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>.
Version: | 0.0.3 |
Depends: | R (≥ 3.5) |
Imports: | assertthat (≥ 0.2.1), generics, glue (≥ 1.3.1), keras3, matrixStats, nloptr, numDeriv, purrr (≥ 0.3.3), R6 (≥ 2.4.1), Rcpp, RcppParallel, rlang (≥ 0.4.5), stats, utils |
LinkingTo: | BH, Rcpp, RcppArmadillo, RcppParallel |
Suggests: | covr, callr, colorspace, data.table, dplyr (≥ 0.8.4), evmix, fitdistrplus (≥ 1.0.14), flextable (≥ 0.5.8), formattable (≥ 0.2.0.1), furrr (≥ 0.1.0), ggplot2 (≥ 3.2.1), ggridges (≥ 0.5.2), knitr (≥ 1.28), logKDE (≥ 0.3.2), officer (≥ 0.3.7), patchwork (≥ 1.0.0), reticulate, rmarkdown (≥ 2.1), rstudioapi, tensorflow (≥ 2.0.0), testthat (≥ 2.1.0), tidyr (≥ 1.0.2), tibble, bench, survival, rticles, bookdown |
Published: | 2024-06-24 |
DOI: | 10.32614/CRAN.package.reservr |
Author: | Alexander Rosenstock [aut, cre, cph] |
Maintainer: | Alexander Rosenstock <alexander.rosenstock at web.de> |
BugReports: | https://github.com/AshesITR/reservr/issues |
License: | GPL-2 | GPL-3 [expanded from: GPL] |
URL: | https://ashesitr.github.io/reservr/, https://github.com/AshesITR/reservr |
NeedsCompilation: | yes |
SystemRequirements: | GNU make |
Materials: | README NEWS |
In views: | Distributions |
CRAN checks: | reservr results |
Reference manual: | reservr.pdf |
Vignettes: |
Working with Distributions Fitting Distributions and Neural Networks to Censored and Truncated Data: The R Package reservr TensorFlow Integration |
Package source: | reservr_0.0.3.tar.gz |
Windows binaries: | r-devel: reservr_0.0.3.zip, r-release: reservr_0.0.3.zip, r-oldrel: reservr_0.0.3.zip |
macOS binaries: | r-release (arm64): reservr_0.0.3.tgz, r-oldrel (arm64): reservr_0.0.3.tgz, r-release (x86_64): reservr_0.0.3.tgz, r-oldrel (x86_64): reservr_0.0.3.tgz |
Old sources: | reservr archive |
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