Dirichlet: The Dirichlet Distribution
In MiSPU: Microbiome Based Sum of Powered Score (MiSPU) Tests

Description Usage Arguments Details Value Author(s) Examples

Density function and random number generation for the Dirichlet distribution

1	rdirichlet(n, alpha)

`n`	number of random observations to draw
`alpha`	the Dirichlet distribution's parameters. Can be a vector (one set of parameters for all observations) or a matrix (a different set of parameters for each observation), see “Details”

The Dirichlet distribution is a multidimensional generalization of the Beta distribution where each dimension is governed by an alpha-parameter. Formally this is

D(α)=[Γ(∑α)/∏Γ(α)]∏ y^(α-1)

Usually, alpha is a vector thus the same parameters will be used for all observations. If alpha is a matrix, a complete set of alpha-parameters must be supplied for each observation.

returns a matrix with random numbers according to the supplied alpha vector or matrix.

Chong Wu

1 2	X1 <- rdirichlet(100, c(5, 5, 10)) X1

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Type 'help( Spam)' or 'demo( spam)' for a short introduction 
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suffix '.spam' to the function name, e.g. 'help( chol.spam)'.

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