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reservr  

Fit Distributions and Neural Networks to Censored and Truncated Data
View on CRAN: Click here


Download and install reservr package within the R console
Install from CRAN:
install.packages("reservr")

Install from Github:
library("remotes")
install_github("cran/reservr")

Install by package version:
library("remotes")
install_version("reservr", "0.0.3")



Attach the package and use:
library("reservr")
Maintained by
Alexander Rosenstock
[Scholar Profile | Author Map]
First Published: 2022-12-09
Latest Update: 2023-10-18
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 B
How to cite:
Alexander Rosenstock (2022). reservr: Fit Distributions and Neural Networks to Censored and Truncated Data. R package version 0.0.3, https://cran.r-project.org/web/packages/reservr. Accessed 26 Mar. 2025.
Previous versions and publish date:
0.0.1 (2022-12-09 15:40), 0.0.2 (2023-10-18 22:50)
Other packages that cited reservr R package
View reservr citation profile
Other R packages that reservr depends, imports, suggests or enhances
Complete documentation for reservr
Functions, R codes and Examples using the reservr R package
Some associated functions: Distribution . GenPareto . Pareto . as_params . blended_transition . callback_adaptive_lr . callback_debug_dist_gradients . dist_bdegp . dist_beta . dist_binomial . dist_blended . dist_dirac . dist_discrete . dist_empirical . dist_erlangmix . dist_exponential . dist_gamma . dist_genpareto . dist_lognormal . dist_mixture . dist_negbinomial . dist_normal . dist_pareto . dist_poisson . dist_translate . dist_trunc . dist_uniform . dist_weibull . fit.reservr_keras_model . fit_blended . fit_dist . fit_dist_start . fit_erlang_mixture . fit_mixture . flatten_params . integrate_gk . interval-operations . interval . is.Distribution . k_matrix . plot_distributions . predict.reservr_keras_model . prob_report . quantile.Distribution . reexports . softmax . tf_compile_model . tf_initialise_model . trunc_obs . truncate_claims . weighted_moments . weighted_quantile . weighted_tabulate . 
Some associated R codes: RcppExports.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 . dist_blended.R . dist_dirac.R . dist_discrete.R . dist_empirical.R . dist_erlangmix.R . dist_exponential.R . dist_gamma.R . dist_genpareto.R . dist_lognormal.R . dist_mixture.R . dist_negbinomial.R . dist_normal.R . dist_pareto.R . dist_poisson.R . dist_translate.R . dist_trunc.R . dist_uniform.R . dist_weibull.R . distribution_class.R . distribution_generics.R . distribution_methods.R . fit_blended.R . fit_erlang_mixture.R . fit_mixture.R . fit_util.R . flatten_params.R . gpd.R . integrate.R . interval.R . pareto.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 . zzz.R .  Full reservr package functions and examples
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