urstab.trunc {alphastable} | R Documentation |
urstab.trunc
Description
using the methodology given by Soltan and Shirvani (2010), Shirvani and Soltani (2013) for simulating iid
truncated stable random variable, it simulates truncated stable realizations.
Usage
urstab.trunc(n, alpha, beta, sigma, mu, a, b, param)
Arguments
n |
sample size |
alpha |
tail index parameter |
beta |
skewness parameter |
sigma |
scale parameter |
mu |
location parameter |
a |
lower bound of truncation |
b |
upper bound of truncation |
param |
kind of parameterization; must be 0 or 1 for |
Value
a vector of n
numeric values
Author(s)
Mahdi Teimouri, Adel Mohammadpour, and Saralees Nadarajah
References
Shirvani, A. and Soltani, A. R. (2013). A characterization for truncated Cauchy random variables with nonzero skewness parameter, Computational Statistics, 28(3), 1011-1016.
Soltani, A. R. and Shirvani, A. (2010). Truncated stable random variables: characterization and simulation, Computational Statistics, 25(1), 155-161.
Teimouri, M. and Nadarajah, S. (2013). On simulating truncated stable random variables, Computational Statistics, 28(5), 2367-2377.
Teimouri, M. and Nadarajah, S. (2017). On simulating truncated skewed Cauchy random variables, Communications in Statistics-Simulation and Computation, 46(2), 1318-1321.
Examples
# We simulate n=200 iid realizations from truncated stable distribution with parameters
# alpha=1.3, beta=0.5, sigma=2, and mu=0 which is truncated over (-5,5) in S_0 parameterization.
urstab.trunc(200,1.3,0.5,2,0,-5,5,0)