Representative Publications
Bayesian method and computation
Nishimura, A. and Suchard, M. A. (2022)
Prior-preconditioned conjugate gradient method for accelerated Gibbs sampling in “large n, large p” Bayesian sparse regression.
Journal of the American Statistical Association.Nishimura, A. and Suchard, M. A. (2022)
Shrinkage with shrunken shoulders: Gibbs sampling shrinkage model posteriors with guaranteed convergence rates.
Bayesian Analysis.Holbrook, A., Nishimura, A., Ji, X., and Suchard M. A. (2021)
Computational Statistics \& Data Science in the 21st Century
In Computational Statistics in Data Science, John Wiley & Sons.Nishimura, A., Dunson, D. B., and Lu, J. (2020)
Discontinuous Hamiltonian Monte Carlo for discrete parameters and discontinuous likelihoods.
Biometrika.
Scientific and public health applications
Nishimura, A., Xie, J., Kostka, K., Duarte-Salles, T., Bertolín, S. F., Aragón, M., Blacketer, C., Shoaibi, A., DuVall, S. L., Lynch, K., Matheny, M. E., Falconer, T., Morales D. R., Conover, M. M., You, S. C., Pratt, N., Weaver, J., Sena, A. G., Schuemie, M. J., Reps, J., Reich, C., Rijnbeek, P. R., Ryan, P. B., Hripcsak, G., Prieto-Alhambra, D., and Suchard M. A. (2022).
International cohort study indicates no association between alpha-1 blockers and susceptibility to COVID-19 in benign prostatic hyperplasia patients.
Frontiers in Pharmacology.Wang, Z., Bowring, M. G., Rosen, A., Garibaldi, B. T., Zeger, S. L., and Nishimura, A. (2022).
Learning and Predicting from Dynamic Models for COVID-19 Patient Monitoring.
Statistical Science.Zhang, Z., Nishimura, A., Bastide, P., Ji, X., Lemey, P., and Suchard, M. A. (2021)
Large-scale inference of correlation among mixed-type biological traits with phylogenetic multivariate probit models.
Annals of Applied Statistics.
Latest works in preprint
- Nishimura, A., Zhang, Z., and Suchard, M. A. (2021).
Hamiltonian zigzag sampler got more momentum than its Markovian counterpart: Equivalence of two zigzags under a momentum refreshment limit.