.hessian

We perform a quick check about the expected runtime and adjust the
precision accordingly.

internal

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

.hessian function

<dl><dt>f</dt>
<dd>function to compute Hessian for</dd>
<dt>x</dt>
<dd>location to evaluate Hessian at</dd>
<dt>seconds.warning</dt>
<dd>time threshold in seconds to trigger message and
reduce the number of iterations for Richardson extrapolation of
numDeriv::hessian</dd>
<dt>default.r</dt>
<dd>default number of iterations (high-precision recommendation
of numDeriv)</dd>
<dt>min.r</dt>
<dd>minial number of iteration, must be at least 2,</dd>
<dt>...</dt>
<dd>further arguments passed to method.args of numDeriv::hessian</dd></dl>

Arguments

Numerical evaluation of the hessian of a function using numDeriv::hessian — .hessian

<dl>

<dt>f</dt>
<dd>function to compute Hessian for</dd>


<dt>x</dt>
<dd>location to evaluate Hessian at</dd>


<dt>seconds.warning</dt>
<dd>time threshold in seconds to trigger message and
reduce the number of iterations for Richardson extrapolation of
numDeriv::hessian</dd>


<dt>default.r</dt>
<dd>default number of iterations (high-precision recommendation
of numDeriv)</dd>


<dt>min.r</dt>
<dd>minial number of iteration, must be at least 2,</dd>


<dt>...</dt>
<dd>further arguments passed to method.args of numDeriv::hessian</dd>

</dl>

.hessian: Numerical evaluation of the hessian of a function using numDeriv::hessian

Description

Usage

Arguments