Package: surveynnet 1.0.1
surveynnet: Neural Network for Complex Survey Data
The goal of 'surveynnet' is to extend the functionality of 'nnet', which already supports survey weights, by enabling it to handle clustered and stratified data. It achieves this by incorporating design effects through the use of effective sample sizes as outlined by Chen and Rust (2017), <doi:10.1093/jssam/smw036>, and performed by 'deffCR' in the package 'PracTools' (Valliant, Dever, and Kreuter (2018), <doi:10.1007/978-3-319-93632-1>).
Authors:
surveynnet_1.0.1.tar.gz
surveynnet_1.0.1.zip(r-4.7-any)surveynnet_1.0.1.zip(r-4.6-any)
surveynnet_1.0.1.tar.gz(r-4.7-any)surveynnet_1.0.1.tar.gz(r-4.6-any)
surveynnet_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
surveynnet/json (API)
| # Install 'surveynnet' in R: |
| install.packages('surveynnet', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/237triangle/surveynnet/issues
- body_fat - Simple body fat example data
- nhanes.demo - Nhanes example
Last updated from:2f41c9f218. Checks:6 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 99 | ||
| source / vignettes | OK | 181 | ||
| linux-release | OK | 109 | ||
| windows-devel | OK | 64 | ||
| windows-release | OK | 90 | ||
| wasm-release | OK | 122 |
Exports:surveynnet
Dependencies:classclassIntclicpp11DBIdplyre1071farvergenericsgeosphereggplot2gluegtableisobandKernSmoothlabelinglatticelifecyclemagrittrMASSMatrixminqamitoolsnnetnumDerivpillarpkgconfigPracToolsproxyR6RColorBrewerRcppRcppArmadillorlangs2S7scalessfsurveysurvivaltibbletidyselectunitsusmapusmapdatautf8vctrsviridisLitewithrwk
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Simple body fat example data | body_fat |
| Nhanes example | nhanes.demo |
| Predict response from fitted nnet, using new data | predict.surveynnet |
| Neural Net for Complex Survey Data | surveynnet |
