Data underlying the research on On-line warning system for pipe burst using Bayesian dynamic linear models

doi:10.4121/17169383.v3
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/17169383
Datacite citation style:
Henriques da Silva, Renato; Schmidt, Alexandra M.; Duchesne, Sophie; Fortin St-Gelais, Nicolas (2022): Data underlying the research on On-line warning system for pipe burst using Bayesian dynamic linear models. Version 3. 4TU.ResearchData. dataset. https://doi.org/10.4121/17169383.v3
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
choose version:
version 3 - 2022-09-15 (latest)
version 2 - 2022-04-12 version 1 - 2022-04-04
usage stats
1690
views
1
citations
3337
downloads
time coverage
2015-01-01 to 2016-12-31
licence
cc-0.png logo CC0

The dataset contains the following items:


- dma1_flow.txt = hourly water flow (m3/h) for district meter area 1

(rows are days, columns are the 24 hours)


- dma1_pressure.txt = hourly pressure (psi) for district meter area 1

(rows are days, columns are the 24 hours)


- temperature.txt = hourly temperature (Celcius)

(rows are days, columns are the 24 hours)


- wk_dummy.txt = dummy variable indicating whether its a workday or a weekend

(rows are days, columns are the 2 dummy variables)


- dates : dates of the recordings

(rows are days)


dlm_script.R : a R script to run the dynamic linear model with the example dataset.


history
  • 2022-04-04 first online
  • 2022-09-15 published, posted
publisher
4TU.ResearchData
format
txt, R-script
funding
  • Mitacs IT15343
organizations
Halifax Water

DATA

files (6)