Package: pql 0.1.0
pql: A Partitioned Quasi-Likelihood for Distributed Statistical Inference
In the big data setting, working data sets are often distributed on multiple machines. However, classical statistical methods are often developed to solve the problems of single estimation or inference. We employ a novel parallel quasi-likelihood method in generalized linear models, to make the variances between different sub-estimators relatively similar. Estimates are obtained from projection subsets of data and later combined by suitably-chosen unknown weights. The philosophy of the package is described in Guo G. (2020) <doi:10.1007/s00180-020-00974-4>.
Authors:
pql_0.1.0.tar.gz
pql_0.1.0.zip(r-4.5)pql_0.1.0.zip(r-4.4)pql_0.1.0.zip(r-4.3)
pql_0.1.0.tgz(r-4.4-any)pql_0.1.0.tgz(r-4.3-any)
pql_0.1.0.tar.gz(r-4.5-noble)pql_0.1.0.tar.gz(r-4.4-noble)
pql_0.1.0.tgz(r-4.4-emscripten)pql_0.1.0.tgz(r-4.3-emscripten)
pql.pdf |pql.html✨
pql/json (API)
# Install 'pql' in R: |
install.packages('pql', repos = c('https://guangbaog.r-universe.dev', 'https://cloud.r-project.org')) |
The latest version of this package failed to build. Look at thebuild logs for more information.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 months agofrom:7a118bfc87. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 31 2024 |
R-4.5-win | OK | Oct 31 2024 |
R-4.5-linux | OK | Oct 31 2024 |
R-4.4-win | OK | Oct 31 2024 |
R-4.4-mac | OK | Oct 31 2024 |
R-4.3-win | OK | Oct 31 2024 |
R-4.3-mac | OK | Oct 31 2024 |
Exports:pqlBLogistpqlBpoisson1pqlBpoisson2pqlLogistpqlPoisson
Dependencies:pracma
Readme and manuals
Help Manual
Help page | Topics |
---|---|
The weighted Gauss-Newton estimators of the PQL in Logistic-GLMs | pqlBLogist |
The weight Gauss-Newton estimators of the PQL in Poisson-GLMS | pqlBpoisson1 |
The weighted Gauss-Newton estimators of the PQL in Poisson-GLMS | pqlBpoisson2 |
pqlLogist | pqlLogist |
The weighted Gauss-Newton estimators of the PQL in Poisson-GLMs | pqlPoisson |