Package: treehunt 0.0.2

Jules Bangard

treehunt: Evolutionary Search for Optimal Node Combinations in Trees

Provides Markov chain Monte Carlo (MCMC) sampling and genetic algorithms for searching combinations of nodes in hierarchical trees. Includes scores for binary outcomes, continuous outcomes, and recurrent events, with applications to pharmacovigilance and hospital data. Importance weighting estimates uniform combination score references from tempered MCMC samples and reports weight-based effective sample sizes. Computational routines are implemented in C++ via 'Rcpp'.

Authors:Jules Bangard [aut, cre]

treehunt_0.0.2.tar.gz
treehunt_0.0.2.zip(r-4.7-x86_64)treehunt_0.0.2.zip(r-4.7-arm64)treehunt_0.0.2.zip(r-4.6-x86_64)treehunt_0.0.2.zip(r-4.6-arm64)
treehunt_0.0.2.tar.gz(r-4.7-arm64)treehunt_0.0.2.tar.gz(r-4.7-x86_64)treehunt_0.0.2.tar.gz(r-4.6-arm64)treehunt_0.0.2.tar.gz(r-4.6-x86_64)
treehunt_0.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
treehunt/json (API)

# Install 'treehunt' in R:
install.packages('treehunt', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/julesba-git/treehunt/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

cppopenmp

1.70 score 24 exports 5 dependencies

Last updated from:3e9eca9460. Checks:10 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK127
linux-devel-x86_64OK149
source / vignettesOK187
linux-release-arm64OK124
linux-release-x86_64OK142
windows-devel-arm64OK228
windows-devel-x86_64OK162
windows-release-arm64OK223
windows-release-x86_64OK173
wasm-releaseOK134

Exports:aggregate_ga_resultsclustering_genetic_algorithmcompute_scoredecode_treehunt_solutionsfilter_out_cocktailsfit_pwp_rao_contextget_dissimilarity_of_listget_takermap_cocktail_namesmcmc_size_2_true_score_distributionplot_ga_clustersprocess_ga_scoresrefit_pwp_combinationsrun_ga_batchrun_genetic_algorithmrun_genetic_algorithm_df_treerun_mcmcrun_mcmc_df_treerun_pwp_genetic_algorithmrun_pwp_mcmcscore_pwp_combinationssummarize_ga_pipelineuniform_score_referenceweight_ess

Dependencies:jsonlitelatticeMatrixRcppsurvival

Readme and manuals

Help Manual

Help pageTopics
Aggregate GA Results from Multiple JSON Files returned by run_ga_batchaggregate_ga_results
Clustering of a Cocktail List using DBSCAN on UMAP Projectionclustering_genetic_algorithm
Compute scores for supplied node combinationscompute_score
Decode treehunt node indexesdecode_treehunt_solutions
Filter a list of cocktails accoring to the mean depth of nodes inside each cocktail. A cocktail is kept if the mean depth of his nodes is greater than 'mean_depth_cocktail' (default = 3). This function aim is to provide more interpretable cocktail to the user.filter_out_cocktails
Fit the reduced PWP model and prepare a Rao-score contextfit_pwp_rao_context print.pwp_rao_context
Compute the dissimilarity matrix on a list of cocktailsget_dissimilarity_of_list
Identify observations covered by hierarchical combinationsget_taker
Map Cocktail Indices to Names Saved GA combinations use zero-based node indices; tree rows use one-based indices.map_cocktail_names
Run MCMC Algorithm to Compute the Score Distribution Among Node Combinations of Size 2mcmc_size_2_true_score_distribution
Plot GA Clustering Resultsplot_ga_clusters
Process and Attach GA Scores and Statistics (Generic)process_ga_scores
Refit selected combinations with patient-clustered Cox modelsrefit_pwp_combinations
Run Multiple Genetic Algorithm Replicates from Configurationrun_ga_batch
Run Genetic Algorithm for High Score Nodes Combination Searchrun_genetic_algorithm
Run Genetic Algorithm for High Score Nodes Combination Searchrun_genetic_algorithm_df_tree
Run MCMC Algorithm for Estimation of Score Distribution Among Nodes of The Treerun_mcmc
Run MCMC Algorithm for Estimation of Score Distribution Among Nodes of The Treerun_mcmc_df_tree
Run the genetic algorithm with the PWP Rao fitnessrun_pwp_genetic_algorithm
Run MCMC with the PWP Rao fitnessrun_pwp_mcmc
Evaluate full Rao statistics for combinationsscore_pwp_combinations
Complete GA Results Analysis Pipeline (Generic)summarize_ga_pipeline
Recover the uniform score reference from a tempered MCMC trajectoryuniform_score_reference
Effective sample size based on importance weightsweight_ess