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  2. 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. [26] Gaussian processes are thus useful as a powerful non-linear multivariate interpolation tool. Kriging is also used to extend Gaussian ...

  3. Gaussian function - Wikipedia

    en.wikipedia.org/wiki/Gaussian_function

    The product of two Gaussian functions is a Gaussian, and the convolution of two Gaussian functions is also a Gaussian, with variance being the sum of the original variances: = +. The product of two Gaussian probability density functions (PDFs), though, is not in general a Gaussian PDF.

  4. Kernel density estimation - Wikipedia

    en.wikipedia.org/wiki/Kernel_density_estimation

    In Analytica release 4.4, the Smoothing option for PDF results uses KDE, and from expressions it is available via the built-in Pdf function. In C/C++, FIGTree is a library that can be used to compute kernel density estimates using normal kernels. MATLAB interface available. In C++, libagf is a library for variable kernel density estimation.

  5. Exponentially modified Gaussian distribution - Wikipedia

    en.wikipedia.org/wiki/Exponentially_modified...

    In probability theory, an exponentially modified Gaussian distribution (EMG, also known as exGaussian distribution) describes the sum of independent normal and exponential random variables. An exGaussian random variable Z may be expressed as Z = X + Y , where X and Y are independent, X is Gaussian with mean μ and variance σ 2 , and Y is ...

  6. 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 ...

  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. Gabor transform - Wikipedia

    en.wikipedia.org/wiki/Gabor_transform

    The function to be transformed is first multiplied by a Gaussian function, which can be regarded as a window function, and the resulting function is then transformed with a Fourier transform to derive the time-frequency analysis. [1] The window function means that the signal near the time being analyzed will have higher weight.

  9. Matrix normal distribution - Wikipedia

    en.wikipedia.org/wiki/Matrix_normal_distribution

    The probability density function for the random matrix X (n × p) that follows the matrix normal distribution , (,,) has the form: (,,) = ⁡ ([() ()]) / | | / | | /where denotes trace and M is n × p, U is n × n and V is p × p, and the density is understood as the probability density function with respect to the standard Lebesgue measure in , i.e.: the measure corresponding to integration ...