disc

Class <code>disc</code> is used to represent an arbitrary univariate
discrete distribution with a finite number of support points.

Mainly for maximum likelihood estimation of nonparametric
and semiparametric mixture models, but can also be used
for fitting finite mixtures. The algorithms are
developed in Wang (2007)
<doi:10.1111/j.1467-9868.2007.00583.x> and Wang (2010)
<doi:10.1007/s11222-009-9117-z>.

Yong Wang

nspmix

Nonparametric and Semiparametric Mixture Estimation

disc function

<dl><dt>pt</dt>
<dd>a numeric vector for support points.</dd>
<dt>pr</dt>
<dd>a numeric vector for probability values at the support
points.</dd>
<dt>sort</dt>
<dd>=TRUE, by default. If TRUE, support points are sorted
(in increasing order).</dd>
<dt>collapse</dt>
<dd>=TRUE, by default. If TRUE, identical support
points are collapsed, with their masses aggregated.</dd></dl>

Arguments

Yong Wang &lt;yongwang@auckland.ac.nz&gt;

Author

Class disc — disc

<dl>

<dt>pt</dt>
<dd>a numeric vector for support points.</dd>


<dt>pr</dt>
<dd>a numeric vector for probability values at the support
points.</dd>


<dt>sort</dt>
<dd>=TRUE, by default. If TRUE, support points are sorted
(in increasing order).</dd>


<dt>collapse</dt>
<dd>=TRUE, by default. If TRUE, identical support
points are collapsed, with their masses aggregated.</dd>

</dl>

disc: Class `disc`

Description

Usage

Arguments

Author

Details

See Also

Examples