Package: reservr 0.0.3
Alexander Rosenstock
reservr: Fit Distributions and Neural Networks to Censored and Truncated Data
Define distribution families and fit them to interval-censored and interval-truncated data, where the truncation bounds may depend on the individual observation. The defined distributions feature density, probability, sampling and fitting methods as well as efficient implementations of the log-density log f(x) and log-probability log P(x0 <= X <= x1) for use in 'TensorFlow' neural networks via the 'tensorflow' package. Allows training parametric neural networks on interval-censored and interval-truncated data with flexible parameterization. Applications include Claims Development in Non-Life Insurance, e.g. modelling reporting delay distributions from incomplete data, see Bücher, Rosenstock (2022) <doi:10.1007/s13385-022-00314-4>.
Authors:
reservr_0.0.3.tar.gz
reservr_0.0.3.tar.gz(r-4.5-noble)reservr_0.0.3.tar.gz(r-4.4-noble)
reservr_0.0.3.tgz(r-4.4-emscripten)reservr_0.0.3.tgz(r-4.3-emscripten)
reservr.pdf |reservr.html✨
reservr/json (API)
NEWS
| # Install 'reservr' in R: |
| install.packages('reservr', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ashesitr/reservr/issues
Pkgdown site:https://ashesitr.github.io
Last updated 6 months agofrom:fa7ed11875. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 22 2024 |
| R-4.5-linux-x86_64 | OK | Dec 22 2024 |
Exports:as_paramsas_trunc_obsblended_transitionblended_transition_invcallback_adaptive_lrcallback_debug_dist_gradientsdgpddist_bdegpdist_betadist_binomialdist_blendeddist_diracdist_discretedist_empiricaldist_erlangmixdist_exponentialdist_gammadist_genparetodist_genpareto1dist_lognormaldist_mixturedist_negbinomialdist_normaldist_paretodist_poissondist_translatedist_truncdist_uniformdist_weibulldparetodsoftmaxfitfit_blendedfit_distfit_dist_directfit_dist_startfit_erlang_mixturefit_mixtureflatten_boundsflatten_paramsflatten_params_matrixinflate_paramsintegrate_gkintervalinterval_intersectioninterval_unionis.Distributionis.Intervalk_matrixpgpdplot_distributionspparetoprob_reportqgpdqparetorepdel_obsrgpdrparetosoftmaxtf_compile_modeltf_initialise_modeltrunc_obstruncate_claimstruncate_obsweighted_medianweighted_momentsweighted_quantileweighted_tabulate
Dependencies:assertthatbackportsbase64encBHcliconfigfastmapgenericsglueherejsonlitekeras3latticelifecyclemagrittrMatrixmatrixStatsnloptrnumDerivpngprocessxpspurrrR6rappdirsRcppRcppArmadilloRcppParallelRcppTOMLreticulaterlangrprojrootrstudioapitensorflowtfautographtfrunstidyselectvctrswhiskerwithryamlzeallot
Fitting Distributions and Neural Networks to Censored and Truncated Data: The R Package reservr
Rendered fromjss_paper.Rmdusingknitr::rmarkdownon Dec 22 2024.Last update: 2024-06-25
Started: 2024-06-25
TensorFlow Integration
Rendered fromtensorflow.Rmdusingknitr::rmarkdownon Dec 22 2024.Last update: 2024-06-25
Started: 2022-12-09
Working with Distributions
Rendered fromdistributions.Rmdusingknitr::rmarkdownon Dec 22 2024.Last update: 2022-12-09
Started: 2022-12-09
