mphcrm.control

parameters that can be adjusted. See the <code>vignette("whatmph")</code> for more details.<ul>
<li>threads. integer. The number of threads to use. Defaults to <code>getOption('durmod.threads')</code>.</li>
<li>iters. integer. How many iterations should we maximally run. Defaults to 50.</li>
<li>ll.improve. numeric. How much must the log-likelihood improve from the last iteration before
 termination. Defaults to 0.001.</li>
<li>newpoint.maxtime. numeric. For how many seconds should a global search for a new point
 improving the likelihood be conducted before we continue with the best we have found. Defaults to
 120.</li>
<li>callback. A
 user-specified <code>function(fromwhere, opt, dataset, control,
 ...)</code> which is called after each optimization step. It can be
 used to report what is happening, check whatever it wants, and
 optionally stop the estimation by calling stop(). In this case,
 <code>mphcrm()</code> will return with the most recently estimated set
 of parameters. See the help on <code><a rd-options="" href="/link/mphcrm.callback?package=durmod&version=1.1-4" data-mini-rdoc="durmod::mphcrm.callback">mphcrm.callback</a></code> for
 information on the argument.</li>
<li>trap.interrupt. logical. Should interrupts be trapped so that <code>mphcrm</code> returns gracefully?
In this case the program will continue. Defaults to <code>interactive()</code>.</li>
<li>cluster. Cluster specification from package parallel or snow.</li>
</ul>

Modify the default estimation parameters for
 <code><a rd-options="" href="/link/mphcrm?package=durmod&version=1.1-4" data-mini-rdoc="durmod::mphcrm">mphcrm</a></code>.

Estimation of piecewise constant mixed proportional hazard competing risk model with NPMLE.
The model is described in S. Gaure et al. (2007) <doi:10.1016/j.jeconom.2007.01.015>,
J. Heckman and B. Singer (1984) <doi:10.2307/1911491>, and
B.G. Lindsay (1983) <doi:10.1214/aos/1176346059>.

Simen Gaure

durmod

Mixed Proportional Hazard Competing Risk Model

mphcrm.control function

parameters that can be adjusted. See the <code>vignette("whatmph")</code> for more details.<ul>
<li>threads. integer. The number of threads to use. Defaults to <code>getOption('durmod.threads')</code>.</li>
<li>iters. integer. How many iterations should we maximally run. Defaults to 50.</li>
<li>ll.improve. numeric. How much must the log-likelihood improve from the last iteration before
 termination. Defaults to 0.001.</li>
<li>newpoint.maxtime. numeric. For how many seconds should a global search for a new point
 improving the likelihood be conducted before we continue with the best we have found. Defaults to
 120.</li>
<li>callback. A
 user-specified <code>function(fromwhere, opt, dataset, control,
 ...)</code> which is called after each optimization step. It can be
 used to report what is happening, check whatever it wants, and
 optionally stop the estimation by calling stop(). In this case,
 <code>mphcrm()</code> will return with the most recently estimated set
 of parameters. See the help on <code><a rd-options='' href='mphcrm.callback'>mphcrm.callback</a></code> for
 information on the argument.</li>
<li>trap.interrupt. logical. Should interrupts be trapped so that <code>mphcrm</code> returns gracefully?
In this case the program will continue. Defaults to <code>interactive()</code>.</li>
<li>cluster. Cluster specification from package parallel or snow.</li>
</ul>

Modify the default estimation parameters for
 <code><a rd-options='' href='mphcrm'>mphcrm</a></code>.

mphcrm.control: Control parameters for mphcrm

Description

Usage

Arguments

Value