The behaviour of many processes in science and engineering can be accurately described by dynamical system models consisting of a set of ordinary differential equations (ODEs). Often these models have

DataCite Commons2020-08-25 更新60

Ord_TJ_EVOL_16-0165R2_BIphylogeny_posteriordistribution

贝叶斯推断

系统发育学

Entire posterior distribution (minus burn-in) used to create Bayesian inference consensus tree

DataONE2016-06-01 更新30

Efficient Bayesian Inference for Nonlinear State Space Models With Univariate Autoregressive State Equation

统计建模

贝叶斯推断

Latent autoregressive processes are a popular choice to model time varying parameters. These models can be formulated as nonlinear state space models for which inference is not straightforward due to

DataCite Commons2021-09-29 更新60

Sir data from A comparison of approximate versus exact techniques for Bayesian parameter inference in nonlinear ordinary differential equation models

贝叶斯推断

流行病学建模

NIAID Data Ecosystem30