rmixgamma: Generating Random Data From A Gamma Mixture Model

In mixR: Finite Mixture Modeling for Raw and Binned Data

Description

The function rmixgamma generates random data from a Gamma mixture model.

Usage

rmixgamma(n, pi, mu, sd)

Arguments

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

Details

The number of random data from each component n_0 (a vector) is generated from a multinomial distribution Multinom(n, pi). Then the random data from each component is generated with the sample sized specified in n_0 and parameters of Gamma distributions specified in mu and sd.

Value

The function rmixgamma returns a numeric vector of random data from the specified Gamma mixture model.

See Also

rmixnormal, rmixweibull, rmixlnorm

Examples

x <- rmixgamma(1000, c(0.4, 0.6), c(2, 5), c(1, 0.5))
hist(x, breaks = 40)

mixR documentation built on June 1, 2021, 5:07 p.m.