subbofish

Calculate the standard errors, the correlation, the
Fisher Information matrix and its inverse for a power exponential density
with given parameters

Create densities, probabilities, random numbers, quantiles, and maximum likelihood estimation for several
distributions, mainly the symmetric and asymmetric power exponential (AEP), a.k.a. the Subbottin family of
distributions, also known as the generalized error distribution.
Estimation is made using the design of Bottazzi (2004) <https://ideas.repec.org/p/ssa/lemwps/2004-14.html>, where
the likelihood is maximized by several optimization procedures using the 'GNU Scientific Library (GSL)', translated to 'C++'
code, which makes it both fast and accurate. The package also provides methods for the gamma, Laplace, and Asymmetric
Laplace distributions.

Elias Haddad

Rsubbotools

Fast Estimation of Subbottin and AEP Distributions (Generalized
Error Distribution)

Giulio  Bottazzi

Fernando J.  Von Zuben

Jochen  Voss

J.D.  Lamb

Brian  Gough

subbofish function

<dl><dt>size</dt>
<dd>numeric - number of observations (Default: 01)</dd>
<dt>b</dt>
<dd>numeric - the exponent b (Default: 2.0)</dd>
<dt>m</dt>
<dd>numeric - the location parameter (Default: 0.0)</dd>
<dt>a</dt>
<dd>numeric - the scale parameter (Default: 1.0)</dd>
<dt>O_munknown</dt>
<dd>numeric - if true assumes m known</dd></dl>

Arguments

Return the Fisher Information Matrix for the Subbotin Distribution — subbofish

<dl>

<dt>size</dt>
<dd>numeric - number of observations (Default: 01)</dd>


<dt>b</dt>
<dd>numeric - the exponent b (Default: 2.0)</dd>


<dt>m</dt>
<dd>numeric - the location parameter (Default: 0.0)</dd>


<dt>a</dt>
<dd>numeric - the scale parameter (Default: 1.0)</dd>


<dt>O_munknown</dt>
<dd>numeric - if true assumes m known</dd>

</dl>

subbofish: Return the Fisher Information Matrix for the Subbotin Distribution

Description

Usage

Value

Arguments