Contains functions for estimating generalized parametric mixture and non-mixture cure models <doi:10.1016/j.cmpb.2022.107125>, loss of lifetime, mean residual lifetime, and crude event probabilities.

Estimate mixture cure models with subgroup survival probabilities as auxiliary information. A reference of the underlying methods is Jie Ding, Jialiang Li and Xiaoguang Wang (2024) <doi:10.1093/jrsssc/qlad106>.

Cure dependent censoring regression models for long-term survival multivariate data. These models are based on extensions of the frailty models, capable to accommodating the cure fraction and the dependence between failure and censoring times, with Weibull and piecewise exponential marginal distributions. Theoretical details regarding the models implemented in the package can be found in Schneider et al. (2022) <doi:10.1007/s10651-022-00549-0>.

Expectation-Maximization (EM) algorithm for point estimation and variance estimation to
    the nonparametric maximum likelihood estimator (NPMLE) for 
    logistic-Cox cure-rate model with left truncation and right-
    censoring. See Hou, Chambers and Xu (2017) <doi:10.1007/s10985-017-9415-2>.

Creates 'ggplot2' Cumulative Residual (CURE) plots to check the goodness-of-fit of a count model; or the tables to create a customized version. A dataset of crashes in Washington state is available for illustrative purposes.

The curl() and curl_download() functions provide highly
    configurable drop-in replacements for base url() and download.file() with
    better performance, support for encryption (https, ftps), gzip compression,
    authentication, and other 'libcurl' goodies. The core of the package implements a
    framework for performing fully customized requests where data can be processed
    either in memory, on disk, or streaming via the callback or connection
    interfaces. Some knowledge of 'libcurl' is recommended; for a more-user-friendly
    web client see the 'httr' package which builds on this package with http
    specific tools and logic.