Least Squares Regression

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 zip includes:(1) lsqAffineSpace: a 'low level' routine that takes a set of m-dimensional real sample data and returns the optimal-fit k-dimensional affine subspace, with some options for discarding outliers.(2) lsqPlane and lsqLine: lsqAffineSpace wrappers, that compute optimal line and... 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

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

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

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

Is a cross-platform software package for econometric analysis, written in the C programming language. It is free, open-source software. You may redistribute it and/or modify it under the terms of the GNU General Public License (GPL) as published by the Free Software Foundation. Features Easy... Platforms: Windows

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

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

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

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

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

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

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

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

4 files are included in the package:(1) fs01.m - the 1st-order local linear approximation (LLA) very similar to algorithm by Farmer and Sidorowich (1987). Uses constrained linear least squares (lsqlin) and(2) ts1.m - to reconstruct the vectors of the state space.(3) Example.m - runs fs01 and ts1... 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