Bootstrap Methods for Various Network Estimation Routines
Bootstrap methods to assess accuracy and stability of estimated network structures
and centrality indices. Allows for flexible specification of any undirected network
estimation procedure in R, and offers default sets for 'qgraph', 'IsingFit', 'IsingSampler',
'glasso', 'huge' and 'parcor' packages.
Changes in Version 1.2
o New features:
- Added support for statistics "bridgeStrength", "bridgeCloseness", "bridgeBetweenness", and "bridgeExpectedInfluence". Thanks to Payton Jones!
- The statistics argument in bootnet can now be "all"
- Added bootThreshold function to threshold a network based on bootstraps (e.g., bootstrapped interval includes 0)
- Added bootInclude function to obtain a network of bootstrap inclusion probabilities
- the 'statistics' argument in bootnet now defaults to c("edge","strength","outStrength","inStrength"). This means that closeness and betweenness are no longer stored by default!
- corStability will now use all tested statistics by default
- The corStability function now accepts statistics written with an upper case first letter
- Fixed a bug using default = "mgm" with only one binary variable
- IsingFit and IsingSampler defaults now transform -1, 1 data to 0, 1 when computing network, then back when returning results
- Included the 'includeDiagonal' argument to bootnet to include storing diagonal entries (self-loops) for directed networks only
- Bootnet now copies the library used by the user to the clusters when using nCores > 1. This is important for checkpoint and packrat compatability
- corStability now returns NA for incomputable correlations (e.g., due to infinite values)
- Added default set "piecewiseIsing" for estimating Ising models while selecting participants on a sum-score (very experimental)
- Added default set "SVAR_lavaan" for step-up structural VAR model selection using Lavaan (experimental)
Changes in Version 1.1
- New supported default sets:
- "cor" - Correlation networks
- "TMFG" - Triangulated Maximally Filtered Graph
- "LoGo"- Local/Global Sparse Inverse Covariance Matrix
- "ggmModSelect" - Unregularized stepwise GGM model selection
- "graphicalVAR" - LASSO regularized graphical VAR models
- Some changes to mgm default:
- mgm version >= 1.2 is now required
- Renamed lev to level
- Renamed degree to order, now defaults to 2 instead of 3
- Added binarySign argument. Now chosen by defult.
- Added the 'replicationSimulator' function, which can be used to assess expected replicability of networks
- Many default sets now support the 'principalDirection' argument, which can be used to multiply variables with the sign of the first principal component
- plot method now supports split0 = TRUE, will show how often an edge was 0 and only show CIs of non-zero estimates (faded relative to proportion of times edge was zero).
- Updated the 'genGGM' function to support various different network structures, with thanks to Mark Brandt!
- Added RSPBC and Hybrid centrality, thanks to Alex Christensen
- Added the 'alpha' argument to default set "pcor"
- Added functionality for functions returning multiple graphs
- Added outStrength, inStrength, outExpectedInfluence and inExpectedInfluence
- Fixed a bug reporting the number of non-zero edges in the print methods
- Added 'args' argument to netSimulator
- Fixed a bug in which fun is not usuable in bootnet()
- Added lambda.min.ratio argument to some estimators. Now defaults to 0.01 for default = "huge"
- bootnet and netSimulator now show a progress bar (thanks to pbapply package)
- plot method now shows bootstrapped mean in addition to sample value
- The 'statistics' argument in bootnet and plot method now accept statistics with a upper case first letter, to be consistent with qgraph
- CIstyle argument can now only be one value, and always defaults to quantiles
Changes in Version 1.0.1
- missing = "fiml" is now supported for EBICglasso and pcor default sets
- Relative importance networks now do not crash when the number of predictors is 0 or 1
- plotting bootnetResults now supports the labels argument
- mgm default now uses matrices to resolve an error with the latest version of mgm
- The plot method of networks estimated using 'estimateNetwork' now uses different defaults than qgraph!
- cut defaults to NULL
- theme defaults to "colorblind"
- parallelEdge defaults to TRUE
- layout always defaults to "spring" (rather than "circle" for undirected networks)
Changes in Version 1.0.0:
- Implemented the netSimulator function that allows for researchers to investigate sample size requirements and input arguments to estimateNetwork
- Added genGGM, ggmGenerator, and IsingGenerator functions to be used in netSimulator
- bootnet now stores less results and should have better memory usuage! Thanks to Giulio Costantini!
- Fixed some bugs related to manual parametric bootstrap
- EstimateNetwork now references packages used in a message
- pcor default set now supports the argument 'threshold'
- Fixed a bug where rule argument was not passed in bootnet default set
- Bootnet now supports directed networks
- Relative importance networks now implemented using default = "relimp"
- Updated compatibility with MGM version 1.2.0
Changes in version 0.4:
- estimateNetwork now accepts a custom estimation function using the argument 'fun'
- Reworked default sets as functions!
- This makes it easier to change common arguments, such as the EBIC tuning parameter
- See the following functions for details:
- The corStability function now has a greatly improved output
- Default set "IsingLL" has been renamed to "IsingSampler"
- Default set "mgm" is now supported
- labels argument is now supported in difference plots
- Quantile now uses type = 6, this makes CIs slightly wider and therefore the difference test slightly more conservative
Changes in version 0.3:
- Eiko Fried joined the author list
- Added 'estimateNetwork' function, allowing one to estimate the network structure
from within bootnet
- The plot method will run qgraph on the estimated network structure
- The qgraph function getWmat can now be applied to networks estimated in bootnet.
Allowing one to use, e.g., centralityPlot on a network estimated with
- Added 'differenceTest' function to test for significant differences between edge
weights and centrality indices
- Added 'corStability' to compute the CS-coefficient as described in our paper:
- Epskamp, S., Borsboom, D., & Fried, E. I. (2016). Estimating psychological
networks and their accuracy: a tutorial paper. arXiv preprint,
- The plot method now supports 'plot = "difference"', to make plots of significant
differences between edge-weights and centralities
- New default sets:
- 'nCores' argument added to bootnet to use parallel computing
- bootnet print methods now print a list of relevant references on the network
estimation procedure used
- When EBICglasso is used as default set, variables that are made ordinal are now
printed only when estimating the first network
- Updated CITATION such that citation("bootnet") now references the pre-print
- Bootnet now gives a message on loading that it is BETA software
- Added 'statistics' argument to bootnet. Now, distance and length are not stored by
- Several minor bugfixes