Bayesian Modeling of Time Series Data (BayModTS)


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.

Related Identifier IsCitedBy
Metadata Access
Creator Höpfl, Sebastian ORCID logo
Publisher DaRUS
Contributor Höpfl, Sebastian; Radde, Nicole
Publication Year 2024
Funding Reference DFG FOR 5151 - 436883643 ; DFG EXC 2075 - 390740016
Rights CC BY 4.0; info:eu-repo/semantics/openAccess;
OpenAccess true
Contact Höpfl, Sebastian (University of Stuttgart); Radde, Nicole (University of Stuttgart)
Resource Type Dataset
Format application/zip
Size 850053521; 833326785; 292585173; 239306911; 246690428; 656396758; 96612662
Version 1.1
Discipline Life Sciences; Medicine