Package: cluscov 1.1.0
Emmanuel S Tsyawo
cluscov: Clustered Covariate Regression
Clustered covariate regression enables estimation and inference in both linear and non-linear models with linear predictor functions even when the design matrix is column rank deficient. Routines in this package implement algorithms in Soale and Tsyawo (2019) <doi:10.13140/RG.2.2.32355.81441>.
Authors:
cluscov_1.1.0.tar.gz
cluscov_1.1.0.tar.gz(r-4.5-noble)cluscov_1.1.0.tar.gz(r-4.4-noble)
cluscov_1.1.0.tgz(r-4.4-emscripten)cluscov_1.1.0.tgz(r-4.3-emscripten)
cluscov.pdf |cluscov.html✨
cluscov/json (API)
# Install 'cluscov' in R: |
install.packages('cluscov', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:b14c66a1aa. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 20 2024 |
R-4.5-linux-x86_64 | OK | Nov 20 2024 |
Exports:c_chmodCCRlsCCRls.coordCCRseqkchmoddcluspargoldensearchgoldoptlinrclusnetdat
Dependencies:latticeMASSMatrixMatrixModelsquantregSparseMsurvival
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Concrete class constructor | c_chmod |
Sequential CCR | CCRls |
Linear regression via coordinate descent with covariate clustering | CCRls.coord |
Sequential CCR with k clusters | CCRseqk |
Model criterion function | chmod |
Regression - gammainverse class | chmod.gammainverse |
Regression - gammalog class | chmod.gammalog |
Regression - lm class | chmod.lm |
Regression - logit class | chmod.logit |
Regression - negbin class | chmod.negbin |
Regression - poissonidentity class | chmod.poissonidentity |
Regression - poissonlog class | chmod.poissonlog |
Regression - poissonsqrt class | chmod.poissonsqrt |
Regression - probit class | chmod.probit |
Regression - qreg class | chmod.qreg |
Clustering of vector elements | dcluspar |
Golden Section Search Algorithm | goldensearch |
Integer Golden Search Minimisation | goldopt |
Linear regression via coordinate descent with covariate clustering | linrclus |
Construct a network design matrix | netdat |