Least Squares Examples

Functions NELSONFUN and NELSONFIT evaluate and fit (with non-linear least-squares) the Nelson-Siegel function, a popular yield-curve approximation device.

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...

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 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

Among the considerations in the use of analysis of regression, outliers or bad values can seriously disturb the least-squares fit. They falls far from the line implied by the rest of the data. If these points are really outliers, then the estimate of the intercept may be incorrect and the...


Platforms: Matlab

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

New users and old of optimization in MATLAB will find useful tips and tricks in this document, as well as examples one can use as templates for their own problems.Use this tool by editing the file optimtips.m, then execute blocks of code in cell mode from the editor, or best, publish the file to...


Platforms: Matlab

This toolbox contains a set of functions which can be used to compute the Least Median of Squares regression, the Reweighted Least Squares regression, the accociated location and scale estiamtors, and the Minimum Volume Ellipsoid. The concept is the minimization of the median of the squared...


Platforms: Matlab

Two simple models are provided showing the characteristics of basic iterative algorithms for the inversion of kinematics, namely the Jacobian transpose, its pseudo-inverse and the damped least-squares (DLS). The pro's and con's can be compared interactively for a serial two-links and a...


Platforms: Matlab

Statsmodels is a Python package that provides a complement to scipy for statistical computations including descriptive statistics and estimation of statistical models. Main Features regression: Generalized least squares (including weighted least squares and least squares with autoregressive...


Platforms: *nix

NMath Analysis contains classes for function minimization, root-finding, and linear programming. Product features include classes for minimizing univariate functions using golden section search and Brent's method, minimizing multivariate functions using the downhill simplex method, Powell's...


Platforms: Windows

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

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

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

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

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