Package: acebayes 1.10
acebayes: Optimal Bayesian Experimental Design using the ACE Algorithm
Optimal Bayesian experimental design using the approximate coordinate exchange (ACE) algorithm. See <doi:10.18637/jss.v095.i13>.
Authors:
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acebayes.pdf |acebayes.html✨
acebayes/json (API)
# Install 'acebayes' in R: |
install.packages('acebayes', repos = c('https://amo105.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 4 years agofrom:ab55851906. Checks:OK: 1 NOTE: 8. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 06 2024 |
R-4.5-win-x86_64 | NOTE | Nov 06 2024 |
R-4.5-linux-x86_64 | NOTE | Nov 06 2024 |
R-4.4-win-x86_64 | NOTE | Nov 06 2024 |
R-4.4-mac-x86_64 | NOTE | Nov 06 2024 |
R-4.4-mac-aarch64 | NOTE | Nov 06 2024 |
R-4.3-win-x86_64 | NOTE | Nov 06 2024 |
R-4.3-mac-x86_64 | NOTE | Nov 06 2024 |
R-4.3-mac-aarch64 | NOTE | Nov 06 2024 |
Exports:aceaceglmacenlmacephase1acephase2assessinideshlrnselinideshlrsiginideslrnselinideslrsigoptdesbeetleoptdescomp15badoptdescomp15sigoptdescomp15sigDRSoptdescomp18badoptdeshlrbaaoptdeshlrbadoptdeshlrnseloptdeshlrsigoptdeslinmodoptdeslrbaaoptdeslrbadoptdeslrnseloptdeslrsigpacepaceglmpacenlmutilbeetleutilcomp15badutilcomp15sigutilcomp15sigDRSutilcomp18badutilhlrbaautilhlrbadutilhlrnselutilhlrsigutilityglmutilitynlmutillinmodutillrbaautillrbadutillrnselutillrsig
Dependencies:comparelhsrandtoolboxRcppRcppArmadillorngWELL
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Optimal Bayesian Experimental Design using the Approximate Coordinate Exchange (ACE) Algorithm | acebayes-package acebayes |
Approximate Coordinate Exchange (ACE) Algorithm | ace acephase1 acephase2 pace |
Approximate Coordinate Exchange (ACE) Algorithm for Generalised Linear Models | aceglm paceglm |
Approximate Coordinate Exchange (ACE) Algorithm for Non-Linear Models | acenlm pacenlm |
Print and Summary of 'ace' and 'pace' Objects | print.ace print.pace summary.ace summary.pace |
Compares two designs under the approximate expected utility | assess assess.ace assess.pace |
Print and Summary of 'assess' Objects | print.assess summary.assess |
Functions implementing the examples of Overstall & Woods (2017). | inideshlrnsel inideshlrsig inideslrnsel inideslrsig optdesbeetle optdescomp15bad optdescomp15sig optdescomp15sigDRS optdescomp18bad optdeshlrbaa optdeshlrbad optdeshlrnsel optdeshlrsig optdeslinmod optdeslrbaa optdeslrbad optdeslrnsel optdeslrsig utilbeetle utilcomp15bad utilcomp15sig utilcomp15sigDRS utilcomp18bad utilhlrbaa utilhlrbad utilhlrnsel utilhlrsig utillinmod utillrbaa utillrbad utillrnsel utillrsig |
Plot 'ace' Objects | plot.ace plot.pace |
Plot 'assess' Objects | plot.assess |
Approximate expected utility function for generalised linear models and non-linear regression models | utilityglm utilitynlm |