databinning

Reduce a data set to a named list of 'values' and 'freq',
which are representatives of bins and their frequencies, respectively.

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

databinning function

<dl><dt>data</dt>
<dd>A numeric vector of a data set.</dd>
<dt>bins</dt>
<dd>A positive integer to represent the number of bins.</dd></dl>

Arguments

Reduce a data set to representatives of bins and their frequencies — databinning

<dl>

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


<dt>bins</dt>
<dd>A positive integer to represent the number of bins.</dd>

</dl>

databinning: Reduce a data set to representatives of bins and their frequencies

Description

Usage

Value

Arguments

See Also

Examples