Network Tools for Memory Research

Efficient implementations of network science tools to facilitate research into human (semantic) memory. In its current version, the package contains several methods to infer networks from verbal fluency data, various network growth models, diverse (switcher-) random walk processes, and tools to analyze and visualize networks. To deliver maximum performance the majority of the code is written in C++. For an application see: Wulff, D. U., Hills, T., & Mata, R. (2018) .


The memnet package provides efficient implementations of network science tools to facilitate research into human (semantic) memory. In its current version, the package contains several methods to infer networks from verbal fluency data, various network growth models, diverse (switcher-) random walk processes, and tools to analyze and visualize networks.

The majority of memnet is written in C++ to deliver maximum performance.

Have questions, found annoying errors, or have need/recommendation for additional functionality? Please don't hesitate to write me at [email protected] or https://github.com/dwulff/memnet. Thanks!

News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("memnet")

0.1.0 by Dirk U. Wulff, 7 months ago


Browse source code at https://github.com/cran/memnet


Authors: Dirk U. Wulff [aut, cre]


Documentation:   PDF Manual  


GPL-3 license


Imports igraph

Depends on Rcpp

Suggests knitr, rmarkdown

Linking to Rcpp, BH


See at CRAN