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Computing the noncentral gamma distribution, its inverse and the noncentrality parameter
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Abstract
The noncentral gamma distribution can be viewed as a generalization of
the noncentral chi-squared distribution and it can be expressed as a mixture of a
Poisson density function with a incomplete gamma function. The noncentral gamma
distribution is not available in free conventional statistical programs. This paper aimed
to propose an algorithm for the noncentral gamma by combining the method originally
proposed by Benton and Krishnamoorthy (Comput Stat Data Anal 43(2):249–267,
2003) for the noncentral distributions with the method of inversion of the distribution
function with respect to the noncentrality parameter using Newton–Raphson. The
algorithms are available in pseudocode and implemented as R functions. To evaluate
the accuracy and speed of computation of the algorithms implemented in R, results of
the distribution function, density function, quantiles and noncentrality parameter of the
noncentral incomplete gamma and its particular case, the noncentral chi-squared, were
obtained for the arguments settings used by Benton and Krishnamoorthy (Comput Stat
Data Anal 43(2):249–267, 2003) and Chen (J Stat Comput Simul 75(10):813–829,
2005). The implemented routines performed well and, in general, were as accurate
than other approximations. The R package denoted ncg is available to download on
the CRAN-R package repository http://cran.r-project.org/.
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OLIVEIRA, I. R. C. de; FERREIRA, D. F. Computing the noncentral gamma distribution, its inverse and the noncentrality parameter. Computational Statistics, Heidelberg, v. 28, n. 4, p. 1663–1680, Aug. 2013.
