Stochastic processes, analysis, examples (Python tutorial)
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| Titel: | Stochastic processes, analysis, examples (Python tutorial) |
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| Autoren: | Markus Abel |
| Weitere Verfasser: | Kompetenzzentrum für nicht-textuelle Materialien |
| Verlagsinformationen: | OpenGeoHub Foundation |
| Publikationsjahr: | 2022 |
| Schlagwörter: | Statistical test, Computer science, Open Data, Open science, Studienbereich Informatik, Ingenieurwissenschaften |
| Beschreibung: | (en)In this contribution we will systematically walk to stochastic processes starting from random variables in 1,2, and more dimensions. We show tests and ways to create statistically relevant test data based on requirements or assumptions on the models to be tested. Emphasis is on testing strategies using standard python libraries. |
| Publikationsart: | course material moving image (video) |
| Sprache: | English |
| Relation: | https://av.tib.eu/media/59416 |
| Verfügbarkeit: | https://av.tib.eu/media/59416 |
| Rights: | https://creativecommons.org/licenses/by/3.0/de |
| Dokumentencode: | edsbas.2EC22F01 |
| Datenbank: | BASE |
Nájsť tento článok vo Web of Science | Abstract: | (en)In this contribution we will systematically walk to stochastic processes starting from random variables in 1,2, and more dimensions. We show tests and ways to create statistically relevant test data based on requirements or assumptions on the models to be tested. Emphasis is on testing strategies using standard python libraries. |
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