no code implementations • 21 Apr 2020 • Allison Koenecke, Michael Powell, Ruoxuan Xiong, Zhu Shen, Nicole Fischer, Sakibul Huq, Adham M. Khalafallah, Marco Trevisan, Pär Sparen, Juan J Carrero, Akihiko Nishimura, Brian Caffo, Elizabeth A. Stuart, Renyuan Bai, Verena Staedtke, David L. Thomas, Nickolas Papadopoulos, Kenneth W. Kinzler, Bert Vogelstein, Shibin Zhou, Chetan Bettegowda, Maximilian F. Konig, Brett Mensh, Joshua T. Vogelstein, Susan Athey
Here, we conducted retrospective analyses in two cohorts of patients with acute respiratory distress (ARD, n=18, 547) and three cohorts with pneumonia (n=400, 907).
2 code implementations • 6 Nov 2019 • Akihiko Nishimura, Marc A. Suchard
Use of continuous shrinkage priors -- with a "spike" near zero and heavy-tails towards infinity -- is an increasingly popular approach to induce sparsity in parameter estimates.
Methodology Statistics Theory Statistics Theory
1 code implementation • 29 May 2019 • Xiang Ji, Zhen-Yu Zhang, Andrew Holbrook, Akihiko Nishimura, Guy Baele, Andrew Rambaut, Philippe Lemey, Marc A. Suchard
To make this tractable, we present a linear-time algorithm for ${\cal O}\hspace{-0. 2em}\left( N \right)$-dimensional gradient evaluation and apply it to general continuous-time Markov processes of sequence substitution on a phylogenetic tree without a need to assume either stationarity or reversibility.
Computation Populations and Evolution Methodology
1 code implementation • 29 Oct 2018 • Akihiko Nishimura, Marc A. Suchard
We can then solve the linear system by the conjugate gradient (CG) algorithm through matrix-vector multiplications by $\Phi$; this involves no explicit factorization or calculation of $\Phi$ itself.
1 code implementation • 23 May 2017 • Akihiko Nishimura, David Dunson, Jianfeng Lu
Hamiltonian Monte Carlo has emerged as a standard tool for posterior computation.
Computation