Skellam Distribution: Discrete Probability Distribution, Probability Distribution, Statistically Independent, Random Variable - Tapa blanda

 
9786130496623: Skellam Distribution: Discrete Probability Distribution, Probability Distribution, Statistically Independent, Random Variable

Sinopsis

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. The Skellam distribution is the discrete probability distribution of the difference n1 − n2 of two statistically independent random variables n1 and n2 each having Poisson distributions with different expected values μ1 and μ2. It is useful in describing the statistics of the difference of two images with simple photon noise, as well as describing the point spread distribution in certain sports where all scored points are equal, such as baseball, hockey and soccer. The distribution is also applicable to a special case of the difference of dependent Poisson random variables, but just the obvious case where the two variables have a common additive random contribution which is cancelled by the differencing: see Karlis & Ntzoufras (2003) for details and an application.

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Reseña del editor

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. The Skellam distribution is the discrete probability distribution of the difference n1 − n2 of two statistically independent random variables n1 and n2 each having Poisson distributions with different expected values μ1 and μ2. It is useful in describing the statistics of the difference of two images with simple photon noise, as well as describing the point spread distribution in certain sports where all scored points are equal, such as baseball, hockey and soccer. The distribution is also applicable to a special case of the difference of dependent Poisson random variables, but just the obvious case where the two variables have a common additive random contribution which is cancelled by the differencing: see Karlis & Ntzoufras (2003) for details and an application.

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