Method Of Least Squares

OLS - Orthogonal Least Squares: Proposed by T. Blumensath, M. E. DaviesStOLS - Stagewise OLS: Combining StOMP ideas with OLSROLS - Regularized OLS: Combining ROMP ideas with OLS

Implements the Complex Method of Constrained Optimization, as proposed by Box (1965), improved by Guin (1968) and Krus (1992), and following the method in Andresson (2001). This is capable of optimizing a "black-box" system with few constraints on the optimization function and requiring no...

The design matrix of a GPS network is established for any kind of least squares adjustment, namely;-free (trace minimum),-minimum constrained,-over-determined.The user can adapt easily dmgps to the adjustment problem of a GPS network whose baselines are taken as observations. Moreover, it can be...


Platforms: Matlab

The function The LMFnlsq.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 (see the Reference). This version of LMFnlsq is...


Platforms: Matlab

Statistics::LineFit module least squares line fit, weighted or unweighted. SYNOPSIS use Statistics::LineFit; $lineFit = Statistics::LineFit->new(); $lineFit->setData (@xValues, @yValues) or die "Invalid data"; ($intercept, $slope) = $lineFit->coefficients(); defined $intercept or die...


Platforms: *nix

Statistics::OLS is a Perl module to perform ordinary least squares and associated statistics. SYNOPSIS use Statistics::OLS; my $ls = Statistics::OLS->new(); $ls->setData (@xydataset) or die( $ls->error() ); $ls->setData (@xdataset, @ydataset); $ls->regress(); my ($intercept, $slope)...


Platforms: *nix

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...


Platforms: *nix

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...


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

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

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

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

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

zpkfit uses the nonlinear least-squares fitter (lsqnonlin) to fit an analytic model of any (fixed) number of poles and zeroes to numerical (presumably measured) frequency response data. It takes as arguments a frequency vector, a frequency response vector, and vectors of the initial guesses of...


Platforms: Matlab