Linear Least Squares Fit

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

Function: Savitzky-Golay Smoothing and Differentiation Filter The Savitzky-Golay smoothing/differentiation filter (i.e., the polynomial smoothing/differentiation filter, or the least-squares smoothing/differentiation filters) optimally fit a set of data points to polynomials of different degrees.... 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

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

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

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

This function implements a method of using genetic algorithms to optimise the form of a polynomial, i.e. reducing the number of terms required in comparison to a least-squares fit using all possible terms, as described in the following paper:Clegg, J. et al, "The use of a genetic algorithm to... 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

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

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

This is a fast and non-iterative ellipse fit. Usage: A = EllipseDirectFit(XY)Input: XY(n,2) is the array of coordinates of n points x(i)=XY(i,1), y(i)=XY(i,2) Output: A = [a b c d e f]' is the vector of coefficients of the equation of the best fitting ellipse: ax^2 + bxy + cy^2 + dx + ey + f =... Platforms: Matlab

LAPACK is a linear algebra library, based on LINPACK and EISPACK. LAPACK is written in Fortran77 and provides routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems. The associated... 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

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

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... Platforms: Matlab

FitChiTool provides an interface similar to the Curve Fitting Toolbox to the fitChiSquare function.This allows you to perform fits using chi-square when measurement errors are known on linear or nonlinear models. It allows allows you to perform fits with multiple independent (more than one x)... Platforms: Matlab

Inputs: 1. a 1 dimensional array of drug concentrations 2. the corresponding m x n array of responses Algorithm: generate a set of initial coefficients including the Hill coefficient fit the data to the 4 parameter dose-response curve using nonlinear least squares Output: a matrix of the 4... Platforms: Matlab

The Kernel-Machine Library is a freely available (released under the GPL) C++ library to promote the use and progress of kernel machines. It is both for academic use and for developing real world applications. The Kernel-Machine Library draws heavily from features of modern C++ such as template... Platforms: *nix

Sagata Multiple Regression software offers the power of a professional regression package with the ease and comfort of a Microsoft Excel interface.Features include:Qualitative/Categorical Factors - often inputs or factors in model fitting are qualitative or categorical in nature, e.g., the type... Platforms: Windows