Least Squares Fit Method

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

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.

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

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

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

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

It needs a set of 3D points, equal radii constraints and orientation constraint to fit an ellipsoid into a 3D block object


Platforms: Matlab

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

In this submission we present the code of the Replacement Method (RM) [1-4] and Enhanced Replacement Method (ERM)[5], that were proposed some time ago by our group. Both methods produce linear regression QSPR-QSAR models that are quite close the FS (full search) ones with much less computational...


Platforms: Matlab

rilt Regularized Inverse Laplace Transform [g,yfit,cfg] = rilt(t,y,s,g0,alpha) Array g(s) is the Inverse Laplace Transform of the array y(t), calculated by a regularized least squares method.This script is an emulation of S. Provencher CONTIN program, written in Fortran. See...


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

chemfem is a high order finite element method that can solve general partial differential equations and the reacting Navier Stokes equations in particular. Features . 2D PDE solver . Unstructured meshes . Higher order finite elements . Galerkin and Least squares, including discontinuous...


Platforms: *nix

SciCraft is an open source data analysis software developed in Python which allows you to access advanced mathematical functions through an easy-to-use graphical interface. Typical methods can be anything from areas like statistics, chemometrics and artificial intelligence and from languages like...


Platforms: Linux

If the signal frequency has to be guess, then it should be close to real frequency value. Requirements: - MATLAB 7.6 (R2008a)


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

Group and Block Sparse Signal reconstruction viaMatching Pursuit - BMP, GMPGradient Pursuit - block_gp, group_gpNearly Orthogonal Matching Pursuit - block_nomp, group_nompPartial Conjugate Gradient Pursuit - block_pcgp, group_pcgpOrthogonal Least Squares - BOLS, GOLS


Platforms: Matlab