Efficient simulation from a gamma distribution with small shape parameter

Short Note

DOI: 10.1007/s00180-016-0692-0

Cite this article as:
Liu, C., Martin, R. & Syring, N. Comput Stat (2016). doi:10.1007/s00180-016-0692-0


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.


Acceptance rate Acceptance–rejection method Asymptotic distribution Exponential distribution R software 

Funding information

Funder NameGrant NumberFunding Note
National Science Foundation
  • DMS-1208441
  • DMS-1208833

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Department of StatisticsPurdue UniversityWest LafayetteUSA
  2. 2.Department of StatisticsNorth Carolina State UniversityRaleighUSA

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