se.coef.dr

Bootstrap estimates of standard errors for the regression
 coefficients which are estimated by maximum approximate Bernstein/Beta 
 likelihood estimation method in a density ratio model based on two-sample 
 raw data.

Fit data from a continuous population with a smooth density on finite interval by an approximate Bernstein polynomial model which is a mixture of certain beta distributions and find maximum approximate Bernstein likelihood estimator of the unknown coefficients. Consequently, maximum likelihood estimates of the unknown density, distribution functions, and more can be obtained. If the support of the density is not the unit interval then transformation can be applied. This is an implementation of the methods proposed by the author of this package published in the Journal of Nonparametric Statistics: Guan (2016) <doi:10.1080/10485252.2016.1163349> and Guan (2017) <doi:10.1080/10485252.2017.1374384>. For data with covariates, under some semiparametric regression models such as Cox proportional hazards model and the accelerated failure time model, the baseline survival function can be estimated smoothly based on general interval censored data.

Zhong Guan

mable

Maximum Approximate Bernstein/Beta Likelihood Estimation

se.coef.dr function

<dl><dt>obj</dt>
<dd>Class 'mable_dr' object return by <code>mable.dr</code> or <code>mable.dr.group</code> functions</dd>
<dt>grouped</dt>
<dd>logical: are data grouped or not.</dd>
<dt>B</dt>
<dd>number of bootstrap runs.</dd>
<dt>parallel</dt>
<dd>logical: do parallel or not.</dd>
<dt>ncore</dt>
<dd>number of cores used for parallel computing. Default is half of availables.</dd>
<dt>controls</dt>
<dd>Object of class <code>mable.ctrl()</code> specifying iteration limit
and the convergence criterion for EM and Newton iterations. Default is 
<code>mable.ctrl</code>. See Details.</dd></dl>

Arguments

Standard errors of coefficients in density ratio model — se.coef.dr

<dl>

<dt>obj</dt>
<dd>Class 'mable_dr' object return by <code>mable.dr</code> or <code>mable.dr.group</code> functions</dd>


<dt>grouped</dt>
<dd>logical: are data grouped or not.</dd>


<dt>B</dt>
<dd>number of bootstrap runs.</dd>


<dt>parallel</dt>
<dd>logical: do parallel or not.</dd>


<dt>ncore</dt>
<dd>number of cores used for parallel computing. Default is half of availables.</dd>


<dt>controls</dt>
<dd>Object of class <code>mable.ctrl()</code> specifying iteration limit
and the convergence criterion for EM and Newton iterations. Default is 
<code>mable.ctrl</code>. See Details.</dd>

</dl>

se.coef.dr: Standard errors of coefficients in density ratio model

Description

Usage

Value

Arguments

Details