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We consider the network structure detection for variables Y with auxiliary variables X accommodated, which are possibly subject to measurement error. The following three functions are designed to address various structures by different methods : one is NP_Graph() that is used for handling the nonlinear relationship between the responses and the covariates, another is Joint_Gaussian() that is used for correction in linear regression models via the Gaussian maximum likelihood, and the other Cond_Gaussian() is for linear regression models via conditional likelihood function.
| Version: | 0.1.0 |
| Imports: | glasso, lars, network, GGally, caret, randomForest, metrica, MASS, stats |
| Suggests: | sna |
| Published: | 2025-07-21 |
| DOI: | 10.32614/CRAN.package.PAGE |
| Author: | Wan-Yi Chang [aut, cre], Li-Pang Chen [aut] |
| Maintainer: | Wan-Yi Chang <jessica306a at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| CRAN checks: | PAGE results |
| Reference manual: | PAGE.html , PAGE.pdf |
| Package source: | PAGE_0.1.0.tar.gz |
| Windows binaries: | r-devel: PAGE_0.1.0.zip, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): PAGE_0.1.0.tgz, r-oldrel (x86_64): PAGE_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.