Curvilinear Regression Coefficients

Example code to accompany the "New Regression Capabilities" presentationExample code illustrating the use of the following Statistics Toolbox functionsLinearModelNonLinearModelGeneralizedLinearModel

CurveFitter performs statistical regression analysis to estimate the values of parameters for linear, multivariate, polynomial, exponential and nonlinear functions. The regression analysis determines the values of the parameters that cause the function to best fit the observed data that you...

The Multiple Regression Forecasting model provides a solid basis for identifying value drivers and forecasting data.While it utilises a range of commonly employed statistical measures to test the validity of the analysis, results are summarized in text for ease of use.Once relationships have been...


Platforms: Windows

StatsEasy Regression allows you to compute linear equation from simple regression, you get the equation with slope and intercept, it draws the line graph and scatter diagram.


Platforms: Any Browser + Java

DataFitting is a powerful statistical analysis program that performs linear and nonlinear regression analysis (i.e. curve fitting). DataFitting determines the values of parameters for an equation, whose form you specify, that cause the equation to best fit a set of data values. DataFitting can...


Platforms: Windows

Curvilinear: Easy Learning Plane Analytic Geometry An Intuitively-Easy-To-Use visual interactive software, oriented to overcome the abstraction that exists in the Plane Analytic Geometry (PAG), this is a tool that makes it easy to learn and master the PAG, the user is allowed to literally "see"...


Platforms: Windows

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

Toolbox for MMSE estimators of DFT coefficients under the generalized Gamma densityThe toolbox can also be downloaded from: http://ict.ewi.tudelft.nl/~richard/The matlab files enclosed in this toolbox can be used to tabulate gain functionsfor clean speech complex-DFT, magnitude-DFT and magnitude...


Platforms: Matlab

GMM-GMR is a set of Matlab functions to train a Gaussian Mixture Model (GMM) and retrieve generalized data through Gaussian Mixture Regression (GMR). It allows to encode efficiently any dataset in Gaussian Mixture Model (GMM) through the use of an Expectation-Maximization (EM) iterative learning...


Platforms: Matlab

mex c++ interface to call Eureqa server directly from matlabThe code enables symbolic regression with possible user-defined operators (such as +, -, *, /, ^, exp, log, sin, cos, abs, tan). Applications range from a detection of hidden data relationships to nonlinear regression of different kinds...


Platforms: Matlab

The art of fitting a nonlinear regression model often starts with choosing a model form. This submission is an attempt to teach the reader a simple but general paradigm for their models as a sum of fundamental shapes that are then shifted and scaled to fit the data.I've included a bestiary of...


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

Calculates 6 different intraclass correlation coefficients based on the schema described by Shrout & Fleiss (Psychol Bull. 1979;86:420-428). See comments in code.


Platforms: Matlab

The purpose of this file is to provide beginners a way to understand and analyse time varying coefficient values within regression analysis particularly with financial data analysis.The file is easily customisable to suit requirements and contains information describing the code for ease.I am new...


Platforms: Matlab

This function implements multivariant Gaussian kernel regression and smoothing. A few examples show how it can be used to smooth 3-d noisy images with missing data.For tutorial purpose, the function is implemented in the simplest form. Therefore, it is particularly suitable for beginners to learn...


Platforms: Matlab

Leave-one-out cross-validation for PLS regression or discriminant analysispls_cv = plscv(x,y,vl,'da')input:x (samples x descriptors) for cross-validationy (samples x variables) for regression or (samples x classes) for discriminant analysis. Classes numbers must be >0.vl (1 x 1) number of latent...


Platforms: Matlab

Orthogonal Linear Regression in 3D-space by using Principal Components AnalysisThis is a wrapper function to some pieces of the code from the Statistics Toolbox demo titled "Fitting an Orthogonal Regression Using Principal Components...


Platforms: Matlab

Kernel Regression ToolboxVersion 1.0 (R14) 01-Aug-2004General information. Comprises functions to carry out kernel regressions.General Functions: ykr - Higher order olynomial kernel regression ykr0 - 0-th order kernel regression wfunc - Exponential matrix theory kernal functions gfunc -...


Platforms: Matlab

The aim of this application is to implement scalable mpeg type compression by varying DCT coefficients and finding minimum number of DCT coefficients that can give minimum acceptable quality..This application only works for gray scale.Although this program will do its work but its slow.This code...


Platforms: Matlab

ECR is a new method for regression analysis, which employs a supervising alpha to supervise the X-matrix decomposition. When alpha=0, ECR coincides with principal component regression (PCR), when alpha=1, ECR coincides with partial least squares (PLS), when alpha is between 0 and 1, ECR could...


Platforms: Matlab