gehan_poly_estimation

Estimates regression parameters by optimizing a smoothed version of Gehan's statistic.

Implements several basic algorithms for estimating regression parameters for semiparametric accelerated failure time (AFT) model. The main methods are: Jin rank-based method (Jin (2003) <doi:10.1093/biomet/90.2.341>), Heller’s estimating method (Heller (2012) <doi:10.1198/016214506000001257>), Polynomial smoothed Gehan function method (Chung (2013) <doi:10.1007/s11222-012-9333-9>), Buckley-James method (Buckley (1979) <doi:10.2307/2335161>) and Jin`s improved least squares method (Jin (2006) <doi:10.1093/biomet/93.1.147>). This package can be used for modeling right-censored data and for comparing different estimation algorithms.

Martin Benedikt

aftsem

Semiparametric Accelerated Failure Time Model

gehan_poly_estimation function

<dl><dt>y</dt>
<dd>A numeric vector of the response variable, survival times.</dd>
<dt>Z</dt>
<dd>A matrix of covariates.</dd>
<dt>delta</dt>
<dd>A censoring indicator vector where 1 indicates an uncensored observation and 0 indicates a censored observation.</dd>
<dt>binit</dt>
<dd>Initial values for the beta coefficients.</dd>
<dt>epsilon</dt>
<dd>Smoothing parameter.</dd>
<dt>optimx.alg</dt>
<dd>Optimalization algorithm that will be used (see optimx package documentation for more information)</dd>
<dt>use.grad</dt>
<dd>Indicator wheter numerical or excact gradient will be used, default is FALSE == numerical</dd></dl>

Arguments

Estimation of Regression Parameters from Smoothed Gehan Function — gehan_poly_estimation

<dl>

<dt>y</dt>
<dd>A numeric vector of the response variable, survival times.</dd>


<dt>Z</dt>
<dd>A matrix of covariates.</dd>


<dt>delta</dt>
<dd>A censoring indicator vector where 1 indicates an uncensored observation and 0 indicates a censored observation.</dd>


<dt>binit</dt>
<dd>Initial values for the beta coefficients.</dd>


<dt>epsilon</dt>
<dd>Smoothing parameter.</dd>


<dt>optimx.alg</dt>
<dd>Optimalization algorithm that will be used (see optimx package documentation for more information)</dd>


<dt>use.grad</dt>
<dd>Indicator wheter numerical or excact gradient will be used, default is FALSE == numerical</dd>

</dl>

gehan_poly_estimation: Estimation of Regression Parameters from Smoothed Gehan Function

Description

Usage

Value

Arguments

Details