Zobrazeno 1 - 10
of 1 355
pro vyhledávání: '"SUCHARD, MARC A."'
Reconstructing the evolutionary history relating a collection of molecular sequences is the main subject of modern Bayesian phylogenetic inference. However, the commonly used Markov chain Monte Carlo methods can be inefficient due to the complicated
Externí odkaz:
http://arxiv.org/abs/2408.05058
Hawkes stochastic point process models have emerged as valuable statistical tools for analyzing viral contagion. The spatiotemporal Hawkes process characterizes the speeds at which viruses spread within human populations. Unfortunately, likelihood-ba
Externí odkaz:
http://arxiv.org/abs/2407.11349
Autor:
Fourment, Mathieu, Macaulay, Matthew, Swanepoel, Christiaan J, Ji, Xiang, Suchard, Marc A, Matsen IV, Frederick A
Bayesian inference has predominantly relied on the Markov chain Monte Carlo (MCMC) algorithm for many years. However, MCMC is computationally laborious, especially for complex phylogenetic models of time trees. This bottleneck has led to the search f
Externí odkaz:
http://arxiv.org/abs/2406.18044
Autor:
Tian, Yuxi, Pratt, Nicole, Hester, Laura L, Hripcsak, George, Schuemie, Martijn J, Suchard, Marc A
In pharmacoepidemiology research, instrumental variables (IVs) are variables that strongly predict treatment but have no causal effect on the outcome of interest except through the treatment. There remain concerns about the inclusion of IVs in propen
Externí odkaz:
http://arxiv.org/abs/2403.14563
Autor:
Brusselmans, Marius, Carvalho, Luiz Max, Hong, Samuel L., Gao, Jiansi, Matsen IV, Frederick A., Rambaut, Andrew, Lemey, Philippe, Suchard, Marc A., Dudas, Gytis, Baele, Guy
Modern phylogenetics research is often performed within a Bayesian framework, using sampling algorithms such as Markov chain Monte Carlo (MCMC) to approximate the posterior distribution. These algorithms require careful evaluation of the quality of t
Externí odkaz:
http://arxiv.org/abs/2402.11657
Autor:
Lin, Chin-Yi, Chen, Kuo-Chin, Lemey, Philippe, Suchard, Marc A., Holbrook, Andrew J., Hsieh, Min-Hsiu
Multiproposal Markov chain Monte Carlo (MCMC) algorithms choose from multiple proposals at each iteration in order to sample from challenging target distributions more efficiently. Recent work demonstrates the possibility of quadratic quantum speedup
Externí odkaz:
http://arxiv.org/abs/2312.01402
The Cox proportional hazards model stands as a widely-used semi-parametric approach for survival analysis in medical research and many other fields. Numerous extensions of the Cox model have further expanded its versatility. Statistical computing cha
Externí odkaz:
http://arxiv.org/abs/2310.16238
Autor:
Didier, Gustavo, Glatt-Holtz, Nathan E., Holbrook, Andrew J., Magee, Andrew F., Suchard, Marc A.
The continuous-time Markov chain (CTMC) is the mathematical workhorse of evolutionary biology. Learning CTMC model parameters using modern, gradient-based methods requires the derivative of the matrix exponential evaluated at the CTMC's infinitesimal
Externí odkaz:
http://arxiv.org/abs/2306.15841
Autor:
Weaver, James, Ryan, Patrick B., Strauss, Victoria Y., Suchard, Marc A., Swerdel, Joel, Prieto-Alhambra, Daniel
Outcome phenotype measurement error is rarely corrected in comparative effect estimation studies in observational pharmacoepidemiology. Quantitative bias analysis (QBA) is a misclassification correction method that algebraically adjusts person counts
Externí odkaz:
http://arxiv.org/abs/2305.15524
Autor:
Bu, Fan, Schuemie, Martijn J., Nishimura, Akihiko, Smith, Louisa H., Kostka, Kristin, Falconer, Thomas, McLeggon, Jody-Ann, Ryan, Patrick B., Hripcsak, George, Suchard, Marc A.
Post-market safety surveillance is an integral part of mass vaccination programs. Typically relying on sequential analysis of real-world health data as they accrue, safety surveillance is challenged by the difficulty of sequential multiple testing an
Externí odkaz:
http://arxiv.org/abs/2305.12034