rmixgamma

The function <code>rmixgamma</code> generates random data from a Gamma mixture model.

Performs maximum likelihood estimation for finite mixture models for families including Normal, Weibull, Gamma and Lognormal by using EM algorithm, together with Newton-Raphson algorithm or bisection method when necessary. It also conducts mixture model selection by using information criteria or bootstrap likelihood ratio test. The data used for mixture model fitting can be raw data or binned data. The model fitting process is accelerated by using R package 'Rcpp'.

Youjiao Yu

mixR

Finite Mixture Modeling for Raw and Binned Data

rmixgamma function

<dl><dt>n</dt>
<dd>a positive integer specifying the number of observations we want to generate from the mixture model</dd>
<dt>pi</dt>
<dd>a numeric vector for the proportion of each component</dd>
<dt>mu</dt>
<dd>a numeric vector for the mean of each component</dd>
<dt>sd</dt>
<dd>a numeric vector for the standard deviation of each component</dd></dl>

Arguments

Generating Random Data From A Gamma Mixture Model — rmixgamma

<dl>

<dt>n</dt>
<dd>a positive integer specifying the number of observations we want to generate from the mixture model</dd>


<dt>pi</dt>
<dd>a numeric vector for the proportion of each component</dd>


<dt>mu</dt>
<dd>a numeric vector for the mean of each component</dd>


<dt>sd</dt>
<dd>a numeric vector for the standard deviation of each component</dd>

</dl>

rmixgamma: Generating Random Data From A Gamma Mixture Model

Description

Usage

Value

Arguments

Details

See Also

Examples