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>.

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 (≥, 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>
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: yes
SystemRequirements: GNU make
Materials: README NEWS
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:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): reservr_0.0.3.tgz, r-oldrel (arm64): reservr_0.0.2.tgz, r-release (x86_64): reservr_0.0.3.tgz, r-oldrel (x86_64): reservr_0.0.2.tgz
Old sources: reservr archive


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