datastats

Compute the mean and the standard deviation of a data set
represented by the pair of the numeric vectors <code>data</code> and optionally its
frequency vector <code>freq</code>.

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

datastats function

<dl><dt>data</dt>
<dd>A numeric vector of a data set.</dd>
<dt>freq</dt>
<dd>A frequency vector corresponding to the <code>data</code> vector.
The default value is <code>NULL</code>, which means all frequencies are one.</dd></dl>

Arguments

Compute the mean and the standard deviation of a data set — datastats

<dl>

<dt>data</dt>
<dd>A numeric vector of a data set.</dd>


<dt>freq</dt>
<dd>A frequency vector corresponding to the <code>data</code> vector.
The default value is <code>NULL</code>, which means all frequencies are one.</dd>

</dl>

datastats: Compute the mean and the standard deviation of a data set

Description

Usage

Value

Arguments

See Also

Examples