evalstep

Given a markov chain multi state model with exactly observed transition times,
sample from this chain at the observation times, giving interval censored observations (panel data).

Allows for the non-parametric estimation of transition intensities in interval-censored
multi-state models using the approach of Gomon and Putter (2024) <doi:10.48550/arXiv.2409.07176> or
Gu et al. (2023) <doi:10.1093/biomet/asad073>.

Daniel Gomon

icmstate

Interval Censored Multi-State Models

Hein Putter

evalstep function

<dl><dt>time</dt>
<dd>Times at which a transition occurs</dd>
<dt>stepf</dt>
<dd>States at which the chain is in at <code>time</code>s</dd>
<dt>newtime</dt>
<dd>Observation times of the chain, to create observed states</dd>
<dt>subst</dt>
<dd>State to return if observation time is before first transition time. Default = -Inf.</dd>
<dt>to.data.frame</dt>
<dd>Should the result be returned as a <code>data.frame</code>?</dd></dl>

Arguments

Author

Sample from a markov chain multi state model with exactly observed transition times — evalstep

<dl>

<dt>time</dt>
<dd>Times at which a transition occurs</dd>


<dt>stepf</dt>
<dd>States at which the chain is in at <code>time</code>s</dd>


<dt>newtime</dt>
<dd>Observation times of the chain, to create observed states</dd>


<dt>subst</dt>
<dd>State to return if observation time is before first transition time. Default = -Inf.</dd>


<dt>to.data.frame</dt>
<dd>Should the result be returned as a <code>data.frame</code>?</dd>

</dl>

evalstep: Sample from a markov chain multi state model with exactly observed transition times

Description

Usage

Value

Arguments

Author

Examples