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  2. Multivariate normal distribution - Wikipedia

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

    Copula, for the definition of the Gaussian or normal copula model. Multivariate t-distribution , which is another widely used spherically symmetric multivariate distribution. Multivariate stable distribution extension of the multivariate normal distribution, when the index (exponent in the characteristic function) is between zero and two.

  3. Multivariate kernel density estimation - Wikipedia

    en.wikipedia.org/wiki/Multivariate_kernel...

    We employ the Matlab routine for 2-dimensional data. The routine is an automatic bandwidth selection method specifically designed for a second order Gaussian kernel. [14] The figure shows the joint density estimate that results from using the automatically selected bandwidth. Matlab script for the example

  4. Gaussian function - Wikipedia

    en.wikipedia.org/wiki/Gaussian_function

    The peak is "well-sampled", so that less than 10% of the area or volume under the peak (area if a 1D Gaussian, volume if a 2D Gaussian) lies outside the measurement region. The width of the peak is much larger than the distance between sample locations (i.e. the detector pixels must be at least 5 times smaller than the Gaussian FWHM).

  5. Gaussian process - Wikipedia

    en.wikipedia.org/wiki/Gaussian_process

    Inference of continuous values with a Gaussian process prior is known as Gaussian process regression, or kriging; extending Gaussian process regression to multiple target variables is known as cokriging. [27] Gaussian processes are thus useful as a powerful non-linear multivariate interpolation tool. Kriging is also used to extend Gaussian ...

  6. Gaussian integral - Wikipedia

    en.wikipedia.org/wiki/Gaussian_integral

    A different technique, which goes back to Laplace (1812), [3] is the following. Let = =. Since the limits on s as y → ±∞ depend on the sign of x, it simplifies the calculation to use the fact that e −x 2 is an even function, and, therefore, the integral over all real numbers is just twice the integral from zero to infinity.

  7. Comparison of Gaussian process software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_Gaussian...

    Gaussian Uncorrelated Manually (no grad.) MAP No No No OpenTURNS; UQLab [17] Proprietary: MATLAB: Yes No No ND No Gaussian Correlated No MAP No No No UQLab; ooDACE [18] Proprietary: MATLAB: Yes No No ND No Gaussian Correlated No MAP No No No ooDACE; DACE: Proprietary: MATLAB: Yes No No ND No Gaussian No No MAP No No No DACE; GpGp: MIT: R: No No ...

  8. Ricker wavelet - Wikipedia

    en.wikipedia.org/wiki/Ricker_wavelet

    3D view of 2D Mexican hat wavelet. The multidimensional generalization of this wavelet is called the Laplacian of Gaussian function. In practice, this wavelet is sometimes approximated by the difference of Gaussians (DoG) function, because the DoG is separable [4] and can therefore save considerable computation time in two or more dimensions.

  9. 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 ...