plot.mable_reg

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

plot.mable_reg function

<dl><dt>x</dt>
<dd>a class 'mable_reg' object return by functions such as <code>mable.ph</code> which contains 
<code>M</code>, <code>coefficients</code>, <code>p</code>, <code>m</code>, <code>x0</code>, <code>tau.n</code>, <code>tau</code> 
<code>lk</code>, <code>lr</code>.</dd>
<dt>y</dt>
<dd>a new data.frame of covariate value(s) as row(s), whose columns are
arranged in the same order as in the <code>formula</code> called by the function
that returned the object <code>x</code>.</dd>
<dt>newdata</dt>
<dd>a new data.frame (ignored if <code>y</code> is included), imputed
by the working baseline <code>x0</code> if both missing.</dd>
<dt>ntime</dt>
<dd>number of evaluations of density, survival or cumulative distribution
curve to be plotted.</dd>
<dt>xlab</dt>
<dd>x-axis label</dd>
<dt>which</dt>
<dd>indicates which graphs to plot, options are 
"survival", "likelihood", "change-point", "density", or "all". If not "all", 
<code>which</code> can contain more than one options.</dd>
<dt>add</dt>
<dd>logical add to an existing plot or not</dd>
<dt>...</dt>
<dd>additional arguments to be passed to the base plot function</dd></dl>

Arguments

Author

Plot mathod for class 'mable_reg' — plot.mable_reg

<dl>

<dt>x</dt>
<dd>a class 'mable_reg' object return by functions such as <code>mable.ph</code> which contains 
<code>M</code>, <code>coefficients</code>, <code>p</code>, <code>m</code>, <code>x0</code>, <code>tau.n</code>, <code>tau</code> 
<code>lk</code>, <code>lr</code>.</dd>


<dt>y</dt>
<dd>a new data.frame of covariate value(s) as row(s), whose columns are
arranged in the same order as in the <code>formula</code> called by the function
that returned the object <code>x</code>.</dd>


<dt>newdata</dt>
<dd>a new data.frame (ignored if <code>y</code> is included), imputed
by the working baseline <code>x0</code> if both missing.</dd>


<dt>ntime</dt>
<dd>number of evaluations of density, survival or cumulative distribution
curve to be plotted.</dd>


<dt>xlab</dt>
<dd>x-axis label</dd>


<dt>which</dt>
<dd>indicates which graphs to plot, options are 
"survival", "likelihood", "change-point", "density", or "all". If not "all", 
<code>which</code> can contain more than one options.</dd>


<dt>add</dt>
<dd>logical add to an existing plot or not</dd>


<dt>...</dt>
<dd>additional arguments to be passed to the base plot function</dd>

</dl>

plot.mable_reg: Plot mathod for class 'mable_reg'

Description

Usage

Arguments

Author