Package: netcom 2.1.6

netcom: NETwork COMparison Inference

Infer system functioning with empirical NETwork COMparisons. These methods are part of a growing paradigm in network science that uses relative comparisons of networks to infer mechanistic classifications and predict systemic interventions. They have been developed and applied in Langendorf and Burgess (2021) <doi:10.1038/s41598-021-99251-7>, Langendorf (2020) <doi:10.1201/9781351190831-6>, and Langendorf and Goldberg (2019) <arxiv:1912.12551>.

Authors:Ryan Langendorf [aut, cre], Debra Goldberg [ctb], Matthew Burgess [ctb]

netcom_2.1.6.tar.gz
netcom_2.1.6.zip(r-4.7)netcom_2.1.6.zip(r-4.6)netcom_2.1.6.zip(r-4.5)
netcom_2.1.6.tgz(r-4.6-any)netcom_2.1.6.tgz(r-4.5-any)
netcom_2.1.6.tar.gz(r-4.7-any)netcom_2.1.6.tar.gz(r-4.6-any)
netcom_2.1.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
netcom/json (API)

# Install 'netcom' in R:

install.packages('netcom', repos = c('https://langendorfr.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/langendorfr/netcom/issues

On CRAN:

4.41 score 5 stars 104 scripts 619 downloads 34 exports 70 dependencies

Last updated from:bc0b912255. Checks:8 ERROR, 1 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	ERROR	151
source / vignettes	ERROR	256
linux-release-x86_64	ERROR	146
macos-release-arm64	ERROR	116
macos-oldrel-arm64	ERROR	104
windows-devel	ERROR	93
windows-release	ERROR	72
windows-oldrel	ERROR	75
wasm-release	OK	126

Exports:%>%align best_fit_optim classify classify_Systematic compare compare_Target gini grow_DD grow_DM grow_ER grow_NM grow_PA grow_SW ics make_DD make_DM make_Mixture make_NM make_Null make_Null_canonical make_Null_mixture make_SW make_Systematic make_Systematic_canonical make_Systematic_directedCanonicalLike make_Systematic_mixture null_fit_optim stir_DD stir_DM stir_ER stir_NM stir_PA stir_SW

Dependencies:base64enc cachem cli clue cluster codetools cpp11 doParallel dplyr expm farver fastmap foreach generics GenSA ggforce ggfortify ggplot2 ggraph ggrepel glue graphlayouts gridExtra gtable igraph isoband iterators jsonlite labeling lattice lifecycle magrittr MASS Matrix memoise mgcv nlme nloptr numDeriv optimx pdist permute pillar pkgconfig plyr polyclip pracma purrr R6 RColorBrewer Rcpp RcppArmadillo reshape2 rlang S7 scales stringi stringr systemfonts tibble tidygraph tidyr tidyselect tweenr utf8 vctrs vegan viridis viridisLite withr

Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.

Help page	Topics
Network Alignment	align
Empirical parameterization	best_fit_optim
Mechanistic Network Classification	classify
Mechanistic Network Classification	classify_Systematic
Compare Networks Many-to-Many	compare
Compare Networks One-to-Many	compare_Target
Gini coefficient	gini
Grow a Duplication and Divergence Network	grow_DD
Grow a Duplication and Mutation Network	grow_DM
Grow an Erdos-Renyi Random Network	grow_ER
Grow a Niche Model Network	grow_NM
Grow a Preferential Attachment Network	grow_PA
Grow a Small-World Network	grow_SW
Induced Conserved Structure (ICS)	ics
Makes a Duplication and Divergence Network	make_DD
Make a Duplication and Mutation Network	make_DM
Make a Mixture Mechanism Network	make_Mixture
Make a Niche Model network	make_NM
Mechanism Null Distributions	make_Null
Mechanism Null Distributions	make_Null_canonical
Mechanism Null Distributions	make_Null_mixture
Makes a Small-World Network	make_SW
Systematically Make Networks	make_Systematic
Systematically Make Networks	make_Systematic_canonical
Systematically Make Networks	make_Systematic_directedCanonicalLike
Systematically Make Networks	make_Systematic_mixture
Empirical parameterization via null distributions	null_fit_optim
Sitrs a Duplication and Divergence Network	stir_DD
Stirs a Duplication and Mutation Network	stir_DM
Stir an Erdos-Renyi Random Network	stir_ER
Stirs a Niche Model Network	stir_NM
Stirs a Preferential Attachment Network	stir_PA
Stirs a Small-World Network	stir_SW

Package: netcom 2.1.6

netcom: NETwork COMparison Inference

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