rkolm

Random Variates for the Kolmogorov Distribution

Estimates multivariate subgaussian stable densities
and probabilities as well as generates random variates using product
distribution theory. A function for estimating the parameters from
data to fit a distribution to data is also provided, using the
method from Nolan (2013) <doi:10.1007/s00180-013-0396-7>.

Bruce Swihart

mvpd

Multivariate Product Distributions for Elliptically Contoured
Distributions

rkolm function

<dl><dt>n</dt>
<dd>the number of random variate to simulate</dd>
<dt>nterms</dt>
<dd>the number of terms in the limiting sum. That is, turning
infinity into a Big K on the top of the summation.</dd></dl>

Arguments

Random Variates for the Kolmogorov Distribution — rkolm

<dl>

<dt>n</dt>
<dd>the number of random variate to simulate</dd>


<dt>nterms</dt>
<dd>the number of terms in the limiting sum. That is, turning
infinity into a Big K on the top of the summation.</dd>

</dl>

rkolm: Random Variates for the Kolmogorov Distribution

Description

Usage

Value

Arguments

Examples