np_nll

Marginal log likelihood function of the nonparametric multinomial with censoring and truncation

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

np_nll function

<dl><dt>par</dt>
<dd>vector of <code>D-1</code> parameters</dd>
<dt>cens_lb</dt>
<dd>index of interval in which death occurs</dd>
<dt>cens_ub</dt>
<dd>index of interval in which death occurs (if death is observed), or else the largest interval.</dd>
<dt>trunc_lb</dt>
<dd>vector of largest index for the lower truncation</dd>
<dt>trunc_ub</dt>
<dd>vector of smallest index for the upper truncation</dd></dl>

Arguments

Marginal log likelihood function of the nonparametric multinomial with censoring and truncation — np_nll

<dl>

<dt>par</dt>
<dd>vector of <code>D-1</code> parameters</dd>


<dt>cens_lb</dt>
<dd>index of interval in which death occurs</dd>


<dt>cens_ub</dt>
<dd>index of interval in which death occurs (if death is observed), or else the largest interval.</dd>


<dt>trunc_lb</dt>
<dd>vector of largest index for the lower truncation</dd>


<dt>trunc_ub</dt>
<dd>vector of smallest index for the upper truncation</dd>

</dl>

np_nll: Marginal log likelihood function of the nonparametric multinomial with censoring and truncation

Description

Usage

Value

Arguments