.censTruncLimits

internal

A collection of parametric and nonparametric methods for the analysis of survival data. Parametric families implemented include Gompertz-Makeham, exponential and generalized Pareto models and extended models. The package includes an implementation of the nonparametric maximum likelihood estimator for arbitrary truncation and censoring pattern based on Turnbull (1976) <doi:10.1111/j.2517-6161.1976.tb01597.x>, along with graphical goodness-of-fit diagnostics. Parametric models for positive random variables and peaks over threshold models based on extreme value theory are described in Rootzén and Zholud (2017) <doi:10.1007/s10687-017-0305-5>; Belzile et al. (2021) <doi:10.1098/rsos.202097> and Belzile et al. (2022) <doi:10.1146/annurev-statistics-040120-025426>.

Leo Belzile

longevity

Statistical Methods for the Analysis of Excess Lifetimes

.censTruncLimits function

<dl><dt>tsets</dt>
<dd>Turnbull's sets</dd>
<dt>lcens</dt>
<dd>numeric vector of left censoring</dd>
<dt>rcens</dt>
<dd>numeric vector of right censoring</dd>
<dt>ltrunc</dt>
<dd>numeric vector of left truncation</dd>
<dt>rtrunc</dt>
<dd>numeric vector of right truncation</dd>
<dt>trunc</dt>
<dd>logical are observation truncated?</dd></dl>

Arguments

Identification sets — .censTruncLimits

<dl>

<dt>tsets</dt>
<dd>Turnbull's sets</dd>


<dt>lcens</dt>
<dd>numeric vector of left censoring</dd>


<dt>rcens</dt>
<dd>numeric vector of right censoring</dd>


<dt>ltrunc</dt>
<dd>numeric vector of left truncation</dd>


<dt>rtrunc</dt>
<dd>numeric vector of right truncation</dd>


<dt>trunc</dt>
<dd>logical are observation truncated?</dd>

</dl>

.censTruncLimits: Identification sets

Description

Usage

Value

Arguments