On computing the distribution function for the Poisson binomial distribution
The Poisson binomial distribution is the distribution of the sum of independent and non-identically distributed random indicators. Each indicator follows a Bernoulli distribution and the individual probabilities of success vary. When all success probabilities are equal, the Poisson binomial distribution is a binomial distribution. The Poisson binomial distribution has many applications in different areas such as reliability, actuarial science, survey sampling, econometrics, etc. The computing of the cumulative distribution function (cdf) of the Poisson binomial distribution, however, is not straightforward. Approximation methods such as the Poisson approximation and normal approximations have been used in literature. Recursive formulae also have been used to compute the cdf in some areas. In this paper, we present a simple derivation for an exact formula with a closed-form expression for the cdf of the Poisson binomial distribution. The derivation uses the discrete Fourier transform of the characteristic function of the distribution. We develop an algorithm that efficiently implements the exact formula. Numerical studies were conducted to study the accuracy of the developed algorithm and approximation methods. We also studied the computational efficiency of different methods. The paper is concluded with a discussion on the use of different methods in practice and some suggestions for practitioners.
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- Duffie, Darrell & Saita, Leandro & Wang, Ke, 2007.
"Multi-period corporate default prediction with stochastic covariates,"
Journal of Financial Economics,
Elsevier, vol. 83(3), pages 635-665, March.
- Darrel Duffie & Leandro Saita & Ke Wang, 2005. "Multi-Period Corporate Default Prediction With Stochastic Covariates," CIRJE F-Series CIRJE-F-373, CIRJE, Faculty of Economics, University of Tokyo.
- Darrel Duffie & Leandro Saita & Ke Wang, 2005. "Multi-Period Corporate Default Prediction With Stochastic Covariates," CARF F-Series CARF-F-047, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
- Darrell Duffie & Leandro Siata & Ke Wang, 2006. "Multi-Period Corporate Default Prediction With Stochastic Covariates," NBER Working Papers 11962, National Bureau of Economic Research, Inc.
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