- updated depricated
`igraph`

functions - ensure row/column labels are included in p-value matrices

- 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

- speedups in
`pb()`

and`sdsm()`

- fixed minor bugs introduced by
`igraph 1.4.0`

- 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

- 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

- fixed bug in
`fastball()`

so it will work with R < 4.1.0

- fixed bug in
`fastball()`

so it will work with R < 4.1.0

- 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)

- 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

- removed
`testthat`

tests due to unknown MKL error; will be restored in a future version

- 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

- 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

- speedups to sdsm

- 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

- 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

- 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

- 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

- 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
- update vignette to reflect package changes
- bug fixes

- initial release