Package: pECV 1.0.1
pECV: Entrywise Splitting Cross-Validation for Factor Models
Implements entrywise splitting cross-validation (ECV) and its penalized variant (pECV) for selecting the number of factors in generalized factor models.
Authors:
pECV_1.0.1.tar.gz
pECV_1.0.1.zip(r-4.7-x86_64)pECV_1.0.1.zip(r-4.7-arm64)pECV_1.0.1.zip(r-4.6-x86_64)pECV_1.0.1.zip(r-4.6-arm64)pECV_1.0.1.zip(r-4.5-x86_64)
pECV_1.0.1.tgz(r-4.6-x86_64)pECV_1.0.1.tgz(r-4.6-arm64)pECV_1.0.1.tgz(r-4.5-x86_64)pECV_1.0.1.tgz(r-4.5-arm64)
pECV_1.0.1.tar.gz(r-4.7-arm64)pECV_1.0.1.tar.gz(r-4.7-x86_64)pECV_1.0.1.tar.gz(r-4.6-arm64)pECV_1.0.1.tar.gz(r-4.6-x86_64)
pECV_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
pECV/json (API)
| # Install 'pECV' in R: |
| install.packages('pECV', repos = c('https://wzjwangzhijing.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/wangatsu/ecv/issues
Last updated from:9c207a078a. Checks:15 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 93 | ||
| linux-devel-x86_64 | OK | 117 | ||
| source / vignettes | OK | 174 | ||
| linux-release-arm64 | OK | 96 | ||
| linux-release-x86_64 | OK | 112 | ||
| macos-release-arm64 | OK | 136 | ||
| macos-release-x86_64 | OK | 379 | ||
| macos-oldrel-arm64 | OK | 165 | ||
| macos-oldrel-x86_64 | OK | 335 | ||
| windows-devel-arm64 | OK | 356 | ||
| windows-devel-x86_64 | OK | 152 | ||
| windows-release-arm64 | OK | 364 | ||
| windows-release-x86_64 | OK | 100 | ||
| windows-oldrel-x86_64 | OK | 114 | ||
| wasm-release | OK | 91 |
Exports:estimate_Cestimate_C_binarygenerate_binary_datagenerate_binary_data_missgenerate_continuous_datagenerate_continuous_data_missgenerate_count_datagenerate_count_data_misspECVpECV.miss
Dependencies:irlbalatticeMatrixRcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Estimate constraint constant C for continuous data | estimate_C |
| Estimate constraint constant C for binary data | estimate_C_binary |
| Generate binary data example | generate_binary_data |
| Generate binary data with missing values | generate_binary_data_miss |
| Generate continuous data example | generate_continuous_data |
| Generate continuous data with missing values | generate_continuous_data_miss |
| Generate count data example | generate_count_data |
| Generate count data with missing values | generate_count_data_miss |
| Entrywise Splitting Cross-Validation for Factor Models | pECV |
| Entrywise Splitting Cross-Validation with Missing Data | pECV.miss |