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Krahasoni metodat

Shqyrtoni metodat e zgjedhura krah për krah; rreshtat që ndryshojnë janë të theksuar.

Modeli i Grafëve të Rastit Eksponencialë të Drejtuar×Modeli Bllokues Stokastik×
FushaAnaliza e rrjeteveAnaliza e rrjeteve
FamiljaMachine learningProcess / pipeline
Viti i origjinës1986 (foundations); 2007 (modern directed ERGM formulation)1983
KrijuesiFrank, O. & Strauss, D.; extended by Robins, Pattison, Kalish & Lusher
LlojiStatistical generative model for directed networksProbabilistic generative graph model
Burimi themeluesRobins, G., Pattison, P., Kalish, Y. & Lusher, D. (2007). An introduction to exponential random graph (p*) models for social networks. Social Networks, 29(2), 173-191. DOI ↗Holland, P.W., Laskey, K.B. & Leinhardt, S. (1983). Stochastic Blockmodels: First Steps. Social Networks, 5(2), 109-137. DOI ↗
Emërtime të tjeraDirected ERGM, p-star model (directed), directed p* model, directed Markov graph modelSBM, degree-corrected SBM, DCSBM, Stokastik Blok Modeli (SBM)
Të lidhura47
PërmbledhjaThe Directed Exponential Random Graph Model (Directed ERGM) is a family of statistical models for directed networks that estimates the probability of observing a given directed graph as a function of structural configurations — such as reciprocity, transitive triads, and in-degree centralization — and node or dyad covariates, enabling principled inference about the social processes that generate directed ties.The Stochastic Block Model (SBM), introduced by Holland, Laskey and Leinhardt (1983), is a probabilistic generative model for graphs that assigns nodes to latent blocks and parametrically estimates the connection probabilities between blocks. It is the foundational approach for community detection, core-periphery identification, and hierarchical structure discovery in network analysis.
ScholarGateSeti i të dhënave
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  1. v1
  2. 2 Burimet
  3. PUBLISHED

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ScholarGateKrahasoni metodat: Directed Exponential Random Graph Model · Stochastic Block Model. Marrë më 2026-06-17 nga https://scholargate.app/sq/compare