Package: reservr
Title: Fit Distributions and Neural Networks to Censored and Truncated
        Data
Version: 0.0.3.9000
Authors@R: 
    person(given = "Alexander",
           family = "Rosenstock",
           role = c("aut", "cre", "cph"),
           email = "alexander.rosenstock@web.de")
Description: 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>.
License: GPL
BugReports: https://github.com/AshesITR/reservr/issues
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
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
LinkingTo: BH, Rcpp, RcppArmadillo, RcppParallel
VignetteBuilder: knitr
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.1
SystemRequirements: GNU make
Collate: 'RcppExports.R' 'fit_util.R' 'distribution_class.R' 'zzz.R'
        'interval.R' 'aaa.R' 'blended_transition.R'
        'callback_adaptive_lr.R' 'callback_debug_dist_gradients.R'
        'check_lengths.R' 'compiler.R' 'dist_bdegp.R' 'dist_beta.R'
        'dist_binomial.R' 'fit_blended.R' 'dist_blended.R'
        'dist_dirac.R' 'dist_discrete.R' 'dist_empirical.R'
        'fit_erlang_mixture.R' 'dist_erlangmix.R' 'dist_exponential.R'
        'dist_gamma.R' 'gpd.R' 'dist_genpareto.R' 'dist_lognormal.R'
        'fit_mixture.R' 'dist_mixture.R' 'dist_negbinomial.R'
        'dist_normal.R' 'pareto.R' 'dist_pareto.R' 'dist_poisson.R'
        'dist_translate.R' 'dist_trunc.R' 'dist_uniform.R'
        'dist_weibull.R' 'distribution_generics.R'
        'distribution_methods.R' 'flatten_params.R' 'integrate.R'
        'plot_distributions.R' 'prob_report.R' 'reservr-package.R'
        'softmax.R' 'tf_compile.R' 'tf_compile_loss.R' 'tf_constants.R'
        'tf_fit.R' 'tf_initialise.R' 'tf_util.R'
        'trunc_erlangmix_init.R' 'trunc_obs.R' 'truncate_claims.R'
        'weighted_stats.R'
URL: https://ashesitr.github.io/reservr/,
        https://github.com/AshesITR/reservr
Config/pak/sysreqs: cmake make libpng-dev python3
Repository: https://ashesitr.r-universe.dev
Date/Publication: 2024-06-25 16:19:06 UTC
RemoteUrl: https://github.com/ashesitr/reservr
RemoteRef: HEAD
RemoteSha: 4405efdff7cc26bb30b4994f41bc7ee07271ef4a
NeedsCompilation: yes
Packaged: 2026-06-11 09:56:27 UTC; root
Author: Alexander Rosenstock [aut, cre, cph]
Maintainer: Alexander Rosenstock <alexander.rosenstock@web.de>