rnbconv

Generates random samples from the convolution of arbitrary negative binomial random variables.

Three distinct methods are implemented for evaluating the sums of arbitrary negative binomial distributions. These methods are: Furman's exact probability mass function (Furman (2007) <doi:10.1016/j.spl.2006.06.007>), saddlepoint approximation, and a method of moments approximation. Functions are provided to calculate the density function, the distribution function and the quantile function of the convolutions in question given said evaluation methods. Functions for generating random deviates from negative binomial convolutions and for directly calculating the mean, variance, skewness, and excess kurtosis of said convolutions are also provided.

Gregory Bedwell

nbconv

Evaluate Arbitrary Negative Binomial Convolutions

rnbconv function

<dl><dt>mus</dt>
<dd>Vector of individual mean values</dd>
<dt>phis</dt>
<dd>Vector of individual dispersion parameters. Equivalent to 'size' in dnbinom.</dd>
<dt>ps</dt>
<dd>Vector of individual probabilities of success.</dd>
<dt>n.samp</dt>
<dd>The number of samples per distribution</dd>
<dt>n.cores</dt>
<dd>The number of CPU cores to use in the evaluation. Allows parallelization.</dd></dl>

Arguments

Random deviates — rnbconv

<dl>

<dt>mus</dt>
<dd>Vector of individual mean values</dd>


<dt>phis</dt>
<dd>Vector of individual dispersion parameters. Equivalent to 'size' in dnbinom.</dd>


<dt>ps</dt>
<dd>Vector of individual probabilities of success.</dd>


<dt>n.samp</dt>
<dd>The number of samples per distribution</dd>


<dt>n.cores</dt>
<dd>The number of CPU cores to use in the evaluation. Allows parallelization.</dd>

</dl>

rnbconv: Random deviates

Description

Usage

Value

Arguments

Examples