PyMC3 PROBPROG example

NIAID Data Ecosystem2026-03-12 收录

概率编程

贝叶斯推断

数据链接：

https://figshare.com/articles/dataset/PyMC3_PROBPROG_example/13093091 数据链接链接失效反馈

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资源简介：

InferenceData containing results of the radon model generated with PyMC3 and ArviZ

创建时间：

2020-10-14

fig 4 from A comparison of approximate versus exact techniques for Bayesian parameter inference in nonlinear ordinary differential equation models

贝叶斯推断

常微分方程

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100

Supplementary data from Sampaio Mayer et al.

系统发育学

贝叶斯推断

mcc contains the Maximum Clade Credibility tree, while posterior_sample contains the 100 random trees from the posterior sample.

NIAID Data Ecosystem80

Code and simulation data for: A Bayesian method for inference of effective connectivity in brain networks for detecting the Mozart effect

神经科学

贝叶斯推断

Developed MATLAB code and simulation data for the Mozart effect study. The code requires the Bayesian topology identification code and the MVGC toolbox to run (see references).

DataCite Commons2025-04-01 更新50

Appendix D. Priors and posteriors for variance parameters.

贝叶斯推断

方差参数

Priors and posteriors for variance parameters.

DataCite Commons2020-09-03 更新90

Bayesian Inference for Regression Copulas

贝叶斯推断

Copulas

We propose a new semiparametric distributional regression smoother that is based on a copula decomposition of the joint distribution of the vector of response values. The copula is high-dimensional an

DataCite Commons2021-04-01 更新70

PyMC3 PROBPROG example

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