Stochastic processes, analysis, examples (Python tutorial)

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Bibliographic Details
Title: Stochastic processes, analysis, examples (Python tutorial)
Authors: Markus Abel
Contributors: Kompetenzzentrum für nicht-textuelle Materialien
Publisher Information: OpenGeoHub Foundation
Publication Year: 2022
Subject Terms: Statistical test, Computer science, Open Data, Open science, Studienbereich Informatik, Ingenieurwissenschaften
Description: (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.
Document Type: course material
moving image (video)
Language: English
Relation: https://av.tib.eu/media/59416
Availability: https://av.tib.eu/media/59416
Rights: https://creativecommons.org/licenses/by/3.0/de
Accession Number: edsbas.2EC22F01
Database: BASE
Description
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.