Multivariate Nonlinear Regression

Let us assume the following MIMO model:Y(k)=HX(k)+Y(k)This file can detect the number of sources, i.e the size of the vector X(k) from the received signal Y(k). The noise is assumed spatially white and the number of receivers must be strictly greater than the number of sources. For more details...

Mean or standard deviation are usually computed for whole part of the analysed signal. However, sometimes we would like to know how this quantities are changing in the data flow. MEANSTDF compute the expected mean and standard deviation values using user defined window for every data position....

ENZyme KINetics is the study of the chemical reactions that are catalysed by enzymes. In enzyme kinetics the reaction rate is measured and the effects of varying the conditions of the reaction investigated. Studying an enzyme's kinetics in this way can reveal the catalytic mechanism of this...


Platforms: Matlab

SIMPGRIDSEARCH Multi-dimensional unconstrained nonlinear minimization using grid search + Simplex method. X = SIMPGDSEARCH(OBJFUN,GDVALUES) returns a vector X that is a minimizer of the function described in OBJFUN (usually an m file: OBJFUN.M).See OBJFUN_DEMO.M for how to write an objective...


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 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

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

This function will perform a local regression at the given points. Using the data at hand. You will need to input a spanwidth which will tell the function how many datapoints he will use in the local regression at each evaluation.Example...


Platforms: Matlab

L-BFGS-B is a collection of Fortran 77 routines for solving nonlinear optimization problems with bound constraints on the variables. One of the key features of the nonlinear solver is that the Hessian is not needed. I've designed an interface to the L-BFGS-B solver so that it can be called like...


Platforms: Matlab

The APMonitor Modeling Language is optimization software for differential and algebraic equations. It is coupled with large-scale nonlinear programming solvers for data reconciliation, real-time optimization, dynamic simulation, and nonlinear predictive control. It is available as a free web...


Platforms: Windows

The objective of this project is to make available an open-source version of our Multifactor Dimensionality Reduction (MDR) software. MDR is a nonparametric alternative to logistic regression for detecting and characterizing nonlinear interactions.


Platforms: Windows, Mac, Linux

pystats is a comprehensive Python module implementing algorithms for statistics and information theory, including probability distributions, descriptive statistics, analysis of variance, regression, and inference.


Platforms: Windows, Mac, Linux

This package includes files for modelling nonlinear dynamic systems using a recurrent generalized neural network. The learning scheme uses the complex method of nonlinear nonderivative optimization, thereby avoiding the problems of computing the derivative of an infinite impulse response filter...


Platforms: Matlab

Neural Network Based System Identification Toolbox Version 2The NNSYSID toolbox contains a number of tools for identification of nonlinear dynamic systems with neural networks. Several nonlinear model structures based on multilayer perceptron networks are provided and there are also many...


Platforms: Matlab

CodonW is a programme designed to simplify the Multivariate analysis (correspondence analysis) of codon and amino acid usage. It was written in ANSI compliant C. See the README file for more information.


Platforms: *nix

The Gaussian Kernel can be changed to any desired kernel. However such a change will not dramatically improve results. This is a variant of ridge regression using the kernel trick (Mercers Theorem).


Platforms: Matlab

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

process from the Book of Smith, Corripio - Automatic Process ControlContent:+ m-file linearization of nonlinear model+ m-file definition of the nonlinear model+ simulink models for the simulation of the process


Platforms: Matlab

The extended Kalman filter can not only estimate states of nonlinear dynamic systems from noisy measurements but also can be used to estimate parameters of a nonlinear system. A direct application of parameter estimation is to train artificial neural networks. This function and an embeded example...


Platforms: Matlab

This is a SAS(r) Software macro package for performing multipoint QTL mapping using the DeFries-Fulker multiple regression approach to unselected and selected samples.


Platforms: Windows, Mac, Linux