Alex T. Kalinka <alex.t.kalinka@gmail.com>, with contributions
from Alain Geunoche
Link communities reveal the nested and overlapping
structure in networks, and uncover the key nodes that form
connections to multiple communities. linkcomm provides a set of
tools for generating, visualizing, and analysing link
communities in networks of arbitrary size and type. The
linkcomm package also includes tools for generating,
visualizing, and analysing Overlapping Cluster Generator (OCG)
communities.

Alex T. Kalinka <alex.t.kalinka@gmail.com>, with contributions
from Alain Guenoche

Access to 'LinkedIn' Ads via the 'Windsor.ai' API
Collect  marketing data from 'LinkedIn' Ads using the 'Windsor.ai' API <https://windsor.ai/api-fields/>.

Linkage information based genotype imputation method
Yi Xu <statxy@gmail.com> and Jixiang Wu <jixiang.wu@sdstate.edu>
A linkage information based method for imputing missing diploid genotypes

c(
person( "Michal", "Bojanowski", email="michal2992@gmail.com", role=c("aut", "cre")),
person("Bartosz", "Chrol", email="bartek.chrol@gmail.com", role=c("aut")),
person(family="National Science Centre", role="fnd", comment="grant 2012/07/D/HS6/01971")
)
Implementations of most of the existing proximity-based methods of
link prediction in graphs. Among the 20 implemented methods are e.g.:
Adamic L. and Adar E. (2003) <doi:10.1016/S0378-8733(03)00009-1>,
Leicht E., Holme P., Newman M. (2006) <doi:10.1103/PhysRevE.73.026120>,
Zhou T. and Zhang Y (2009) <doi:10.1140/epjb/e2009-00335-8>, and
Fouss F., Pirotte A., Renders J., and Saerens M. (2007) <doi:10.1109/TKDE.2007.46>.
Michal Bojanowski [aut, cre],
Bartosz Chrol [aut],
National Science Centre [fnd] (grant 2012/07/D/HS6/01971)

Bivariate Correlations Calculation and Visualization
c(
person("Alassane", "Samba", role = c("aut", "cre"),email = "alassane.samba@orange.com"),
person(family="Orange", role = c("cph"))
)
Compute and visualize using the 'visNetwork' package all the bivariate correlations of a dataframe.
Several and different types of correlation coefficients (Pearson's r, Spearman's rho, Kendall's tau,
distance correlation, maximal information coefficient and
equal-freq discretization-based maximal normalized mutual information) are used according to
the variable couple type (quantitative vs categorical, quantitative vs quantitative, categorical vs categorical).
shiny, visNetwork, infotheo, minerva, energy, mclust,
rAmCharts, Hmisc, pbapply, ggplot2, dplyr, tidyr
'linkspotterComplete.R' 'boostedBoxplot.R'
'clusterVariables.R' 'emptyVar.R'
'linkspotterDurationEstimator.R' 'linkspotterGraph.R'
'linkspotterGraphOnMatrix.R' 'linkspotterOnFile.R'
'linkspotterUI.R' 'corCouplesToMatrix.R' 'matrixToCorCouples.R'
'maxNMI.R' 'BeEFdiscretization_numfact.R'
'BeEFdiscretization_numnum.R' 'multiBivariateCorrelation.R'
'NormalizedMI.R' 'uselessVar.R' 'createShinyAppFolder.R'