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  2. Symmetric derivative - Wikipedia

    en.wikipedia.org/wiki/Symmetric_derivative

    In mathematics, the symmetric derivative is an operation generalizing the ordinary derivative.. It is defined as: [1] [2] (+) (). The expression under the limit is sometimes called the symmetric difference quotient.

  3. Sigmoid function - Wikipedia

    en.wikipedia.org/wiki/Sigmoid_function

    Sigmoid curves are also common in statistics as cumulative distribution functions (which go from 0 to 1), such as the integrals of the logistic density, the normal density, and Student's t probability density functions. The logistic sigmoid function is invertible, and its inverse is the logit function.

  4. Hessian matrix - Wikipedia

    en.wikipedia.org/wiki/Hessian_matrix

    In mathematics, the Hessian matrix, Hessian or (less commonly) Hesse matrix is a square matrix of second-order partial derivatives of a scalar-valued function, or scalar field. It describes the local curvature of a function of many variables.

  5. Symmetric function - Wikipedia

    en.wikipedia.org/wiki/Symmetric_function

    In statistics, an -sample statistic (a function in variables) that is obtained by bootstrapping symmetrization of a -sample statistic, yielding a symmetric function in variables, is called a U-statistic. Examples include the sample mean and sample variance.

  6. Bell-shaped function - Wikipedia

    en.wikipedia.org/wiki/Bell-shaped_function

    The Gaussian function is the archetypal example of a bell shaped function. A bell-shaped function or simply 'bell curve' is a mathematical function having a characteristic "bell"-shaped curve.

  7. Logistic function - Wikipedia

    en.wikipedia.org/wiki/Logistic_function

    The standard logistic function is the logistic function with parameters =, =, =, which yields = + = + = / / + /.In practice, due to the nature of the exponential function, it is often sufficient to compute the standard logistic function for over a small range of real numbers, such as a range contained in [−6, +6], as it quickly converges very close to its saturation values of 0 and 1.

  8. Symmetry of second derivatives - Wikipedia

    en.wikipedia.org/wiki/Symmetry_of_second_derivatives

    The derivative of an integrable function can always be defined as a distribution, and symmetry of mixed partial derivatives always holds as an equality of distributions. The use of formal integration by parts to define differentiation of distributions puts the symmetry question back onto the test functions , which are smooth and certainly ...

  9. Symmetric probability distribution - Wikipedia

    en.wikipedia.org/wiki/Symmetric_probability...

    The distribution can be discrete or continuous, and the existence of a density is not required, but the inertia must be finite and non null. In the univariate case, this index was proposed as a non parametric test of symmetry. [2] For continuous symmetric spherical, Mir M. Ali gave the following definition.