Preprint Article Version 1 This version is not peer-reviewed

Computational Simulations of Similar Probabilistic Distributions to the Binomial and Poisson Distributions

Version 1 : Received: 6 January 2020 / Approved: 8 January 2020 / Online: 8 January 2020 (07:43:23 CET)

How to cite: Frometa-Castillo, T.; Pyakuryal, A.; Wals-Zurita, A.; Mesbahi, A. Computational Simulations of Similar Probabilistic Distributions to the Binomial and Poisson Distributions. Preprints 2020, 2020010065 (doi: 10.20944/preprints202001.0065.v1). Frometa-Castillo, T.; Pyakuryal, A.; Wals-Zurita, A.; Mesbahi, A. Computational Simulations of Similar Probabilistic Distributions to the Binomial and Poisson Distributions. Preprints 2020, 2020010065 (doi: 10.20944/preprints202001.0065.v1).

Abstract

This study has developed a Matlab application for simulating statistical models project (SMp) probabilistic distributions that are similar to binomial and Poisson, which were created by mathematical procedures. The simulated distributions are graphically compared with these popular distributions. The application allows to obtain many probabilistic distributions, and shows the trend (τ ) for n trials with success probability p, i.e. the maximum probability as τ=np. While the Poisson distribution PD(x;µ) is a unique probabilistic distribution, where PD=0 in x=+∞, the application simulates many SMp(x;µ,Xmax) distributions, where µ is the Poisson parameter and value of x with generally the maximum probability, and Xmax is the upper limit of x with SMp(x;µ,Xmax) ≥ 0 and limit of the stochastic region of a random discrete variable. It is shown that by simulation via, one can get many and better probabilistic distributions than by mathematical one.

Subject Areas

simulation; binomial distribution; Poisson distribution; stochastic process; modelling

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