rgamma_c

Returns a sample from a gamma-distributed random variable.
The function uses the Marsaglia-Tsang fast gamma method used to generate
the random samples. See more details below. The name was chosen so it
doesn't clash with R's native method.

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

rgamma_c function

<dl><dt>n</dt>
<dd>(int)</dd>
<dt>b</dt>
<dd>(numeric) - shape parameter. Must be in the range \((0, \infty)\).</dd>
<dt>a</dt>
<dd>(numeric) - scale parameter. Must be in the range \((0, \infty)\).</dd></dl>

Arguments

Generates a Gamma-distributed sample — rgamma_c

<dl>

<dt>n</dt>
<dd>(int)</dd>


<dt>b</dt>
<dd>(numeric) - shape parameter. Must be in the range \((0, \infty)\).</dd>


<dt>a</dt>
<dd>(numeric) - scale parameter. Must be in the range \((0, \infty)\).</dd>

</dl>

rgamma_c: Generates a Gamma-distributed sample

Description

Usage

Value

Arguments

Details

Examples