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  2. Split normal distribution - Wikipedia

    en.wikipedia.org/wiki/Split_Normal_Distribution

    The split normal distribution results from merging two halves of normal distributions. In a general case the 'parent' normal distributions can have different variances which implies that the joined PDF would not be continuous. To ensure that the resulting PDF integrates to 1, the normalizing constant A is used.

  3. Generalized hypergeometric function - Wikipedia

    en.wikipedia.org/wiki/Generalized_hypergeometric...

    Generalized hypergeometric functions include the (Gaussian) hypergeometric function and the confluent hypergeometric function as special cases, which in turn have many particular special functions as special cases, such as elementary functions, Bessel functions, and the classical orthogonal polynomials.

  4. SciPy - Wikipedia

    en.wikipedia.org/wiki/SciPy

    SciPy (pronounced / ˈ s aɪ p aɪ / "sigh pie" [2]) is a free and open-source Python library used for scientific computing and technical computing. [3]SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.

  5. Generalized normal distribution - Wikipedia

    en.wikipedia.org/wiki/Generalized_normal...

    The generalized normal log-likelihood function has infinitely many continuous derivates (i.e. it belongs to the class C ∞ of smooth functions) only if is a positive, even integer. Otherwise, the function has ⌊ β ⌋ {\displaystyle \textstyle \lfloor \beta \rfloor } continuous derivatives.

  6. Multivariate normal distribution - Wikipedia

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

    Hoyt distribution, the pdf of the vector length of a bivariate normally distributed vector (correlated and centered) Complex normal distribution, an application of bivariate normal distribution; Copula, for the definition of the Gaussian or normal copula model.

  7. Wrapped normal distribution - Wikipedia

    en.wikipedia.org/wiki/Wrapped_normal_distribution

    In terms of the circular variable = the circular moments of the wrapped normal distribution are the characteristic function of the normal distribution evaluated at integer arguments: z n = ∫ Γ e i n θ f W N ( θ ; μ , σ ) d θ = e i n μ − n 2 σ 2 / 2 . {\displaystyle \langle z^{n}\rangle =\int _{\Gamma }e^{in\theta }\,f_{WN}(\theta ...

  8. Gaussian function - Wikipedia

    en.wikipedia.org/wiki/Gaussian_function

    Mathematically, the derivatives of the Gaussian function can be represented using Hermite functions. For unit variance, the n-th derivative of the Gaussian is the Gaussian function itself multiplied by the n-th Hermite polynomial, up to scale. Consequently, Gaussian functions are also associated with the vacuum state in quantum field theory.

  9. Normal distribution - Wikipedia

    en.wikipedia.org/wiki/Normal_distribution

    All these extensions are also called normal or Gaussian laws, so a certain ambiguity in names exists. The multivariate normal distribution describes the Gaussian law in the k-dimensional Euclidean space. A vector X ∈ R k is multivariate-normally distributed if any linear combination of its components Σ k j=1 a j X j has a (univariate) normal ...