sinvreg

`sinvreg' is used in the examples for the <code>semimrFull</code> and <code>semimrOne</code> functions to obtain
initial values based on sliced inverse regression (Li, 1991).

Various functions are provided to estimate parametric mixture models
(with Gaussian, t, Laplace, log-concave distributions, etc.) and
non-parametric mixture models. The package performs hypothesis tests
and addresses label switching issues in mixture models.
The package also allows for parameter estimation in mixture of regressions,
proportion-varying mixture of regressions, and robust mixture of regressions.

Suyeon Kang

MixSemiRob

Mixture Models: Parametric, Semiparametric, and Robust

Xin Shen

Weixin Yao

Sijia Xiang

Yan Ge

sinvreg function

<dl><dt>x</dt>
<dd>an n by p matrix of observations where n is the number of observations and
p is the number of explanatory variables.</dd>
<dt>y</dt>
<dd>an n-dimentionsl vector of response values.</dd>
<dt>nslice</dt>
<dd>number of slices. Default is 10.</dd></dl>

Arguments

Dimension Reduction Based on Sliced Inverse Regression — sinvreg

<dl>

<dt>x</dt>
<dd>an n by p matrix of observations where n is the number of observations and
p is the number of explanatory variables.</dd>


<dt>y</dt>
<dd>an n-dimentionsl vector of response values.</dd>


<dt>nslice</dt>
<dd>number of slices. Default is 10.</dd>

</dl>

sinvreg: Dimension Reduction Based on Sliced Inverse Regression

Description

Usage

Value

Arguments

References

See Also

Examples