Package: netdiffuseR 1.22.7
netdiffuseR: Analysis of Diffusion and Contagion Processes on Networks
Empirical statistical analysis, visualization and simulation of diffusion and contagion processes on networks. The package implements algorithms for calculating network diffusion statistics such as transmission rate, hazard rates, exposure models, network threshold levels, infectiousness (contagion), and susceptibility. The package is inspired by work published in Valente, et al., (2015) <doi:10.1016/j.socscimed.2015.10.001>; Valente (1995) <ISBN: 9781881303213>, Myers (2000) <doi:10.1086/303110>, Iyengar and others (2011) <doi:10.1287/mksc.1100.0566>, Burt (1987) <doi:10.1086/228667>; among others.
Authors:
netdiffuseR_1.22.7.tar.gz
netdiffuseR_1.22.7.zip(r-4.5)netdiffuseR_1.22.7.zip(r-4.4)netdiffuseR_1.22.7.zip(r-4.3)
netdiffuseR_1.22.7.tgz(r-4.4-x86_64)netdiffuseR_1.22.7.tgz(r-4.4-arm64)netdiffuseR_1.22.7.tgz(r-4.3-x86_64)netdiffuseR_1.22.7.tgz(r-4.3-arm64)
netdiffuseR_1.22.7.tar.gz(r-4.5-noble)netdiffuseR_1.22.7.tar.gz(r-4.4-noble)
netdiffuseR_1.22.7.tgz(r-4.4-emscripten)netdiffuseR_1.22.7.tgz(r-4.3-emscripten)
netdiffuseR.pdf |netdiffuseR.html✨
netdiffuseR/json (API)
NEWS
# Install 'netdiffuseR' in R: |
install.packages('netdiffuseR', repos = c('https://usccana.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/usccana/netdiffuser/issues
- brfarmers - Brazilian Farmers
- brfarmersDiffNet - 'diffnet' version of the Brazilian Farmers data
- fakeDynEdgelist - Fake dynamic edgelist
- fakeEdgelist - Fake static edgelist
- fakesurvey - Fake survey data
- fakesurveyDyn - Fake longitudinal survey data
- kfamily - Korean Family Planning
- kfamilyDiffNet - 'diffnet' version of the Korean Family Planning data
- medInnovations - Medical Innovation
- medInnovationsDiffNet - 'diffnet' version of the Medical Innovation data
contagiondiffusion-networknetwork-analysisnetwork-visualization
Last updated 9 days agofrom:7bd4c98190. Checks:OK: 1 WARNING: 6 ERROR: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 12 2024 |
R-4.5-win-x86_64 | ERROR | Nov 12 2024 |
R-4.5-linux-x86_64 | WARNING | Nov 12 2024 |
R-4.4-win-x86_64 | WARNING | Nov 12 2024 |
R-4.4-mac-x86_64 | WARNING | Nov 12 2024 |
R-4.4-mac-aarch64 | ERROR | Nov 12 2024 |
R-4.3-win-x86_64 | WARNING | Nov 12 2024 |
R-4.3-mac-x86_64 | WARNING | Nov 12 2024 |
R-4.3-mac-aarch64 | WARNING | Nov 12 2024 |
Exports:%*%adjmat_to_edgelistadopt_changesapprox_geodesicapprox_geodistas_dgCMatrixas_diffnetas_spmatas.dgCMatrixbass_dFbass_fbass_Fbootnetclassifyclassify_adoptersclassify_graphcompare_matrixcumulative_adopt_countdgrdiag_expanddiffmapdiffnet_check_attr_classdiffnet_to_igraphdiffnet_to_networkdiffnet_to_networkDynamicdiffnet.attrsdiffnet.attrs<-diffnet.toadiffnet.toa<-diffnetLapplydiffregdiffusionMapdrawColorKeydrop_isolatededgelist_to_adjmatedgelist_to_diffnetedges_coordsego_varianceegonet_attrsexposurefitbassgraph_powergrid_distributionhazard_rateigraph_to_diffnetigraph_vertex_rescaleinfectionis_multipleis_selfis_undirectedis_valuedisolatedleader_matchingmatrix_comparementor_matchingmorann_rewiresnedgesnetmatchnetmatch_preparenetwork_to_diffnetnetworkDynamic_to_diffnetnew_diffnetnlinksnnodesnodesnslicesnverticespermute_graphplot_adoptersplot_diffnetplot_diffnet2plot_hazardplot_infectsuscepplot_thresholdpretty_withinrdiffnetrdiffnet_multipleread_mlread_pajekread_ucinetread_ucinet_headrecoderesample_graphrescale_vertex_igraphrewire_graphrewire_permuterewire_qaprgraph_bargraph_errgraph_wsring_latticeround_to_seqselect_egoalterstruct_equivstruct_teststruct_test_asympsurvey_to_diffnetsusceptibilitythresholdtoa_difftoa_mattransformGraphByvertex_covariate_comparevertex_covariate_distvertex_mahalanobis_distvertex_rescale_igraphweighted_varwvar
Dependencies:backportsbootchkclicodacpp11dplyrfansigenericsglueigraphlatticelifecyclemagrittrMASSMatchItMatrixnetworknetworkDynamicnetworkLitepillarpkgconfigR6RcppRcppArmadilloRcppProgressrlangsnaSparseMstatnet.commontibbletidyselectutf8vctrsviridisLitewithr
netdiffuseR showcase: Medical Innovations
Rendered fromanalyzing-medical-innovation-data.Rmd
usingknitr::rmarkdown
on Nov 12 2024.Last update: 2018-03-26
Started: 2016-02-04
Not-Lost in translation: Getting diffusion data into netdiffuseR
Rendered fromnot-lost-in-translation-importing-and-exporting-graphs.Rmd
usingknitr::rmarkdown
on Nov 12 2024.Last update: 2016-10-26
Started: 2016-03-30
Simulating diffusion networks: Using the rdiffnet function
Rendered fromintroduction-to-netdiffuser.Rmd
usingknitr::rmarkdown
on Nov 12 2024.Last update: 2017-10-16
Started: 2016-01-13
Time Discounted Infection and Susceptibility
Rendered fromtime_discount_suscep_infect.Rmd
usingknitr::rmarkdown
on Nov 12 2024.Last update: 2015-12-24
Started: 2015-11-12
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Matrix multiplication | %*% %*%.default %*%.diffnet |
Approximate Geodesic Distances | approx_geodesic approx_geodist Geodesic Shortest-Path |
Coerce a matrix-like objects to 'dgCMatrix' (sparse matrix) | as.dgCMatrix as_dgCMatrix as_dgCMatrix.array as_dgCMatrix.default as_dgCMatrix.diffnet as_dgCMatrix.igraph as_dgCMatrix.list as_dgCMatrix.network as_spmat |
Coerce a diffnet graph into an array | as.array.diffnet |
Bass Model | bass bass_dF bass_F bass_f fitbass fitbass.default fitbass.diffnet plot.diffnet_bass |
Network Bootstrapping | bootnet c.diffnet_bootnet hist.diffnet_bootnet plot.diffnet_bootnet print.diffnet_bootnet resample_graph |
Brazilian Farmers | brfarmers |
'diffnet' version of the Brazilian Farmers data | brfarmersDiffNet |
Combine diffnet objects | c.diffnet |
Classify adopters accordingly to Time of Adoption and Threshold levels. | as.data.frame.diffnet_adopters classify classify_adopters classify_adopters.default classify_adopters.diffnet ftable.diffnet_adopters plot.diffnet_adopters |
Analyze an R object to identify the class of graph (if any) | classify_graph |
Cummulative count of adopters | cumulative_adopt_count |
Indegree, outdegree and degree of the vertices | degree dgr indegree outdegree plot.diffnet_degSeq |
Creates a square matrix suitable for spatial statistics models. | diag_expand diag_expand.array diag_expand.dgCMatrix diag_expand.diffnet diag_expand.list diag_expand.matrix |
Infer whether 'value' is dynamic or static. | diffnet_check_attr_class |
Indexing diffnet objects (on development) | diffnet_index [.diffnet [<-.diffnet [[.diffnet [[<-.diffnet |
'diffnet' Arithmetic and Logical Operators | &.diffnet *.diffnet -.diffnet /.diffnet diffnet-arithmetic graph_power ^.diffnet |.diffnet |
Creates a 'diffnet' class object | as.data.frame.diffnet as_diffnet as_diffnet.default as_diffnet.networkDynamic diffnet diffnet-class diffnet.attrs diffnet.attrs<- diffnet.toa diffnet.toa<- diffnetLapply dim.diffnet dimnames.diffnet is_multiple is_multiple.default is_multiple.diffnet is_self is_self.default is_self.diffnet is_undirected is_undirected.default is_undirected.diffnet is_valued is_valued.default is_valued.diffnet new_diffnet nodes print.diffnet str.diffnet t.diffnet |
Diffusion regression model | diffreg |
Diffusion Network Datasets | diffusion-data |
Creates a heatmap based on a graph layout and a vertex attribute | diffmap diffusionMap diffusionMap.default diffusionMap.diffnet image.diffnet_diffmap plot.diffnet_diffmap print.diffnet_diffmap |
Draw a color key in the current device | drawColorKey |
Conversion between adjacency matrix and edgelist | adjmat_to_edgelist edgelist_to_adjmat |
Compute ego/alter edge coordinates considering alter's size and aspect ratio | edges_coords |
Computes variance of Y at ego level | ego_variance |
Retrieve alter's attributes (network effects) | egonet_attrs |
Ego exposure | exposure |
Fake dynamic edgelist | fakeDynEdgelist |
Fake static edgelist | fakeEdgelist |
Fake survey data | fakesurvey |
Fake longitudinal survey data | fakesurveyDyn |
Distribution over a grid | grid_distribution |
Network Hazard Rate | hazard_rate plot.diffnet_hr plot_hazard plot_hazarrate |
Coercion between graph classes | diffnet_to_igraph igraph igraph_to_diffnet |
Susceptibility and Infection | infection susceptibility |
Find and remove isolated vertices | drop_isolated isolated |
Korean Family Planning | kfamily |
'diffnet' version of the Korean Family Planning data | kfamilyDiffNet |
Non-zero element-wise comparison between two sparse matrices | binary-functions compare_matrix matrix_compare |
Medical Innovation | medInnovations |
'diffnet' version of the Medical Innovation data | medInnovationsDiffNet |
Optimal Leader/Mentor Matching | leader_matching mentor_matching plot.diffnet_mentor |
Computes Moran's I correlation index | moran |
netdiffuseR | netdiffuseR-package netdiffuseR |
Network data formats | netdiffuseR-graphs |
'netdiffuseR' default options | netdiffuseR-options |
Matching Estimators with Network Data | netmatch netmatch_prepare |
Coercion between 'diffnet', 'network' and 'networkDynamic' | diffnet_to_network diffnet_to_networkDynamic network networkDynamic networkDynamic_to_diffnet network_to_diffnet |
Count the number of vertices/edges/slices in a graph | nedges nlinks nnodes nslices nvertices |
Permute the values of a matrix | CUG permute_graph QAP rewire_permute rewire_qap |
Visualize adopters and cumulative adopters | plot_adopters |
Plot the diffusion process | plot_diffnet plot_diffnet.default plot_diffnet.diffnet |
Another way of visualizing diffusion | plot_diffnet2 plot_diffnet2.default plot_diffnet2.diffnet |
Plot distribution of infect/suscep | plot_infectsuscep |
Threshold levels through time | plot_threshold plot_threshold.array plot_threshold.default plot_threshold.diffnet |
S3 plotting method for diffnet objects. | plot.diffnet |
Pretty numbers within a range. | pretty_within |
Random diffnet network | rdiffnet rdiffnet_multiple |
Read foreign graph formats | read_dl read_ml read_net read_pajek |
Reads UCINET files | read_ucinet read_ucinet_head UCINET ucinet |
Recodes an edgelist such that ids go from 1 to n | recode recode.data.frame recode.matrix |
Rescale vertex size to be used in 'plot.igraph'. | igraph_vertex_rescale rescale_vertex_igraph vertex_rescale_igraph |
Graph rewiring algorithms | rewire_graph |
Scale-free and Homophilic Random Networks | rgraph_ba scale-free |
Erdos-Renyi model | bernoulli rgraph_er |
Watts-Strogatz model | rgraph_ws small-world |
Ring lattice graph | ring_lattice |
Takes a numeric vector and maps it into a finite length sequence | round_to_seq |
Calculate the number of adoption changes between ego and alter. | adopt_changes select_egoalter summary.diffnet_adoptChanges |
Structural Equivalence | print.diffnet_se struct_equiv |
Structure dependence test | c.diffnet_struct_test hist.diffnet_struct_test n_rewires print.diffnet_struct_test struct_test struct_test_asymp |
Summary of diffnet objects | summary.diffnet |
Convert survey-like data and edgelists to a 'diffnet' object | edgelist_to_diffnet survey_to_diffnet |
Retrive threshold levels from the exposure matrix | threshold |
Difference in Time of Adoption (TOA) between individuals | toa_diff |
Time of adoption matrix | toa_mat |
Apply a function to a graph considering non-diagonal structural zeros | transformGraphBy transformGraphBy.dgCMatrix transformGraphBy.diffnet |
Comparisons at dyadic level | vertex_covariate_compare |
Computes covariate distance between connected vertices | mahalanobis minkowski p-norm vertex_covariate_dist vertex_mahalanobis_dist |
Computes weighted variance | weighted_var wvar |