mixgamma {bmixture} | R Documentation |
Mixture of Gamma distribution
Description
Random generation and density function for a finite mixture of Gamma distribution.
Usage
rmixgamma( n = 10, weight = 1, alpha = 1, beta = 1 )
dmixgamma( x, weight = 1, alpha = 1, beta = 1 )
Arguments
n |
number of observations. |
x |
vector of quantiles. |
weight |
vector of probability weights, with length equal to number of components ( |
alpha |
vector of non-negative parameters of the Gamma distribution. |
beta |
vector of non-negative parameters of the Gamma distribution. |
Details
Sampling from finite mixture of Gamma distribution, with density:
where
Value
Generated data as an vector with size .
Author(s)
Reza Mohammadi a.mohammadi@uva.nl
References
Mohammadi, A., Salehi-Rad, M. R., and Wit, E. C. (2013) Using mixture of Gamma distributions for Bayesian analysis in an M/G/1 queue with optional second service. Computational Statistics, 28(2):683-700, doi: 10.1007/s00180-012-0323-3
Mohammadi, A., and Salehi-Rad, M. R. (2012) Bayesian inference and prediction in an M/G/1 with optional second service. Communications in Statistics-Simulation and Computation, 41(3):419-435, doi: 10.1080/03610918.2011.588358
See Also
Examples
## Not run:
n = 10000
weight = c( 0.6 , 0.3 , 0.1 )
alpha = c( 100 , 200 , 300 )
beta = c( 100/3, 200/4, 300/5 )
data = rmixgamma( n = n, weight = weight, alpha = alpha, beta = beta )
hist( data, prob = TRUE, nclass = 30, col = "gray" )
x = seq( -20, 20, 0.05 )
densmixgamma = dmixnorm( x, weight, alpha, beta )
lines( x, densmixgamma, lwd = 2 )
## End(Not run)