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Akihiko Nishimura

Showing results (1-10 of 35) with videos related to

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Journal of the American Statistical Association|March 29, 2024
Prior-Preconditioned Conjugate Gradient Method for Accelerated Gibbs Sampling in "Large <i>n</i>, Large <i>p</i>" Bayesian Sparse RegressionAkihiko Nishimura, Marc A Suchard
Bayesian Analysis|May 21, 2024
Shrinkage with shrunken shoulders: Gibbs sampling shrinkage model posteriors with guaranteed convergence ratesAkihiko Nishimura, Marc A Suchard
JAMIA Open|October 28, 2024
Assessing the impact of social determinants of health on diabetes severity and managementXiyu Ding, Hadi Kharrazi, Akihiko Nishimura
Journal of the American Statistical Association|August 11, 2025
Zigzag path connects two Monte Carlo samplers: Hamiltonian counterpart to a piecewise deterministic Markov processAkihiko Nishimura, Zhenyu Zhang, Marc A Suchard
JAMA Ophthalmology|March 27, 2025
Conflicting Results-Need for More Transparent and Reproducible ResearchCindy X Cai, Michelle Hribar, Akihiko Nishimura
Ophthalmology. Retina|February 22, 2025
ReplyCindy X Cai, Akihiko Nishimura, George Hripcsak
Statistics in Medicine|January 16, 2023
Adjusting for both sequential testing and systematic error in safety surveillance using observational data: Empirical calibration and MaxSPRTMartijn J Schuemie, Fan Bu, Akihiko Nishimura, et al.
Biometrika|February 25, 2020
Bayesian constraint relaxationLeo L Duan, Alexander L Young, Akihiko Nishimura, et al.
Statistical Science : a Review Journal of the Institute of Mathematical Statistics|May 22, 2023
Learning and Predicting from Dynamic Models for COVID-19 Patient MonitoringZitong Wang, Mary Grace Bowring, Antony Rosen, et al.
Molecular Biology and Evolution|November 11, 2023
Shrinkage-based Random Local Clocks with Scalable InferenceAlexander A Fisher, Xiang Ji, Akihiko Nishimura, et al.
Pageof 4

Showing results (1-10 of 35) with videos related to

Sort By:
Pageof 4
Journal of the American Statistical Association|March 29, 2024
Prior-Preconditioned Conjugate Gradient Method for Accelerated Gibbs Sampling in "Large <i>n</i>, Large <i>p</i>" Bayesian Sparse RegressionAkihiko Nishimura, Marc A Suchard
Bayesian Analysis|May 21, 2024
Shrinkage with shrunken shoulders: Gibbs sampling shrinkage model posteriors with guaranteed convergence ratesAkihiko Nishimura, Marc A Suchard
JAMIA Open|October 28, 2024
Assessing the impact of social determinants of health on diabetes severity and managementXiyu Ding, Hadi Kharrazi, Akihiko Nishimura
Journal of the American Statistical Association|August 11, 2025
Zigzag path connects two Monte Carlo samplers: Hamiltonian counterpart to a piecewise deterministic Markov processAkihiko Nishimura, Zhenyu Zhang, Marc A Suchard
JAMA Ophthalmology|March 27, 2025
Conflicting Results-Need for More Transparent and Reproducible ResearchCindy X Cai, Michelle Hribar, Akihiko Nishimura
Ophthalmology. Retina|February 22, 2025
ReplyCindy X Cai, Akihiko Nishimura, George Hripcsak
Statistics in Medicine|January 16, 2023
Adjusting for both sequential testing and systematic error in safety surveillance using observational data: Empirical calibration and MaxSPRTMartijn J Schuemie, Fan Bu, Akihiko Nishimura, et al.
Biometrika|February 25, 2020
Bayesian constraint relaxationLeo L Duan, Alexander L Young, Akihiko Nishimura, et al.
Statistical Science : a Review Journal of the Institute of Mathematical Statistics|May 22, 2023
Learning and Predicting from Dynamic Models for COVID-19 Patient MonitoringZitong Wang, Mary Grace Bowring, Antony Rosen, et al.
Molecular Biology and Evolution|November 11, 2023
Shrinkage-based Random Local Clocks with Scalable InferenceAlexander A Fisher, Xiang Ji, Akihiko Nishimura, et al.
Pageof 4