Method Of Least Squares

Statistics::GaussHelmert is a general weighted least squares estimation module. SYNOPSIS use Statistics::GaussHelmert; # create an empty model my $estimation = new Statistics::GaussHelmert; # setup the model given observations $y, covariance matrices # $Sigma_yy, an initial guess $b0...

The function LMFsolve.m serves for finding optimal solution of an overdetermined system of nonlinear equations in the least-squares sense. The standard Levenberg- Marquardt algorithm was modified by Fletcher and coded in FORTRAN many years ago. LMFsolve is its essentially shortened version...

Given numbers of votes for a list of parties and a fixed total number of seats, the method of Sainte-LagudoTz allocates seats to each party. The article at http://en.wikipedia.org/wiki/Sainte-Lagu%C3%AB_method describes details of the method. The Matlab function sainte_lague can also return the...


Platforms: Matlab

The function computes parameters a, b, and c of the weighted orthogonal least squares fit of line ax+by+c=0 to a set of 2D points with coordinates given by x and y and weights w.n=100;x=1:n;y=2.5*x + (5+300./x).*randn(1,n);plot(x,y,'.k')hold onw=1:n;[a b c] = wols(x,y,w);plot([0,n],[-c/b,-c/b -...


Platforms: Matlab

BestCurFit calculates the parameters of 12 curves using the method of Linear Least Squares, fitting each curve to user data. The nonlinear equations are linearized. The obtained parameters are used for following optimization procedure using Simplex and Gauss-Newton algorithm. If it does not...


Platforms: Windows

1 Introduction This toolbox implements all the routine PLS-related/based algorithms which kind of serves as the basics in chemometrics, including PLS calibration and prediction, leave one out cross validation (LOOCV), K-fold cross validation, Monte Carlo cross validation(MCCV), double cross...


Platforms: Matlab

Performs linear regression using the Least Squares method. Determines the regression coefficients, the generalized correlation coefficient and the standard error of estimate. Does multivariate regression. Displays 2D and 3D plots.


Platforms: Windows

Gravers Football Squares project is a Web-based version of Superbowl Squares. Gravers Football Squares was created so multiple people could enjoy Football Squares during the Superbowl or any other major game that may be going on. Ive been using it for the last few years, and thought I would...


Platforms: *nix

This is the fastest (though not most accurate) method of fitting a circlle to data points on a plane (given by their xy-coordinates). It returns the circle center (a,b) and radius R. It was proposed by I. Kasa in article "A curve fitting procedure and its error analysis", IEEE Trans. Inst. Meas.,...


Platforms: Matlab

Cosinor analysis uses the least squares method to fit a sine wave to a time series. Cosinor analysis is often used in the analysis of biologic time series that demonstrate predictible rhythms. This method can be used with an unequally spaced time series. Follows cosinor analysis of a time series...


Platforms: Matlab

For a system having multiple inputs x and outputs y, the partial coherence is the coherence computed between any individual input and the output when the effect of all other inputs is removed from the output by a linear least squares prediction. This coherence obeys the usual inequality, and will...


Platforms: Matlab

The code implemented a special case of the ellipsoid fitting technique proposed in the paper Least Squares Ellipsoid Specific Fitting, corresponding to case k= 4. Just put the two files in the same directory and run "testFit4". You can change the noise level to observe the fitting accuracy and...


Platforms: Matlab

Demonstrates a way to implement the LSM algorithm.This is done on a example from the book of Astrom and Wittenmark, Adaptive Control, 2nd ed


Platforms: Matlab

The code implements the shooting method by means of the Runge-Kutta method of 4th order and the interval bisection method. There is the graphical interface too. When the differential equation is inserted in terms of the standard mathematical notation (no in MATLAB code), the programme create the...


Platforms: Matlab

The Unscrambler® is the complete multivariate analysis and experimental design software, equipped with powerful methods including Principal Component Analysis (PCA), Multivariate Curve Resolution (MCR), Partial Least Squares Regression (PLS-R), 3-Way PLS Regression, K-Means Clustering and SIMCA...


Platforms: Windows

DMFitter ActiveX control allows you to add sophisticated regression analysis tools to your software in a few lines of code. Features include: both linear and nonlinear (Levenberg-Marquardt) least squares curve fitting algorithms, arbitrary user models (defined analytically or by string...


Platforms: Windows

The DynaFit application was developed to perform nonlinear least-squares regression of chemical kinetic, enzyme kinetic, or ligand-receptor binding data. The experimental data can be either initial reaction velocities in dependence on the concentration of varied species (e.g., inhibitor...


Platforms: Windows

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

The model relies on the theory of strength of least square curve fitting and auto regression techniques. Requirements: - MATLAB 7.5 or higher


Platforms: Windows, Mac, *nix, Matlab, BSD Solaris