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  2. Moment-generating function - Wikipedia

    en.wikipedia.org/wiki/Moment-generating_function

    As its name implies, the moment-generating function can be used to compute a distribution’s moments: the nth moment about 0 is the nth derivative of the moment-generating function, evaluated at 0. In addition to real-valued distributions (univariate distributions), moment-generating functions can be defined for vector- or matrix-valued random ...

  3. Factorial moment generating function - Wikipedia

    en.wikipedia.org/wiki/Factorial_moment...

    In probability theory and statistics, the factorial moment generating function (FMGF) of the probability distribution of a real-valued random variable X is defined as = ⁡ [] for all complex numbers t for which this expected value exists.

  4. Category:Generating functions - Wikipedia

    en.wikipedia.org/wiki/Category:Generating_functions

    Download as PDF; Printable version; ... Pages in category "Generating functions" ... Factorial moment generating function; G.

  5. Method of moments (statistics) - Wikipedia

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

    In statistics, the method of moments is a method of estimation of population parameters.The same principle is used to derive higher moments like skewness and kurtosis. It starts by expressing the population moments (i.e., the expected values of powers of the random variable under consideration) as functions of the parameters of interest.

  6. Weibull distribution - Wikipedia

    en.wikipedia.org/wiki/Weibull_distribution

    The moment generating function of the logarithm of a Weibull distributed random variable is ... "A statistical distribution function of wide applicability" (PDF), ...

  7. Factorial moment - Wikipedia

    en.wikipedia.org/wiki/Factorial_moment

    In probability theory, the factorial moment is a mathematical quantity defined as the expectation or average of the falling factorial of a random variable.Factorial moments are useful for studying non-negative integer-valued random variables, [1] and arise in the use of probability-generating functions to derive the moments of discrete random variables.

  8. Taylor expansions for the moments of functions of random ...

    en.wikipedia.org/wiki/Taylor_expansions_for_the...

    In probability theory, it is possible to approximate the moments of a function f of a random variable X using Taylor expansions, provided that f is sufficiently differentiable and that the moments of X are finite. A simulation-based alternative to this approximation is the application of Monte Carlo simulations.

  9. Probability-generating function - Wikipedia

    en.wikipedia.org/.../Probability-generating_function

    Other generating functions of random variables include the moment-generating function, the characteristic function and the cumulant generating function. The probability generating function is also equivalent to the factorial moment generating function , which as E ⁡ [ z X ] {\displaystyle \operatorname {E} \left[z^{X}\right]} can also be ...