Package: subsampling 0.1.1
subsampling: Optimal Subsampling Methods for Statistical Models
Balancing computational and statistical efficiency, subsampling techniques offer a practical solution for handling large-scale data analysis. Subsampling methods enhance statistical modeling for massive datasets by efficiently drawing representative subsamples from full dataset based on tailored sampling probabilities. These probabilities are optimized for specific goals, such as minimizing the variance of coefficient estimates or reducing prediction error.
Authors:
subsampling_0.1.1.tar.gz
subsampling_0.1.1.zip(r-4.5)subsampling_0.1.1.zip(r-4.4)subsampling_0.1.1.zip(r-4.3)
subsampling_0.1.1.tgz(r-4.4-x86_64)subsampling_0.1.1.tgz(r-4.4-arm64)subsampling_0.1.1.tgz(r-4.3-x86_64)subsampling_0.1.1.tgz(r-4.3-arm64)
subsampling_0.1.1.tar.gz(r-4.5-noble)subsampling_0.1.1.tar.gz(r-4.4-noble)
subsampling_0.1.1.tgz(r-4.4-emscripten)subsampling_0.1.1.tgz(r-4.3-emscripten)
subsampling.pdf |subsampling.html✨
subsampling/json (API)
NEWS
| # Install 'subsampling' in R: |
| install.packages('subsampling', repos = c('https://dqksnow.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/dqksnow/subsampling/issues
Last updated 20 days agofrom:10c1e6443d. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 06 2024 |
| R-4.5-win-x86_64 | OK | Nov 06 2024 |
| R-4.5-linux-x86_64 | OK | Nov 06 2024 |
| R-4.4-win-x86_64 | OK | Nov 06 2024 |
| R-4.4-mac-x86_64 | OK | Nov 06 2024 |
| R-4.4-mac-aarch64 | OK | Nov 06 2024 |
| R-4.3-win-x86_64 | OK | Nov 06 2024 |
| R-4.3-mac-x86_64 | OK | Nov 06 2024 |
| R-4.3-mac-aarch64 | OK | Nov 06 2024 |
Exports:ssp.glmssp.quantregssp.relogitssp.softmax
Dependencies:DBIexpmlatticeMASSMatrixMatrixModelsminqamitoolsnnetnumDerivquantregRcppRcppArmadilloSparseMsurveysurvival
Introduction to ssp.glm: Subsampling for Generalized Linear Models
Rendered fromssp-logit.Rmdusingknitr::rmarkdownon Nov 06 2024.Last update: 2024-10-18
Started: 2024-08-16
Introduction to ssp.quantreg: Subsampling for Quantile Regression
Rendered fromssp-quantreg.Rmdusingknitr::rmarkdownon Nov 06 2024.Last update: 2024-10-18
Started: 2024-10-14
Introduction to ssp.relogit: Subsampling for Logistic Regression Model with Rare Events
Rendered fromssp-relogit.Rmdusingknitr::rmarkdownon Nov 06 2024.Last update: 2024-10-18
Started: 2024-10-14
Introduction to ssp.softmax: Subsampling for Softmax (Multinomial) Regression Model
Rendered fromssp-softmax.Rmdusingknitr::rmarkdownon Nov 06 2024.Last update: 2024-10-18
Started: 2024-08-27
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Optimal Subsampling Methods for Generalized Linear Models | ssp.glm |
| Optimal Subsampling Methods for Quantile Regression Model | ssp.quantreg |
| Optimal Subsampling for Logistic Regression Model with Rare Events Data | ssp.relogit |
| Optimal Subsampling Method for Softmax (multinomial logistic) Regression Model | ssp.softmax |
| Optimal Subsampling Methods for Statistical Models | subsampling-package subsampling |
