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  2. 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 ...

  3. GPOPS-II - Wikipedia

    en.wikipedia.org/wiki/GPOPS-II

    GPOPS-II (pronounced "GPOPS 2") is a general-purpose MATLAB software for solving continuous optimal control problems using hp-adaptive Gaussian quadrature collocation and sparse nonlinear programming.

  4. PottersWheel - Wikipedia

    en.wikipedia.org/wiki/PottersWheel

    PottersWheel is a MATLAB toolbox for mathematical modeling of time-dependent dynamical systems that can be expressed as chemical reaction networks or ordinary differential equations (ODEs). [1] It allows the automatic calibration of model parameters by fitting the model to experimental measurements.

  5. Curve fitting - Wikipedia

    en.wikipedia.org/wiki/Curve_fitting

    Curve fitting [1] [2] is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, [3] possibly subject to constraints. [ 4 ] [ 5 ] Curve fitting can involve either interpolation , [ 6 ] [ 7 ] where an exact fit to the data is required, or smoothing , [ 8 ] [ 9 ] in which a "smooth ...

  6. Multivariate kernel density estimation - Wikipedia

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

    We consider estimating the density of the Gaussian mixture (4π) −1 exp(− 1 ⁄ 2 (x 1 2 + x 2 2)) + (4π) −1 exp(− 1 ⁄ 2 ((x 1 - 3.5) 2 + x 2 2)), from 500 randomly generated points. We employ the Matlab routine for 2-dimensional data. The routine is an automatic bandwidth selection method specifically designed for a second order ...

  7. Levenberg–Marquardt algorithm - Wikipedia

    en.wikipedia.org/wiki/Levenberg–Marquardt...

    The primary application of the Levenberg–Marquardt algorithm is in the least-squares curve fitting problem: given a set of empirical pairs (,) of independent and dependent variables, find the parameters ⁠ ⁠ of the model curve (,) so that the sum of the squares of the deviations () is minimized:

  8. Gaussian process - Wikipedia

    en.wikipedia.org/wiki/Gaussian_process

    GPML: A comprehensive Matlab toolbox for GP regression and classification; STK: a Small (Matlab/Octave) Toolbox for Kriging and GP modeling; Kriging module in UQLab framework (Matlab) CODES Toolbox: implementations of Kriging, variational kriging and multi-fidelity models (Matlab) Matlab/Octave function for stationary Gaussian fields

  9. Phase-type distribution - Wikipedia

    en.wikipedia.org/wiki/Phase-type_distribution

    BuTools a MATLAB and Mathematica script for fitting phase-type distributions to 3 specified moments; momentmatching a MATLAB script to fit a minimal phase-type distribution to 3 specified moments [6] KPC-toolbox a library of MATLAB scripts to fit empirical datasets to Markovian arrival processes and phase-type distributions. [7]