mix2gauss

Dataset generated by mixture of 2 Gaussian Distributions whose density is:
$$\frac{0.3}{\sqrt{2 \pi 0.5^2}}
\exp\left(\frac{(x+1)^2}{2 \cdot 0.5^2}\right) +
\frac{0.7}{\sqrt{2 \pi 0.5^2}}
\exp\left(\frac{(x-1)^2}{2 \cdot 0.5^2}\right)$$.

datasets

The models of probability density functions are Gaussian or
exponential distributions with polynomial correction terms.
Using a maximum likelihood method, 'dsdp' computes parameters of Gaussian
or exponential distributions together with degrees of polynomials by
a grid search, and coefficient of polynomials by a variant of semidefinite
programming. It adopts Akaike Information Criterion for model selection.
See a vignette for a tutorial and more on our 'Github' repository
<https://github.com/tsuchiya-lab/dsdp/>.

Satoshi Kakihara

dsdp

Density Estimation with Semidefinite Programming

Takashi Tsuchiya

mix2gauss function

A list of numeric vectors of Bimodal Gaussian Mixture Model.<dl>
<dt>n200</dt>
<dd>A numeric vector with 200 elements.</dd><dt>n400</dt>
<dd>A numeric vector with 400 elements.</dd><dt>n600</dt>
<dd>A numeric vector with 600 elements.</dd><dt>n800</dt>
<dd>A numeric vector with 800 elements.</dd><dt>n1000</dt>
<dd>A numeric vector with 1000 elements.</dd><dt>n1200</dt>
<dd>A numeric vector with 1200 elements.</dd>
</dl>

Format

Datasets of Mixture of 2 Gaussian Distributions — mix2gauss

A list of numeric vectors of Bimodal Gaussian Mixture Model.<dl>
<dt>n200</dt>
<dd>A numeric vector with 200 elements.</dd>

<dt>n400</dt>
<dd>A numeric vector with 400 elements.</dd>

<dt>n600</dt>
<dd>A numeric vector with 600 elements.</dd>

<dt>n800</dt>
<dd>A numeric vector with 800 elements.</dd>

<dt>n1000</dt>
<dd>A numeric vector with 1000 elements.</dd>

<dt>n1200</dt>
<dd>A numeric vector with 1200 elements.</dd>


</dl>

mix2gauss: Datasets of Mixture of 2 Gaussian Distributions

Description

Usage

Arguments

Format