Publications
- Shi, P. et al. (2023): Time-Informed Dimensionality Reduction for Longitudinal Microbiome Studies.
bioRxiv
- Han, R., Shi, P. and Zhang, A. R. (2023): Guaranteed Functional Tensor Singular Value Decomposition.
Journal of the American Statistical Association, 1-13.
- SenNet Consortium (2022): NIH SenNet Consortium to map senescent cells throughout the human lifespan to understand physiological health. Nature Aging, 1-11. (Shi, P. among other authors as a member of
the SenNet consortium)
- Shi, P., Zhou, Y. and Zhang, A. R. (2022): High-dimensional Log-Error-in-Variable Regression with Applications to Microbial Compositional Data Analysis.
Biometrika, 109(2): 405-420.
- Lu, J. Shi, P. and Li, H. (2019): Generalized Linear Models with Linear Constraints for Microbiome Compositional Data.
Biometrics, 75(1): 235-244.
- Shi, P. and Li, H. (2017): A model for paired-multinomial data and its application to analysis of data on a taxonomic tree.
Biometrics, 73(4): 1266-1278.
Download the R codes
- Shi, P., Zhang, A. and Li, H. (2016): Regression analysis for microbiome compositional data.
Annals of Applied Statistics, 10(2): 1019-1040.
Download the Matlab codes
- Fogarty, C. B., Shi, P., Mikkelsen, M. E. and Small, D. S. (2014): Randomization inference and sensitivity analysis
for composite null hypotheses with binary
outcomes in matched observational studies.
Journal of the American Statistical Association, 112(517): 321-331.
- Lin, W., Shi, P., Feng, R. and Li, H. (2014): Variable selection in regression with compositional covariates.
Biometrika, 101(4): 785-797.
Download the R codes
Other Manuscripts
