perform parameter/input checks inside each
backbone_from_ function
updated citation
backbone 3.0.3
updated/added generic print(), summary()
and plot() functions for backbone objects
corrected p-values in asymmetric marginal likelihood filter (h/t
@florian-huber)
backbone 3.0.2
minor updates to unit tests
backbone 3.0.1
remove deprecated functions from manual
replace all remaining %*% with
(t)crossprod()
include backbone details as graph attributes when input is an
igraph object
add backbone() wrapper function for all input network
types
speed-ups to .fixedfill() null model
specifying backbone_only = FALSE returns a
backbone-class object that can be described using
print()
backbone 3.0.0
all functions re-written to be modular, to facilitate future
extensions
streamlined functions to focus on input network type, rather than
backbone model
keep attributes of retained edges in igraph
objects
functions renamed in snake_case, to match naming conventions in
igraph
eliminated support for edgelist inputs, because they can be
ambiguous
eliminated ordinal stochastic degree sequence model (oSDSM) for
bipartite projections, because it has limited applications and has not
been formally validated
all functions have associated unit tests
backbone 2.1.4
updated depricated igraph functions
ensure row/column labels are included in p-value matrices
backbone 2.1.3
added support for structural 0s and 1s in sdsm() via
the logit() function
vectorized and added additional options to
sparsify()
implemented Marginal Likelihood Filter in mlf()
implemented Locally Adaptive Network Sparsification in
lans()
added missing.as.zero option to statistical models
backbone 2.1.2
speedups in pb() and sdsm()
fixed minor bugs introduced by igraph 1.4.0
backbone 2.1.1
speedups in sparsify() and all statistical backbone
functions
eliminated hyperg() as alternate name for
fixedrow(), eliminated universal() as
alternate name for global()
empty & full rows/cols no longer need to be removed from
bipartite inputs
replaced testthat with tinytest; expanded
unit tests
backbone object includes node attributes, if present
backbone 2.1.0
eliminated dependency on PoissonBinomial;
sdsm() and fixedcol() now use an efficient
implementation of the Refined Normal Approximation in base R
eliminated dependency on MASS; osdsm() now
uses glm() in base R to implement the conditional logistic
regression method described by Neal (2017)
eliminated dependency on network and support for
network objects, which can easily be converted to matrix
objects
removed bipartite generative functions
bipartite.from.probability(),
bipartite.from.sequence(),
bipartite.from.distribution(), and
bipartite.add.blocks(). These are now part of the
incidentally package
speed improvements to bicm()
updated the information provided in the narrative text when
narrative = TRUE
when the original graph is supplied as an igraph object
with vertex attributes, the attributes are preserved in the
backbone
added links to new tutorial: Neal, Z. P. 2022. backbone: An R
Package to Extract Network Backbones. PLOS ONE, 17, e0269137.
https://doi.org/10.1371/journal.pone.0269137
backbone 2.0.3
fixed bug in fastball() so it will work with R <
4.1.0
backbone 2.0.2
fixed bug in fastball() so it will work with R <
4.1.0
backbone 2.0.1
minor bug fixes
faster implementation of fastball() algorithm
set alpha = 0.05 as default in all statistical
models
renamed fwer (familywise error rate) parameter as
mtc (multiple test correction)
backbone 2.0.0
remove davis example data; add examples using synthetic
data
add support for unweighted graphs: sparsify()
add support for weighted bipartite graphs: osdsm()
add support for non-projection weighted graphs:
disparity()
new vignette illustrating all functions
add implementation of fastball() algorithm for
marginal-preserving matrix randomization
re-add testthat tests
allow backbone functions to directly output a backbone, eliminating
the need for the backbone.extract() function
add support for any p.adjust() method of correcting for
familywise error rates
Minor bug fixes
backbone 1.5.1
removed testthat tests due to unknown MKL error; will
be restored in a future version
backbone 1.5.0
add four functions to generate random bipartite graphs:
bipartite.from.probability(), bipartite.from.sequence(),
bipartite.from.distribution(), and bipartite.add.blocks()
set diagonal in positive and negative
backbone object matrices to NA
corrected p-value computation in fixedfill()
remove running time from backbone object summary dataframe
update documentation, readme, vignette
backbone 1.4.0
add fixedcol() function - null model where column degrees are fixed
and row sums are allowed to vary
add fixedfill() function - null model where the number of 1’s in the
matrix (number of edges in the graph) are fixed
replace class.convert() with tomatrix() and frommatrix()
use updated Poisson binomial calculations (more accurate
approximation)
hyperg() now called fixedrow()
remove bipartite.null function
update documentation, readme, vignette
include logo
backbone 1.3.1
speedups to sdsm
backbone 1.3.0
update sdsm to use the bicm model - a new, fast, approximation of
the probabilities
remove all other models from sdsm
if an older model is called in sdsm, show warning that model has
changed
add new function bipartite.null which lets the user pick if they
want rows/cols to be fixed or vary
update fwer m parameter
backbone 1.2.2
fix fdsm to accept all graph inputs
rename sdsm “chi2” model to “rcn”
universal function can now return weighted projection
universal function now has a narrative parameter
class.convert now drops (with warning) rows and columns with zero
sum before sending output to universal, sdsm, fdsm, or hyperg.
update citations
backbone 1.2.1
add narrative parameter to backbone.extract for suggested manuscript
text
add scobit model to sdsm
add time unit to runtime calculation
minor spelling and comment fixes
backbone 1.2.0
add support for sparse matrix, igraph, network, and edgelist objects
(see ‘class.convert’)
add family-wise error rate test corrections (see
‘backbone.extract’)
sdsm: add multiple methods for computing initial probabilities (see
‘sdsm’ details) one of which uses convex optimization (see
‘polytope’)
sdsm: update poisson binomial computation method to increase speed
(see ‘sdsm’ and ‘rna’)
add more descriptives to summary dataframe output of backbone
object
update documentation of functions
update vignette to reflect package changes
bug fixes for R 4.0.0
backbone 1.1.0
add support for sparse matrices
add support for speedglm in sdsm
add poisson binomial approx. in sdsm
add summary output to sdsm, fdsm, hyperg, universal