Package: NetworkComparisonTest
Type: Package
Title: Statistical Comparison of Two Networks Based on Three Invariance
Measures
Version: 2.0.1
Date: 2016-10-28
Author: Claudia D. van Borkulo, with contributions from Sacha Epskamp and Alex Millner
Maintainer: Claudia van Borkulo <cvborkulo@gmail.com>
Imports: qgraph, IsingFit, IsingSampler, reshape2, stats, graphics,
utils
Description: This permutation based hypothesis test, suited for Gaussian and
binary data, assesses the difference between two networks based on several
invariance measures (network structure invariance, global strength invariance,
edge invariance). Network structures are estimated with l1-regularized partial
correlations (Gaussian data) or with l1-regularized logistic regression (eLasso,
binary data). Suited for comparison of independent and dependent samples
(currently, only for one group measured twice).
License: GPL-2
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-10-28 13:43:36 UTC; claudiavanborkulo
Repository: CRAN
Date/Publication: 2016-10-29 00:25:00

person("Claudia", "van Borkulo", email = "cvborkulo@gmail.com",role = c("aut","cre")),
person("Sacha", "Epskamp", role = c("aut")),
person("Payton", "Jones", role = c("aut")),
person("Jonas", "Haslbeck", role = c("ctb")),
person("Alex", "Millner", role = c("ctb")))
Description: This permutation based hypothesis test, suited for Gaussian and binary data,
assesses the difference between two networks based on several invariance measures
(e.g., network structure invariance, global strength invariance, edge invariance).
Network structures are estimated with l1-regularized partial correlations (Gaussian data)
or with l1-regularized logistic regression (eLasso, binary data). Suited for comparison
of independent and dependent samples. For dependent samples, only supported for data of
one group which is measured twice. See van Borkulo et al. (2017)
Packaged: 2019-06-28 07:28:59 UTC; claudiavanborkulo

Description: Network is a prevalent form of data structure in many fields. As an object of analysis, many distance or metric measures have been proposed to define the concept of similarity between two networks. We provide a number of distance measures for networks. See Jurman et al (2011) <doi:10.3233/978-1-60750-692-8-227> for an overview on spectral class of inter-graph distance measures.
Imports: Matrix, Rcpp, Rdpack, RSpectra, doParallel, foreach, parallel,