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→Evaluating the Poisson distribution
=== Evaluating the Poisson distribution ===
=== '''<font color="#ff8000"> Evaluating the Poisson distribution 计算泊松分布</font>'''===
Computing <math>P(k;\lambda)</math> for given <math>k</math> and <math>\lambda</math> is a trivial task that can be accomplished by using the standard definition of <math>P(k;\lambda)</math> in terms of exponential, power, and factorial functions. However, the conventional definition of the Poisson distribution contains two terms that can easily overflow on computers: λ<sup>''k''</sup> and ''k''!. The fraction of λ<sup>''k''</sup> to ''k''! can also produce a rounding error that is very large compared to ''e''<sup>−λ</sup>, and therefore give an erroneous result. For numerical stability the Poisson probability mass function should therefore be evaluated as
Computing <math>P(k;\lambda)</math> for given <math>k</math> and <math>\lambda</math> is a trivial task that can be accomplished by using the standard definition of <math>P(k;\lambda)</math> in terms of exponential, power, and factorial functions. However, the conventional definition of the Poisson distribution contains two terms that can easily overflow on computers: λ<sup>''k''</sup> and ''k''!. The fraction of λ<sup>''k''</sup> to ''k''! can also produce a rounding error that is very large compared to ''e''<sup>−λ</sup>, and therefore give an erroneous result. For numerical stability the Poisson probability mass function should therefore be evaluated as
* [[Mathematica]]: univariate Poisson distribution as <code>PoissonDistribution[<math>\lambda</math>]</code>,<ref name="WLPoissonRefPage">{{cite web |url = http://reference.wolfram.com/language/ref/PoissonDistribution.html |title = Wolfram Language: PoissonDistribution reference page |website = wolfram.com |access-date = 2016-04-08 }}</ref> bivariate Poisson distribution as <code>MultivariatePoissonDistribution[<math>\theta_{12}</math>,{ <math>\theta_1 - \theta_{12}</math>, <math>\theta_2 - \theta_{12}</math>}]</code>,.<ref name="WLMvPoissonRefPage">{{cite web |url = http://reference.wolfram.com/language/ref/MultivariatePoissonDistribution.html |title = Wolfram Language: MultivariatePoissonDistribution reference page |website = wolfram.com |access-date = 2016-04-08 }}</ref>
* [[Mathematica]]: univariate Poisson distribution as <code>PoissonDistribution[<math>\lambda</math>]</code>,<ref name="WLPoissonRefPage">{{cite web |url = http://reference.wolfram.com/language/ref/PoissonDistribution.html |title = Wolfram Language: PoissonDistribution reference page |website = wolfram.com |access-date = 2016-04-08 }}</ref> bivariate Poisson distribution as <code>MultivariatePoissonDistribution[<math>\theta_{12}</math>,{ <math>\theta_1 - \theta_{12}</math>, <math>\theta_2 - \theta_{12}</math>}]</code>,.<ref name="WLMvPoissonRefPage">{{cite web |url = http://reference.wolfram.com/language/ref/MultivariatePoissonDistribution.html |title = Wolfram Language: MultivariatePoissonDistribution reference page |website = wolfram.com |access-date = 2016-04-08 }}</ref>
=== Random drawing from the Poisson distribution 从泊松分布中抽取随机量===
=== Random drawing from the Poisson distribution 从泊松分布中抽取随机量===