AshesITR/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>.

Getting started

Package details

Maintainer
LicenseGPL
Version0.0.3.9000
URL https://ashesitr.github.io/reservr/ https://github.com/AshesITR/reservr
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("AshesITR/reservr")
AshesITR/reservr documentation built on July 1, 2024, 4:50 p.m.