rgammatr: Random generator for a Truncated Gamma distribution.
In LorenzoRimella/RGeode: Geometric Density Estimation

Description Usage Arguments Details Value Author(s) References Examples

View source: R/rgammatr.R

Simulate random number from a truncated Gamma distribution.

1	rgammatr(n = 1, A = 0, B = 1, range = NULL)

`n`	int, optional number of simulations.
`A`	double, optional shape parameter of the distribution.
`B`	double, optional rate parameter of the distribution.
`range`	array_like, optional domain of the distribution, where we truncate our Gamma. range(0) is the min of the range and range(1) is the max of the range.

It provide a way to simulate from a truncated Gamma distribution with given pameters A,B and range range. This will be used during the posterior sampling in th Gibbs sampler.

rgammatr returns the simulated value of the distribution:

`u`	double it is the simulated value of the truncated Gamma distribution. It will be a value in (range(0),range(1)).

L. Rimella, lorenzo.rimella@hotmail.it

[1] Y. Wang, A. Canale, D. Dunson. "Scalable Geometric Density Estimation" (2016).
The implementation of rgammatr is inspired to the Matlab implementation of gamrndtruncated by Ye Wang.

#Simulate a truncated Gamma with parameters 1,2 in the range
#1,5.
#Set the range:
range<- c(1,5)

#Simulate the truncated Gamma
set.seed(123)
vars1<-rgammatr(1000,1,2,range)

#Look at the histogram
hist(vars1,freq=FALSE,ylim=c(0,2),xlim = c(0,5))
lines(density(vars1))

#Compare with a non truncated Gamma
set.seed(123)
vars2<-rgamma(1000,1,2)


#Compare the two results
lines(density(vars2),col='red')

#Observation: simulate without range is equivalent to simulate from
#rgamma(1000,1,2)