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  2. Exchangeable random variables - Wikipedia

    en.wikipedia.org/wiki/Exchangeable_random_variables

    (This is the Cesàro limit of the indicator functions. In cases where the Cesàro limit does not exist this function can actually be defined as the Banach limit of the indicator functions, which is an extension of this limit. This latter limit always exists for sums of indicator functions, so that the empirical distribution is always well-defined.)

  3. Independent and identically distributed random variables

    en.wikipedia.org/wiki/Independent_and...

    Independent: Each outcome will not affect the other outcome (for from 1 to 10), which means the variables , …, are independent of each other. Identically distributed : Regardless of whether the coin is fair (with a probability of 1/2 for heads) or biased, as long as the same coin is used for each flip, the probability of getting heads remains ...

  4. Cauchy distribution - Wikipedia

    en.wikipedia.org/wiki/Cauchy_distribution

    The Cauchy distribution does not have finite moments of order greater than or equal to one; only fractional absolute moments exist. [1] The Cauchy distribution has no moment generating function . In mathematics , it is closely related to the Poisson kernel , which is the fundamental solution for the Laplace equation in the upper half-plane .

  5. Moment-generating function - Wikipedia

    en.wikipedia.org/wiki/Moment-generating_function

    In probability theory and statistics, the moment-generating function of a real-valued random variable is an alternative specification of its probability distribution.Thus, it provides the basis of an alternative route to analytical results compared with working directly with probability density functions or cumulative distribution functions.

  6. Graphon - Wikipedia

    en.wikipedia.org/wiki/Graphon

    In graph theory and statistics, a graphon (also known as a graph limit) is a symmetric measurable function : [,] [,], that is important in the study of dense graphs. Graphons arise both as a natural notion for the limit of a sequence of dense graphs, and as the fundamental defining objects of exchangeable random graph models.

  7. Lindeberg's condition - Wikipedia

    en.wikipedia.org/wiki/Lindeberg's_condition

    [1] [2] [3] Unlike the classical CLT, which requires that the random variables in question have finite variance and be both independent and identically distributed, Lindeberg's CLT only requires that they have finite variance, satisfy Lindeberg's condition, and be independent. It is named after the Finnish mathematician Jarl Waldemar Lindeberg. [4]

  8. Classification of discontinuities - Wikipedia

    en.wikipedia.org/wiki/Classification_of...

    In this case, a single limit does not exist because the one-sided limits, and + exist and are finite, but are not equal: since, +, the limit does not exist. Then, x 0 {\displaystyle x_{0}} is called a jump discontinuity , step discontinuity , or discontinuity of the first kind .

  9. Asymptotic distribution - Wikipedia

    en.wikipedia.org/wiki/Asymptotic_distribution

    In the simplest case, an asymptotic distribution exists if the probability distribution of Z i converges to a probability distribution (the asymptotic distribution) as i increases: see convergence in distribution. A special case of an asymptotic distribution is when the sequence of random variables is always zero or Z i = 0 as i approaches ...