%0 Generic %1 hopfl2024bayesian %A Höpfl, Sebastian %D 2024 %K darus ubs_10008 ubs_20013 ubs_30126 ubs_40439 unibibliografie %R 10.18419/darus-3876 %T Bayesian Modeling of Time Series Data (BayModTS) %X BayModTS is a FAIR workflow for processing highly variable and sparse data. The code and results of the examples in the BayModTS paper are stored in this repository. A maintained version of BayModTS that can be applied to your personal applications can be found on Git Hub.

@misc{hopfl2024bayesian, abstract = {BayModTS is a FAIR workflow for processing highly variable and sparse data. The code and results of the examples in the BayModTS paper are stored in this repository. A maintained version of BayModTS that can be applied to your personal applications can be found on Git Hub. }, added-at = {2024-04-16T12:00:21.000+0200}, affiliation = {Höpfl, Sebastian/Universität Stuttgart}, author = {Höpfl, Sebastian}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2e387ec2cb42763b6f5e27b2ca12a6f25/unibiblio}, doi = {10.18419/darus-3876}, howpublished = {Dataset}, interhash = {b2b0601ad301d9398154094f1df663d4}, intrahash = {e387ec2cb42763b6f5e27b2ca12a6f25}, keywords = {darus ubs_10008 ubs_20013 ubs_30126 ubs_40439 unibibliografie}, orcid-numbers = {Höpfl, Sebastian/0000-0002-5300-0915}, timestamp = {2024-04-16T12:00:21.000+0200}, title = {Bayesian Modeling of Time Series Data (BayModTS)}, year = 2024 }