Learn R Programming

blockmodeling (version 1.1.5)

Generalized and Classical Blockmodeling of Valued Networks

Description

This is primarily meant as an implementation of generalized blockmodeling for valued networks. In addition, measures of similarity or dissimilarity based on structural equivalence and regular equivalence (REGE algorithms) can be computed and partitioned matrices can be plotted: Žiberna (2007), Žiberna (2008), Žiberna (2014).

Copy Link

Version

Install

install.packages('blockmodeling')

Monthly Downloads

1,294

Version

1.1.5

License

GPL (>= 2)

Maintainer

Ales Ziberna

Last Published

August 23rd, 2023

Functions in blockmodeling (1.1.5)

Nice printing of the blocks parameter as used in optRandomParC and critFunC.

Comparing partitions on one or multiple sets of units

A wrapper for function gplot - Two-Dimensional Visualization of Graphs

Function for "unlisting" a partition.

Function for iterated row and column normalization of valued matrices

Two-mode network conversions

The function for generating random partitions

A formating function for numbers

Replaces NaN values by the speficied values (0 by default)

Calculate the value of the Relative Fit function

Functions for loading and writing Pajek files

REGE - Algorithms for compiting (dis)similarities in terms of regular equivalnece

Functions for Generalized blockmodeling for valued networks

Function for extraction of some elements for objects, returend by functions for Generalized blockmodeling

Functions for listing all possible partitions or just counting the number of them

Citation data between social work journals for the 1985-86 period

The notes borrowing network between social-informatics students

Orders the partition so that mean values of fun applied to columns (if funWay=2, default), rows (if funWay=1) or both (if funWay=c(1,2)) is decreasing by clusters.

Generalized matrix multiplication

Functions for computing "relative inverse" (x[1]/x).

funByBlocks.default

Computation of function values by blocks

Reordering an image matrix of the blockmodel (or an error matrix based on new and old partition

Optimizing a set of partitions based on the value of a criterion function

Functions creating a list of partitions based on a single partition and information on the number of units in each set.

Sum of Squared deviations from the mean and sum of Absolute Deviations from the median

Unlist a partition.

Functions for plotting a partitioned matrix (representing the network)

Computes distances in terms of Structural equivalence (Lorrain & White, 1971)

Create canonical partition and find unique canonical partitions in a list of partitions.

Computing the threshold

Expands a square matrix by repeating each row/column the specified number of times.

An R package for Generalized and classical blockmodeling of valued networks