Nonlinear Least Squares Fitting

I need to thank Duane Hanselman for suggesting this great idea.Fminspleas is a simple nonlinear least squares tool that fits regression models of the formY = a1*f1(X,C) + a2*f2(X,C) + ... + an*fn(X,C)X can be any array, so it works on multidimensionalproblems, and C is the set of only...

DataFitting is a powerful statistical analysis program that performs linear and nonlinear regression analysis (i.e. curve fitting). DataFitting determines the values of parameters for an equation, whose form you specify, that cause the equation to best fit a set of data values. DataFitting can...

CurveFitter performs statistical regression analysis to estimate the values of parameters for linear, multivariate, polynomial, exponential and nonlinear functions. The regression analysis determines the values of the parameters that cause the function to best fit the observed data that you...


Platforms: Windows, Windows 7, Other

CurveFitter program performs statistical regression analysis to estimate the values of parameters for linear, multivariate, polynomial, exponential and nonlinear functions. The regression analysis determines the values of the parameters that cause the function to best fit the observed data that...


Platforms: Windows, Other

CurveFitter performs statistical regression analysis to estimate the values of parameters for linear, multivariate, polynomial, exponential and nonlinear functions. The regression analysis determines the values of the parameters that cause the function to best fit the observed data that you...


Platforms: Windows, Windows 7, Other

How to fit a 2D Gaussian function to noisy data in Matlab? Or data with another number of dimensions and arbitrary fit function?It took me a while to find out how Matlab does this by the functions lsqcurvefit, fmincon or fminsearch. This project demonstrates how to use these functions to fit ND...


Platforms: Matlab

FindGraph is a comprehensive graphing, curve fitting, and digitizing tool. FindGraph offers 12 generic fits, including linear regression, logistic functions, fourier approximation, rationals, neural networks, B-splines and parametric curves least squares approximations, plus a library of over 300...


Platforms: Windows

Excel add-in with eleven powerful worksheet functions for 1, 2 and 3 variable lookup and interpolation. Interpolation modes include: closest-value, linear, piecewise parabolic or hyperbolic, cubic spline and polynomial up to 20th order. The functions can also handle tables containing missing and...


Platforms: Windows

It is known that there is no sufficient Matlab program about neuro-fuzzy classifiers. Generally, ANFIS is used as classifier. ANFIS is a function approximator program. But, the usage of ANFIS for classifications is unfavorable. For example, there are three classes, and labeled as 1, 2 and 3. The...


Platforms: Matlab

A command-line peak fitting program for time-series signals, written as a self-contained Matlab function in a single m-file. Uses an non-linear optimization algorithm to decompose a complex, overlapping-peak signal into its component parts. The objective is to determine whether your signal can be...


Platforms: Matlab

New users and old of optimization in MATLAB will find useful tips and tricks in this document, as well as examples one can use as templates for their own problems.Use this tool by editing the file optimtips.m, then execute blocks of code in cell mode from the editor, or best, publish the file to...


Platforms: Matlab

Genetic Programming (GP) generates nonlinear input-output models of dynamical systems from input-output measurement data. This GP-OLS toolbox applies Orthogonal Least Squares algorithm (OLS) to improve the search effeciency of GP.It can be used for static equation discovery or structure...


Platforms: Matlab

This toolbox contains a set of functions which can be used to compute the Least Median of Squares regression, the Reweighted Least Squares regression, the accociated location and scale estiamtors, and the Minimum Volume Ellipsoid. The concept is the minimization of the median of the squared...


Platforms: Matlab

A contour of a 2D region is defined by an ordered set of points where the neighboring elements contain the neighboring points. Such representation can be obtained with many techniques such as boundary tracing and chain codes. (In a simple 2D point set or a curve the points do not have to lie in a...


Platforms: Matlab

bgam - Boosted Generalized Additive Models package---Implements boosting for the Generalized Additive and Linear Models (GAM and GLM).Extensible, fully documented. Implements linear and stub learners,least-squares/logistic/Poisson regression.The generalized linear model (GLM) is a flexible...


Platforms: Matlab

Implementation of the well known Haralick Edge Detector.Here are the steps of the algorithm : (1) Fit a bi-cubic polynomial to a small neighborhood of each pixel (this step provides smoothing too). (2) Compute (analytically) the second and third directional derivatives in the direction of...


Platforms: Matlab

Use coeffs = fit2dPolySVD(x, y, z, order) to fit a polynomial of x and y so that it provides a best fit to the data z.Uses SVD which is robust even if the data is degenerate. Will always produce a least-squares best fit to the data even if the data is overspecified or underspecified.x, y, z are...


Platforms: Matlab

polyfitweighted2.m and polyval2.m---------polyfitweighted2.m: Find a least-squares fit of 2D data z(x,y) with an n th order polynomial, weighted by w(x,y).polyval2.m: Evaluate 2D polynomial produced by polyfitweighted2.m.Usage polyfitweighted2-----P = polyfitweighted2(X,Y,Z,N,W) finds the...


Platforms: Matlab

PDL::Fit::Levmar is a Perl module with Levenberg-Marquardt fit/optimization routines. Levenberg-Marquardt routines for least-squares fit to functions non-linear in fit parameters. This module provides a PDL ( PDL::PDL ) interface to the non-linear fitting library levmar (written in C). Levmar...


Platforms: *nix

Statistics::LTU is an implementation of Linear Threshold Units. SYNOPSIS use Statistics::LTU; my $acr_ltu = new Statistics::LTU::ACR(3, 1); # 3 attributes, scaled $ltu->train([1,3,2], $LTU_PLUS); $ltu->train([-1,3,0], $LTU_MINUS); ... print "LTU looks like this:n"; $ltu->print;...


Platforms: *nix