1. Kowal, D.R., Matteson, D.S., and Ruppert, D. Dynamic Shrinkage Processes.

Published/In Press

  1. Kowal, D.R., Matteson, D.S., and Ruppert, D. (2016). A Bayesian multivariate functional dynamic linear modelJournal of the American Statistical Association. In press. Preprint arXiv:1411.0764. R code and data
  2. Kowal, D.R., Matteson, D.S., and Ruppert, D. (2016). Functional autoregression for sparsely sampled data. Journal of Business & Economic Statistics. Accepted. Preprint arXiv:1603.02982. R code and data.
    • Student Paper Award: Nonparametric Statistics Section (2017)
  3. Kohn, J.C., Chen, A., Cheng, S., Kowal, D.R., King, M.R., and Reinhart-King, C.A. (2016). Mechanical heterogeneities in the subendothelial matrix develop with age and decrease with exerciseJournal of Biomechanics, 49(9), 1447-1453.
  4. Alcoser, T.A., Bordeleau, F., Carey, S.P., Lampi, M.C., Kowal, D.R., Somasegar, S., Varma, S., Shin, S.J., and Reinhart-King, C.A. (2015). Probing the biophysical properties of primary breast tumor-derived fibroblastsCellular and Molecular Bioengineering, 8(1), 76-85.
    • Editors’ Choice Award: Cellular and Molecular Bioengineering (2016)

Working Papers

  1. Kowal, D.R., Matteson, D.S., and Ruppert, D. Dynamic Function-on-Scalar Regression.
  2. Kowal, D.R., Matteson, D.S., Ruppert, D., Jones-Rounds, J., Ye, Z., and De Rosa, E. A Replicate Spatio-Temporal Factor Model for EEG Analysis.

Technical Reports

  1. Kowal, D.R. A Modified Ljung-Box Test for the Functional Linear Model.
  2. Kowal, D.R. and Ding, J. (2012). Applications of linear mixed effect models: an analysis of Missouri school data. Washington U. Senior Honors Thesis Abstracts.
  3. Kowal, D.R. (2009). Methods of capturing stereoscopic movies, their uses, and their limitations. NASA Space Grant Consortium.