logd

A generic method to compute the log-density values
 and possibly their first derivatives with respec to theta and
 beta.

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

logd function

<dl><dt>x</dt>
<dd>an object of a class for data.</dd>
<dt>beta</dt>
<dd>instrumental parameter in a semiparametric mixture.</dd>
<dt>pt</dt>
<dd>a vector of values for the mixing variable theta.</dd>
<dt>which</dt>
<dd>an integer vector of length 3, indicating if,
respectively, the log-density values, the derivatives wrt beta
and the derivatives wrt theta are to be computed and returned if
being 1 (<code>TRUE</code>).</dd></dl>

Arguments

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

Author

Log-density and its derivative values — logd

<dl>

<dt>x</dt>
<dd>an object of a class for data.</dd>


<dt>beta</dt>
<dd>instrumental parameter in a semiparametric mixture.</dd>


<dt>pt</dt>
<dd>a vector of values for the mixing variable theta.</dd>


<dt>which</dt>
<dd>an integer vector of length 3, indicating if,
respectively, the log-density values, the derivatives wrt beta
and the derivatives wrt theta are to be computed and returned if
being 1 (<code>TRUE</code>).</dd>

</dl>

logd: Log-density and its derivative values

Description

Usage

Value

Arguments

Author