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Tutorial
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.. _models_tutorials:
Models
======
This tutorial presents several random graph models: the Erdos-Renyi (ER) model, degree-corrected ER model,
stochastic block model (SBM), degree-corrected SBM, and random dot product graph model. These models provide a basis for studying random graphs. All models are shown fit to the same dataset.
.. toctree::
:maxdepth: 1
tutorials/models/models
.. _simulations_tutorials:
Simulations
===========
The following tutorials demonstrate how to easily sample random graphs from graph models such as the Erdos-Renyi model,
stochastic block model, and random dot product graph (RDPG).
.. toctree::
:maxdepth: 1
tutorials/simulations/erdos_renyi
tutorials/simulations/sbm
tutorials/simulations/rdpg
tutorials/simulations/corr
tutorials/simulations/rdpg_corr
.. _embed_tutorials:
Embedding
=========
Inference on random graphs depends on low-dimensional Euclidean representation of the vertices of graphs, known as *graph embeddings*, typically given by spectral decompositions of adjacency or Laplacian matrices. Below are tutorials for computing graph embeddings of single graph and multiple graphs.
.. toctree::
:maxdepth: 1
tutorials/embedding/AdjacencySpectralEmbed
tutorials/embedding/Omnibus
.. _inference_tutorials:
Inference
===========================
Statistical testing on graphs requires specialized methodology in order to account
for the fact that the edges and nodes of a graph are dependent on one another. Below
are tutorials for robust statistical hypothesis testing on multiple graphs.
.. toctree::
:maxdepth: 1
tutorials/inference/latent_position_test
tutorials/inference/latent_distribution_test
.. _plot_tutorials:
Plotting
========
The following tutorials present ways to visualize the graphs, such as its adjacency matrix, and graph embeddings.
.. toctree::
:maxdepth: 1
tutorials/plotting/heatmaps
tutorials/plotting/gridplot
tutorials/plotting/pairplot
.. _matching_tutorials:
Matching
========
The following tutorials demonstrate how to use the graph matching functionality,
including an introduction to the module, and how to utilize the seeding feature.
.. toctree::
:maxdepth: 1
tutorials/matching/faq
tutorials/matching/sgm