netdiffuseR-graphs: Network data formats

In srdyal/diffusiontest: Analysis of Diffusion and Contagion Processes on Networks

Network data formats

Description

List of accepted graph formats

Details

The netdiffuseR package can handle different types of graph objects. Two general classes are defined across the package's functions: static graphs, and dynamic graphs.

• In the case of static graphs, these are represented as adjacency matrices of size n\times n and can be either matrix (dense matrices) or dgCMatrix (sparse matrix from the Matrix package). While most of the package functions are defined for both classes, the default output graph is sparse, i.e. dgCMatrix.

• With respect to dynamic graphs, these are represented by either a diffnet object, an array of size n\times n \times T, or a list of size T with sparse matrices (class dgCMatrix) of size n\times n. Just like the static graph case, while most of the functions accept both graph types, the default output is dgCMatrix.

Value

No return value (this manual entry only provides information).

diffnet objects

In the case of diffnet-class objects, the following arguments can be omitted when calling fuictions suitable for graph objects:

• toa: Time of Adoption vector

• adopt: Adoption Matrix

• cumadopt: Cumulative Adoption Matrix

• undirected: Whether the graph is directed or not

Objects' names

When possible, netdiffuseR will try to reuse graphs dimensional names, this is, rownames, colnames, dimnames and names (in the case of dynamic graphs as lists). Otherwise, when no names are provided, these will be created from scratch.

Author(s)

George G. Vega Yon

srdyal/diffusiontest documentation built on Dec. 9, 2024, 1:14 a.m.