnable, P. S. (2021). KAT4IA: K-Means Assisted Training for Image Analysis of Field-Grown Plant Phenotypes. Plant Phenomics, Article ID 9805489. Code
Admas, J., Qiu, Y., Posadas, L., Eskridge, K. and Graef, G. (2021). Phenotypic Trait Extraction of Soybean Plants Using Deep Convolutional Neural Networks with Transfer Learning. Big Data and Information Analytics, 6 26–40. Code
Wang, R., Qiu, Y., Zhou, Y. and Schnable, J. (2020). A Comprehensive Pipeline of Image Processing and Functional Growth Analysis for High Throughput Plant Phenotyping. Plant Phenomics, Article ID 7481687. Code
Liang, Z., Qiu, Y. and Schnable, J. (2020). Genome-phenome Wide Association in Maize and Arabidopsis Identifies a Common Molecular and Evolutionary Signature. Molecular Plant, 13 907-922. Code
Adams, J., Qiu, Y., Xu, Y. and Schnable, J. (2020). Plant Segmentation by Supervised Machine Learning Methods. The Plant Phenome Journal, 3. Code
Choudhury, S., Bashyam, S., Qiu, Y., Samal, A. and Awada, T. (2018). Holistic and Component Plant Phenotyping using Temporal Image Sequence. The Plant Methods, 14 Article number: 35.
Liang, Z., Pandey, P., Stoerger, V., Xu, Y., Qiu, Y., Ge, Y. and Schnable, J. (2018). Conventional and Hyperspectral Time-series Imaging of Maize Lines Widely Used in Field Trials. Gigascience, 7 1-11.
Zhang, Y., Ngu, D., Liang, Z., Qiu, Y., Roston, R. and Schnable, J. (2017). Differentially Regulated Ortholog Analysis to Link Gene Regulatory and Phenotypic Divergence Among Panicoid Grasses. The Plant Cell, 29 1938-1951.
COVID-19
Zhu, Y., Gu, J., Qiu, Y. and Chen, S. X. (2022). Real-World COVID-19 Vaccine Protection Rates against Infection in the Delta and Omicron Eras.
Zhu, Y., Gu, J., Qiu, Y. and Chen, S. X. (2022). Estimating COVID-19 Vaccine Efficacy via Dynamic Epidemiological Models–A Study of Ten Countries.
Gu, J., Yan, H., Huang, Y., Zhu, Y., Sun, H., Zhang, X., Wang, Y., Qiu, Y. and Chen, S. X. (2021). Better Strategies for Containing COVID-19 Pandemic–A Study of 25 Countries via a vSIADR Model. Proceedings of the Royal Society A, 477 No. 2248.
Gu, J., Yan, H., Huang, Y., Zhu, Y., Sun, H., Qiu, Y. and Chen, S. X. (2020). Comparing Containment Measures among Nations by Epidemiological Effects of COVID-19. National Science Review, 7(12) 1847–1851.
Sun, H., Qiu, Y., Yan, H., Huang, Y., Zhu, Y. and Chen, S. (2020). Tracking Reproductivity of COVID-19 Epidemic in China with Varying Coefficient SIR Model. Journal of Data Science (with discussions), 18 455-472.
Complete list at Google Scholar
Manuscript
Hu, H. and Qiu, Y. (2022). Rank-based Inference for Conditional Independence Graph with Missing Values.
Guo, X., Qiu, Y., Nettleton, D. and Schnable, P. S. (2022). High-Throughput Field Plant Phenotyping: A Self-Supervised Sequential CNN Model to Segment Overlapping Plants.
Lee, H., Qiu, Y., Carriquiry, A. and Ommen, D. (2022). Optimal Matching Rule with Application in Forensic Science.
Zhang, S., Chen, S. X. and Qiu, Y. (2021). Two-Sample Mean Tests for High-Dimensional Time Series.
Qiu, Y. and Gu, Y. (2021). Residual Refitting Inference for High-Dimensional Linear Regression Models.
Li, J., Qiu, Y. and Li, L. (2020). A Neighborhood-Assisted Hotelling Test for High-Dimensional Means.