Bootstrap Methods for Various Network Estimation Routines
Bootstrap methods to assess accuracy and stability of estimated network structures
and centrality indices <10.3758>. Allows for flexible
specification of any undirected network estimation procedure in R, and offers
default sets for various estimation routines.10.3758>
Changes in Version 1.2.2
- Added 'adjacency' argument to pcor default set, which allows for estimating a network with a fixed structure.
- Fixed parametric bootstrapping
Changes in Version 1.2.1
- corStability should now return the non-finite values warning less often
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