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Implementations from my master's thesis: Community Detection using SBM (Stochastic Block Model) and DC-SBM (Degree-Corrected Stochastic Block Model), as well as evolving static SBM/DC-SBM with Markov Edge Dynamics.

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PapaTuerk99/Master_Code

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Die Implementierungen meiner Masterarbeit. Nur ein kleiner Teil ist in Python und der Rest in R. Der Code ist chronologisch und funktioniert nur, falls es in der Reihenfolge ausgeführt wird. Leider benötigt man RTool, da dynsbm archiviert wurde. Für den Phython Code benötigt man graph-tool, wodurch man insbesondere Ubuntu installiert haben muss.

Im Ordner Main_result_MA findet man die praktische Methode als Funktion geschrieben. Zusätzlich findet man ein eigenes Beispiel, wo man sich einen Graphen zu den DAX log returns anschaut. Eine Kante entsteht, falls die Korrelation hoch genug war in dem vorgegebenen Zeitraum. ############################# The implementations for my master's thesis. Only a small part is in Python, and the rest is in R. The code is arranged chronologically and only works if executed in that specific order. Unfortunately, you need RTool since dynsbm has been archived. For the Python code, you need graph-tool, which requires Ubuntu to be installed.

In the folder Main_result_MA, you will find the practical method written as a function. Additionally, there is a custom example where a graph is generated for DAX log returns. An edge is created if the correlation was high enough within the specified period.

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Implementations from my master's thesis: Community Detection using SBM (Stochastic Block Model) and DC-SBM (Degree-Corrected Stochastic Block Model), as well as evolving static SBM/DC-SBM with Markov Edge Dynamics.

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