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  2. Isserlis' theorem - Wikipedia

    en.wikipedia.org/wiki/Isserlis'_theorem

    In probability theory, Isserlis' theorem or Wick's probability theorem is a formula that allows one to compute higher-order moments of the multivariate normal distribution in terms of its covariance matrix.

  3. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    In probability theory and statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is [ 2 ] [ 3 ] f ( x ) = 1 2 π σ 2 e − ( x − μ ) 2 2 σ 2 . {\displaystyle f(x)={\frac {1}{\sqrt {2\pi \sigma ^{2 ...

  4. Multivariate normal distribution - Wikipedia

    en.wikipedia.org/wiki/Multivariate_normal...

    To obtain the marginal distribution over a subset of multivariate normal random variables, one only needs to drop the irrelevant variables (the variables that one wants to marginalize out) from the mean vector and the covariance matrix. The proof for this follows from the definitions of multivariate normal distributions and linear algebra.

  5. Complex normal distribution - Wikipedia

    en.wikipedia.org/wiki/Complex_normal_distribution

    The standard complex normal random variable or standard complex Gaussian random variable is a complex random variable whose real and imaginary parts are independent normally distributed random variables with mean zero and variance /. [3]: p. 494 [4]: pp. 501 Formally,

  6. Pairwise error probability - Wikipedia

    en.wikipedia.org/wiki/Pairwise_Error_Probability

    Probability theory; Probability. Axioms; ... is a Gaussian random variable with mean 0 and variance | | ... For a zero mean, ...

  7. List of probability distributions - Wikipedia

    en.wikipedia.org/wiki/List_of_probability...

    The Bates distribution is the distribution of the mean of n independent random variables, each of which having the uniform distribution on [0,1]. The logit-normal distribution on (0,1). The Dirac delta function , although not strictly a probability distribution, is a limiting form of many continuous probability functions.

  8. Complex random variable - Wikipedia

    en.wikipedia.org/wiki/Complex_random_variable

    A typical example of a circular symmetric complex random variable is the complex Gaussian random variable with zero mean and zero pseudo-covariance matrix. A complex random variable Z {\displaystyle Z} is circularly symmetric if, for any deterministic ϕ ∈ [ − π , π ] {\displaystyle \phi \in [-\pi ,\pi ]} , the distribution of e i ϕ Z ...

  9. Cumulant - Wikipedia

    en.wikipedia.org/wiki/Cumulant

    For zero-mean random variables , …,, any mixed moment of the form () vanishes if is a partition of {, …,} which contains a singleton = {}. Hence, the expression of their joint cumulant in terms of mixed moments simplifies.