Least Squares Fit Method

Motofit co-refines Neutron and X-ray reflectometry data, using the Abeles matrix / Parratt recursion and least squares fitting (Genetic algorithm or Levenberg Marquardt). It works in the IGOR Pro environment (TM Wavemetrics). Platforms: Windows, Mac, Linux

Sake is a PHP implementation of Polynomial Least Squares Regression. The algorithm takes data points as input and returns the resulting polynomial. Graphs can be made using any plotting package. Sake provides the polynomial and will compute as many point Platforms: Windows, Mac, Linux

Tidal Analysis Program in PYthon (TAPPY) uses the least squares optimization function from scipy to perform a harmonic analysis (calculate amplitude and phases of a set of sine waves) of a hourly time series of water level values. Platforms: Windows, Mac, Linux

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

Both functions caculate the Lomb normalized periodogram (aka Lomb-Scargle, Gauss-Vanicek or Least-Squares spectrum) of a vector x with coordinates in t, which is essentially a generalization of the DFT for unevenly sampled data.The codes are transcriptions from Fortran of the subroutines found in... Platforms: Matlab

1 Introduction PLS-DA for data analysis in chemistry and OMICS studies. Also included in this package are 3 variable selection methods: 1) target projection (TP) 2) competitive adaptive reweighted sampling (CARS) 3) subwindow permutation analysis (SPA). SPA is based on model pupulation analysis... Platforms: Matlab

This is a wrapper function to solve optimization problems (using FMINCON) of the form:min w.r.t. X of CostFunc(X) = beta*(W_ls*F(X)) + (1 - beta)*(max(W_mm*F(X)))subject to: A*X Platforms: Matlab

The code implements the algorithm as given in Chen et. al 1991.It takes max tolerance from the user.It selects Ms significant regressors from the total M regressors.Unfortunately, the error obtained after training the RBF network isn't as expected. Is there a mistake in my code???Please feel free... Platforms: Matlab

An affine (or first-order) optic flow model has 6 parameters, describing image translation, dilation, rotation and shear. The class affine_flow provides methods to estimates these parameters for two frames of an image sequence.The class implements a least-squares fit of the parameters to... Platforms: Matlab

This library implements a randomized algorithm for solving the least-squares equation x = arg min norm(A * x - b, 2) or the underdetermined system min(norm(x, 2)) s.t. Ax=b. With high probability the running this o(mn^2) for an m-by-n matrix.For details of the solver see the paper at:Blendenpik:... Platforms: Matlab

This example solves a complex curve fitting problem that involves parameter pooling and stratification using a nonlinear least-squares approach. This example also takes advantage of some new language features with MATLAB 7. * Anonymous functions * Nested functions Platforms: Matlab

Solves the linear least squares problem with nonnegative variables using the newton's algorithm in:Portugal, Judice and Vicente, A comparison of block pivoting and interior point algorithms for linear least squares problems with nonnegative variables, Mathematics of Computation, 63(1994), pp.... Platforms: Matlab

Solves the linear least squares problem with nonnegative variables using the predictor-corrector algorithm in:Portugal, Judice and Vicente, A comparison of block pivoting and interior point algorithms for linear least squares problems with nonnegative variables, Mathematics of Computation,... 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

Like polyfit.m but includes weighting of each data point.Summary----------------Find a least-squares fit of 1D data y(x) with an nth order polynomial, weighted by w(x).Usage-----P = polyfitweighted(X,Y,N,W) finds the coefficients of a polynomial P(X) of degree N that fits the data Y best in a... Platforms: Matlab

For a given real-valued function of one real variable on an interval, the code calculates the best approximation in the uniform (max) norm by a polynomial of a given degree. Approximating in a uniform norm is much computationally harder compared to the standard least squares fit, but gives eye... Platforms: Matlab

This m-file computes an approximate determination coefficient (R2) for prediction, sayR2pred = 1 - (PRESS/SST)where PRESS = prediction error sum of squares, SST = total sum of squares.This statistic gives some indication of the predictive capability of the regression model. So, we could expect... Platforms: Matlab

This function either displays Zernike polynomials over a circular, hexagonal, elliptical, rectangular or annular shaped pupil, or fits surface data to these pupil shapes. See Mahajan, V.N., G.-m. Dai, "Orthonormal polynomials in wavefront analysis: analytical solution," J. Opt. Soc. Am. A, Vol.... 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

Performs polynomial fits that pass through a specified point (x0,y0).The application is to give a least squares fit that is 'exact' at a desired data point, e.g. an equilibrium point in a nonlinear equation of motion implemented via polynomial approximation. Discussion of theory included in... Platforms: Matlab