Doubly robust estimation for the mean of an arbitrarily transformed survival time under covariate-induced dependent left truncation and noninformative right censoring. The functions truncAIPW(), truncAIPW_cen1(), and truncAIPW_cen2() compute the doubly robust estimators under the scenario without censoring and the two censoring scenarios, respectively. The package also contains three simulated data sets 'simu', 'simu_c1', and 'simu_c2', which are used to illustrate the usage of the functions in this package.
    Reference: Wang, Y., Ying, A., Xu, R. (2022) "Doubly robust estimation under covariate-induced dependent left truncation" <arXiv:2208.06836>.

A collection of functions to deal with the truncated univariate and multivariate normal and Student distributions, described in Botev (2017) <doi:10.1111/rssb.12162> and Botev and L'Ecuyer (2015) <doi:10.1109/WSC.2015.7408180>.

Implements a systematic methodology for estimating population density from
    point-centered quarter method (PCQM) surveys when distance measurements are
    truncated by a maximum search radius (right-censored). The package provides
    a unified framework for analyzing such incomplete data, addressing both
    completely randomly distributed (Poisson) and spatially aggregated
    (Negative Binomial) populations. Key features include: (1) Adjusted
    moment-based density estimators for censored distances; (2) Maximum
    likelihood estimation (MLE) of density under the Poisson (CSR) model; and
    (3) Simultaneous MLE of density and an aggregation parameter under the
    Negative Binomial model. For more details, see Huang, Shen, Xing, and Zhao
    (2026) <doi:10.48550/arXiv.2603.08276>.

A collection of tools to evaluate probability density
        functions, cumulative distribution functions, quantile functions
        and random numbers for truncated random variables.  These functions are
        provided to also compute the expected value and variance. Nadarajah
        and Kotz (2006) developed most of the functions. QQ plots can be produced.
        All the probability functions in the stats, stats4 and evd
        packages are automatically available for truncation..