scalePars

The scale per parameter corresponds to the step width within the optimization path.

Fit parametric models for time-to-event data that show an initial
'incubation period', i.e., a variable delay phase where the hazard is zero. The
delayed Weibull distribution serves as foundational data model. The
specific method of 'MPSE' (maximum product of spacings estimation) and MLE-based methods are used for parameter
estimation. Bootstrap confidence intervals for parameters and significance
tests in a two group setting are provided.

Matthias Kuhn

incubate

Parametric Time-to-Event Analysis with Variable Incubation
Phases

scalePars function

<dl><dt>parV</dt>
<dd>named numeric parameter vector for optimization</dd>
<dt>lowerB</dt>
<dd>numeric. lower bound for parameter scales</dd>
<dt>upperB</dt>
<dd>numeric. upper bound for parameter scales</dd></dl>

Arguments

Calculate parameter scaling for optimization routine. — scalePars

<dl>

<dt>parV</dt>
<dd>named numeric parameter vector for optimization</dd>


<dt>lowerB</dt>
<dd>numeric. lower bound for parameter scales</dd>


<dt>upperB</dt>
<dd>numeric. upper bound for parameter scales</dd>

</dl>

scalePars: Calculate parameter scaling for optimization routine.

Description

Usage

Value

Arguments