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  2. Generalized Pareto distribution - Wikipedia

    en.wikipedia.org/wiki/Generalized_Pareto...

    In statistics, the generalized Pareto distribution (GPD) is a family of continuous probability distributions. It is often used to model the tails of another distribution. It is specified by three parameters: location , scale , and shape .

  3. Scale parameter - Wikipedia

    en.wikipedia.org/wiki/Scale_parameter

    Animation showing the effects of a scale parameter on a probability distribution supported on the positive real line. Effect of a scale parameter over a mixture of two normal probability distributions. If the probability density exists for all values of the complete parameter set, then the density (as a function of the scale parameter only ...

  4. Gompertz distribution - Wikipedia

    en.wikipedia.org/wiki/Gompertz_distribution

    The Gompertz distribution is a flexible distribution that can be skewed to the right and to the left. Its hazard function = is a convex function of (;,).The model can be fitted into the innovation-imitation paradigm with = as the coefficient of innovation and as the coefficient of imitation.

  5. Nakagami distribution - Wikipedia

    en.wikipedia.org/wiki/Nakagami_distribution

    The Nakagami distribution or the Nakagami-m distribution is a probability distribution related to the gamma distribution. The family of Nakagami distributions has two parameters: a shape parameter / and a scale parameter >. It is used to model physical phenomena such as those found in medical ultrasound imaging, communications engineering ...

  6. Pearson distribution - Wikipedia

    en.wikipedia.org/wiki/Pearson_distribution

    A Pearson density p is defined to be any valid solution to the differential equation (cf. Pearson 1895, p. 381) ′ () + + + + = ()with: =, = = +, =. According to Ord, [3] Pearson devised the underlying form of Equation (1) on the basis of, firstly, the formula for the derivative of the logarithm of the density function of the normal distribution (which gives a linear function) and, secondly ...

  7. Erlang distribution - Wikipedia

    en.wikipedia.org/wiki/Erlang_distribution

    The probability density function of the Erlang distribution is (;,) = ()!,,The parameter k is called the shape parameter, and the parameter is called the rate parameter.. An alternative, but equivalent, parametrization uses the scale parameter , which is the reciprocal of the rate parameter (i.e., = /):

  8. Fréchet distribution - Wikipedia

    en.wikipedia.org/wiki/Fréchet_distribution

    The Fréchet distribution, also known as inverse Weibull distribution, [2] [3] is a special case of the generalized extreme value distribution.It has the cumulative distribution function

  9. Raised cosine distribution - Wikipedia

    en.wikipedia.org/wiki/Raised_cosine_distribution

    In probability theory and statistics, the raised cosine distribution is a continuous probability distribution supported on the interval [, +].The probability density function (PDF) is