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  2. Poisson distribution - Wikipedia

    en.wikipedia.org/wiki/Poisson_distribution

    In probability theory and statistics, the Poisson distribution (/ ˈ p w ɑː s ɒ n /) is a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time if these events occur with a known constant mean rate and independently of the time since the last event. [1]

  3. Poisson regression - Wikipedia

    en.wikipedia.org/wiki/Poisson_regression

    In statistics, Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. [1] Poisson regression assumes the response variable Y has a Poisson distribution, and assumes the logarithm of its expected value can be modeled by a linear combination of unknown parameters.

  4. Bootstrapping (statistics) - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_(statistics)

    However, if we are not ready to make such a justification, then we can use the bootstrap instead. Using case resampling, we can derive the distribution of ¯. We first resample the data to obtain a bootstrap resample. An example of the first resample might look like this X 1 * = x 2, x 1, x 10, x 10, x 3, x 4, x 6, x 7, x 1, x 9. There are some ...

  5. Most probable number - Wikipedia

    en.wikipedia.org/wiki/Most_probable_number

    Downloadable EXCEL program for the determination of the Most Probable Numbers (MPN), their standard deviations, confidence bounds and rarity values according to Jarvis, B., Wilrich, C., and P.-T. Wilrich: Reconsideration of the derivation of Most Probable Numbers, their standard deviations, confidence bounds and rarity values.

  6. Fixed-effect Poisson model - Wikipedia

    en.wikipedia.org/wiki/Fixed-effect_Poisson_model

    Linear panel data models use the linear additivity of the fixed effects to difference them out and circumvent the incidental parameter problem. Even though Poisson models are inherently nonlinear, the use of the linear index and the exponential link function lead to multiplicative separability, more specifically [2] E[y it ∨ x i1...

  7. Skellam distribution - Wikipedia

    en.wikipedia.org/wiki/Skellam_distribution

    The probability mass function of a Poisson-distributed random variable with mean μ is given by (;) =!.for (and zero otherwise). The Skellam probability mass function for the difference of two independent counts = is the convolution of two Poisson distributions: (Skellam, 1946)

  8. Compound Poisson distribution - Wikipedia

    en.wikipedia.org/wiki/Compound_Poisson_distribution

    The shift geometric distribution is discrete compound Poisson distribution since it is a trivial case of negative binomial distribution. This distribution can model batch arrivals (such as in a bulk queue [5] [9]). The discrete compound Poisson distribution is also widely used in actuarial science for modelling the distribution of the total ...

  9. Neyman Type A distribution - Wikipedia

    en.wikipedia.org/wiki/Neyman_Type_A_distribution

    In statistics and probability, the Neyman Type A distribution is a discrete probability distribution from the family of Compound Poisson distribution.First of all, to easily understand this distribution we will demonstrate it with the following example explained in Univariate Discret Distributions; [1] we have a statistical model of the distribution of larvae in a unit area of field (in a unit ...