Package: surveynnet 1.0.0
Aaron Cohen
surveynnet: Neural Network for Complex Survey Data
The surveynnet package extends the functionality of nnet (Venables and Ripley, 2002), 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 in the calculations, performed by the package described in Valliant et al. (2023), by following the methods outlined by Chen and Rust (2017) and Valliant et al. (2018).
Authors:
surveynnet_1.0.0.tar.gz
surveynnet_1.0.0.zip(r-4.5)surveynnet_1.0.0.zip(r-4.4)surveynnet_1.0.0.zip(r-4.3)
surveynnet_1.0.0.tgz(r-4.4-any)surveynnet_1.0.0.tgz(r-4.3-any)
surveynnet_1.0.0.tar.gz(r-4.5-noble)surveynnet_1.0.0.tar.gz(r-4.4-noble)
surveynnet_1.0.0.tgz(r-4.4-emscripten)surveynnet_1.0.0.tgz(r-4.3-emscripten)
surveynnet.pdf |surveynnet.html✨
surveynnet/json (API)
# Install 'surveynnet' in R: |
install.packages('surveynnet', repos = c('https://237triangle.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 2 months agofrom:0887c40919. Checks:OK: 1 ERROR: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 10 2024 |
R-4.5-win | ERROR | Dec 10 2024 |
R-4.5-linux | ERROR | Dec 10 2024 |
R-4.4-win | ERROR | Dec 10 2024 |
R-4.4-mac | ERROR | Dec 10 2024 |
R-4.3-win | ERROR | Dec 10 2024 |
R-4.3-mac | ERROR | Dec 10 2024 |
Exports:surveynnet
Dependencies:classclassIntclicolorspaceDBIdplyre1071fansifarvergenericsgeosphereggplot2gluegtableisobandKernSmoothlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmennetpillarpkgconfigPracToolsproxyR6RColorBrewerRcpprlangs2scalessfspsurvivaltibbletidyselectunitsusmapusmapdatautf8vctrsviridisLitewithrwk
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 |