Efficient simulation from a gamma distribution with small shape parameter

Chuanhai Liu (), Ryan Martin () and Nick Syring ()
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Chuanhai Liu: Purdue University
Ryan Martin: North Carolina State University
Nick Syring: North Carolina State University

Computational Statistics, 2017, vol. 32, issue 4, No 25, 1767-1775

Abstract: Abstract Simulating from a gamma distribution with small shape parameter is a challenging problem. Towards an efficient method, we obtain a limiting distribution for a suitably normalized gamma distribution when the shape parameter tends to zero. Then this limiting distribution provides insight to the construction of a new, simple, and highly efficient acceptance–rejection algorithm. The proposed method is fast and comparisons based on acceptance rates show that it is more efficient than existing acceptance–rejection methods.

Keywords: Acceptance rate; Acceptance–rejection method; Asymptotic distribution; Exponential distribution; R software (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s00180-016-0692-0

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