Package: netregR 1.0.1
netregR: Regression of Network Responses
Regress network responses (both directed and undirected) onto covariates of interest that may be actor-, relation-, or network-valued. In addition, compute principled variance estimates of the coefficients assuming that the errors are jointly exchangeable. Missing data is accommodated. Additionally implements building and inversion of covariance matrices under joint exchangeability, and generates random covariance matrices from this class. For more detail on methods, see Marrs, Fosdick, and McCormick (2017) <arxiv:1701.05530>.
Authors:
netregR_1.0.1.tar.gz
netregR_1.0.1.zip(r-4.5)netregR_1.0.1.zip(r-4.4)netregR_1.0.1.zip(r-4.3)
netregR_1.0.1.tgz(r-4.4-any)netregR_1.0.1.tgz(r-4.3-any)
netregR_1.0.1.tar.gz(r-4.5-noble)netregR_1.0.1.tar.gz(r-4.4-noble)
netregR_1.0.1.tgz(r-4.4-emscripten)netregR_1.0.1.tgz(r-4.3-emscripten)
netregR.pdf |netregR.html✨
netregR/json (API)
| # Install 'netregR' in R: |
| install.packages('netregR', repos = c('https://fmarrs3.r-universe.dev', 'https://cloud.r-project.org')) |
- interactions - Social interaction data set
- wolf - Wolf network data set
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:c831e31a8a. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 27 2024 |
| R-4.5-win | OK | Oct 27 2024 |
| R-4.5-linux | OK | Oct 27 2024 |
| R-4.4-win | OK | Oct 27 2024 |
| R-4.4-mac | OK | Oct 27 2024 |
| R-4.3-win | OK | Oct 27 2024 |
| R-4.3-mac | OK | Oct 27 2024 |
Exports:build_exchangeable_matrixinputs_lmnetinvert_exchangeable_matrixlmnetrphivnet
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Build an exchangeable matrix of sparseMatrix class | build_exchangeable_matrix |
| Coef S3 generic for class lmnet | coef.lmnet |
| Input preprocessing | inputs_lmnet |
| Social interaction data set | interactions |
| Invert an exchangeable matrix | invert_exchangeable_matrix |
| Linear regression for network response | lmnet |
| model.matrix S3 generic for class lmnet | model.matrix.lmnet |
| Plot S3 generic for class lmnet | plot.lmnet |
| Print S3 generic for class lmnet | print.lmnet |
| Print S3 generic for class summary.lmnet | print.summary.lmnet |
| Print S3 generic for summary.vnet object | print.summary.vnet |
| Print S3 generic for vnet object | print.vnet |
| Generate positive definite phi set | rphi |
| Summary S3 generic for class lmnet | summary.lmnet |
| Summary S3 generic for vnet object | summary.vnet |
| vcov S3 generic for class lmnet | vcov.lmnet |
| Variance computation for linear regression of network response | vhat_exch vnet |
| Wolf network data set | wolf |
