.turnbull_em_dtrunc

Turnbull EM algorithm (low storage implementation)

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

.turnbull_em_dtrunc 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>weights</dt>
<dd>vector of weights for observations</dd>
<dt>cens</dt>
<dd>logical; if <code>FALSE</code>, then <code>censUpp = censLow</code> and a particular update can be avoided in the EM algorithm</dd>
<dt>tol</dt>
<dd>tolerance level for terminating the EM algorithm</dd>
<dt>maxiter</dt>
<dd>maximum number of iteration for the EM algorithm</dd></dl>

Arguments

Turnbull EM algorithm (low storage implementation) — .turnbull_em_dtrunc

<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>weights</dt>
<dd>vector of weights for observations</dd>


<dt>cens</dt>
<dd>logical; if <code>FALSE</code>, then <code>censUpp = censLow</code> and a particular update can be avoided in the EM algorithm</dd>


<dt>tol</dt>
<dd>tolerance level for terminating the EM algorithm</dd>


<dt>maxiter</dt>
<dd>maximum number of iteration for the EM algorithm</dd>

</dl>

.turnbull_em_dtrunc: Turnbull EM algorithm (low storage implementation)

Description

Usage

Value

Arguments