Package: dynaTree 1.2-17
dynaTree: Dynamic Trees for Learning and Design
Inference by sequential Monte Carlo for dynamic tree regression and classification models with hooks provided for sequential design and optimization, fully online learning with drift, variable selection, and sensitivity analysis of inputs. Illustrative examples from the original dynamic trees paper (Gramacy, Taddy & Polson (2011); <doi:10.1198/jasa.2011.ap09769>) are facilitated by demos in the package; see demo(package="dynaTree").
Authors:
dynaTree_1.2-17.tar.gz
dynaTree_1.2-17.zip(r-4.5)dynaTree_1.2-17.zip(r-4.4)dynaTree_1.2-17.zip(r-4.3)
dynaTree_1.2-17.tgz(r-4.4-x86_64)dynaTree_1.2-17.tgz(r-4.4-arm64)dynaTree_1.2-17.tgz(r-4.3-x86_64)dynaTree_1.2-17.tgz(r-4.3-arm64)
dynaTree_1.2-17.tar.gz(r-4.5-noble)dynaTree_1.2-17.tar.gz(r-4.4-noble)
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dynaTree.pdf |dynaTree.html✨
dynaTree/json (API)
| # Install 'dynaTree' in R: |
| install.packages('dynaTree', repos = c('https://rbgramacy.r-universe.dev', 'https://cloud.r-project.org')) |
- elec2 - The ELEC2 Data Set
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 months agofrom:3d2c914051. Checks:OK: 9. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-win-x86_64 | OK | Oct 31 2024 |
| R-4.5-linux-x86_64 | OK | Oct 31 2024 |
| R-4.4-win-x86_64 | OK | Oct 31 2024 |
| R-4.4-mac-x86_64 | OK | Oct 31 2024 |
| R-4.4-mac-aarch64 | OK | Oct 31 2024 |
| R-4.3-win-x86_64 | OK | Oct 31 2024 |
| R-4.3-mac-x86_64 | OK | Oct 31 2024 |
| R-4.3-mac-aarch64 | OK | Oct 31 2024 |
Exports:alcalc.dynaTreealcalcalcXalcX.dynaTreecopycopy.dynaTreedeleteclouddeletecloudsdynaTreedynaTreesgetBFplotprogressqEIqEI.dynaTreeqEntropyqEntropy.dynaTreerejuvenaterejuvenate.dynaTreerelevancerelevance.dynaTreeretireretire.dynaTreesenssens.dynaTreetreestatstreestats.dynaTreevarproptotalvarproptotal.dynaTreevarpropusevarpropuse.dynaTree
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Dynamic trees for learning and design | dynaTree-package |
| Calculate the ALC or predictive entropy statistic at the X locations, or ALC at new XX predictive locations | alc.dynaTree alcX.dynaTree entropyX.dynaTree |
| Class "dynaTree" | alc alc,dynaTree-method alc-methods alcX alcX,dynaTree-method alcX-methods classprobs classprobs,dynaTree-method classprobs-methods copy copy,dynaTree-method copy-methods dynaTree-class entropyX entropyX,dynaTree-method entropyX-methods ieci ieci,dynaTree-method ieci-methods intervals intervals,dynaTree-method intervals-methods qEI,dynaTree-method qEntropy,dynaTree-method rejuvenate rejuvenate,dynaTree-method rejuvenate-methods relevance relevance,dynaTree-method relevance-methods retire retire,dynaTree-method retire-methods sameleaf sameleaf,dynaTree-method sameleaf-methods sens sens,dynaTree-method sens-methods treestats treestats,dynaTree-method treestats-methods varproptotal varproptotal,dynaTree-method varproptotal-methods varpropuse varpropuse,dynaTree-method varpropuse-methods |
| Fitting Dynamic Tree Models | dynaTree dynaTrees |
| The ELEC2 Data Set | elec2 |
| Extract a Path of (log) Bayes Factors | getBF |
| Plotting Predictive Distributions of Dynamic Tree models | plot.dynaTree |
| Prediction for Dynamic Tree Models | coef.dynaTree predict.dynaTree |
| Rejuvenate particles from the dynaTree posterior | rejuvenate.dynaTree |
| Calculate relevance statistics for input coordinates | relevance.dynaTree |
| Retire (i.e. remove) data from the a dynaTree model | retire.dynaTree |
| Monte Carlo Sensitivity Analysis for dynaTree Models | sens.dynaTree |
| Updating a Dynamic Tree Model With New Data | update.dynaTree |
| Calculate the proportion of variables used in tree splits, and average summary stats of tree heights and leaf sizes | treestats.dynaTree varproptotal.dynaTree varpropuse.dynaTree |
