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 (≥ 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

Documentation:

Reference manual:	reservr.pdf
Vignettes:	Working with Distributions Fitting Distributions and Neural Networks to Censored and Truncated Data: The R Package reservr TensorFlow Integration

Downloads:

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

Linking:

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