AIC.fmsm

Defined as the sum of the AICs of the transition-specific models.

Flexible parametric models for time-to-event data,
including the Royston-Parmar spline model, generalized gamma and
generalized F distributions.  Any user-defined parametric
distribution can be fitted, given at least an R function defining
the probability density or hazard. There are also tools for
fitting and predicting from fully parametric multi-state models,
based on either cause-specific hazards or mixture models.

Christopher Jackson

flexsurv

Flexible Parametric Survival and Multi-State Models

Paul Metcalfe

Jordan Amdahl

Matthew T. Warkentin

Michael Sweeting

Kevin Kunzmann

AIC.fmsm function

<dl><dt>object</dt>
<dd>Object returned by <code>fmsm</code> representing a multistate model.</dd>
<dt>...</dt>
<dd>Further arguments (currently unused).</dd>
<dt>k</dt>
<dd>Penalty applied to number of parameters (defaults to the standard 2).</dd></dl>

Arguments

Akaike's information criterion from a flexible parametric multistate model — AIC.fmsm

<dl>

<dt>object</dt>
<dd>Object returned by <code>fmsm</code> representing a multistate model.</dd>


<dt>...</dt>
<dd>Further arguments (currently unused).</dd>


<dt>k</dt>
<dd>Penalty applied to number of parameters (defaults to the standard 2).</dd>

</dl>

AIC.fmsm: Akaike's information criterion from a flexible parametric multistate model

Description

Usage

Value

Arguments