Name | Version | Summary | date |
penaltyblog |
1.0.3 |
Library from http://pena.lt/y/blog for scraping and modelling football (soccer) data |
2024-12-19 20:10:36 |
climate-trace |
0.4.0 |
A package for loading and analyzing data from the Climate TRACE consortium. |
2024-12-19 13:25:21 |
dynesty |
2.1.5 |
A dynamic nested sampling package for computing Bayesian posteriors and evidences. |
2024-12-17 20:07:48 |
raynest |
1.0.6 |
raynest: Parallel nested sampling based on ray |
2024-11-21 15:22:06 |
linear_segment |
1.2.1 |
Python package for Bayesian Change Point and Circular Binary Segmentation |
2024-11-20 22:22:41 |
gemlib |
0.12.1 |
GEMlib scientific compute library for epidemic modelling |
2024-11-12 05:27:28 |
exotic |
4.2.3 |
EXOTIC: EXOplanet Transit Interpretation Code |
2024-11-07 21:47:24 |
geobipy |
2.3.1 |
McMC inversion of airborne electromagnetic data |
2024-10-10 02:12:17 |
optimas |
0.7.1 |
Optimization at scale, powered by libEnsemble |
2024-09-20 21:16:10 |
HSSM |
0.2.4 |
Bayesian inference for hierarchical sequential sampling models. |
2024-09-18 23:31:00 |
dataprob |
0.9.4 |
Do likelihood based parameter estimation using maximum likeihood and bayesian methods |
2024-09-18 03:53:21 |
dive-EPR |
0.2.1 |
Python package for Bayesian analysis of dipolar EPR spectroscopy data through Markov chain Monte Carlo sampling with PyMC. |
2024-08-14 16:46:36 |
emd-falsify |
1.0.1 |
Original implementation of the EMD (empirical model discrepancy) model comparison criterion |
2024-08-09 22:34:50 |
conjugate-prior |
0.85 |
Bayesian Statistics conjugate prior distributions |
2024-07-28 15:14:12 |
guardpy |
0.0.0 |
A Python Package for Geospatial Uncertainty-Aware Road-Width Detection (GAURD) |
2024-07-25 17:19:55 |
lampe |
0.9.0 |
Likelihood-free AMortized Posterior Estimation with PyTorch |
2024-07-20 21:52:17 |
EmaCalc |
1.1.2 |
Statistical Analysis of Ecological Momentary Assessment (EMA) Data |
2024-07-04 16:11:20 |
comparative-judgement |
0.0.2 |
A package for conducting Comparative Judgement |
2024-06-05 08:21:21 |
threeML |
2.4.2 |
The Multi-Mission Maximum Likelihood framework |
2024-05-31 22:59:19 |
slimp |
0.5.0 |
Linear models with Stan and Pandas |
2024-05-17 15:32:39 |