Regression

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...

CurveFitter program 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...

Regression mAKEr project is a simple modular application for data investigation. This is an application to help user (mathematician) to make regression between series of data, draw grpahics, and export them into various formats by means of common graphics packages (i.e., gnuplot, plotutils). It...


Platforms: *nix

The Multiple Regression Analysis and Forecasting template enables the confident identification of value drivers and forecasting business plan or scientific data. The multiple regression process utilizes commonly employed statistical measures to test the validity of the analysis and results are...


Platforms: Windows, Mac, Windows 8, Windows 7

Sagata Multiple Regression software offers the power of a professional regression package with the ease and comfort of a Microsoft Excel interface.Features include:Qualitative/Categorical Factors - often inputs or factors in model fitting are qualitative or categorical in nature, e.g., the type...


Platforms: Windows

The model relies on the theory of strength of least square curve fitting and auto regression techniques. Requirements: - MATLAB 7.5 or higher


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

The non-linear regression problem (univariate or multivariate) is easily posed using a graphical user interface (GUI) that solves the problem using one of the following solvers: - nlinfit: only univariate problems. - lsqnonlin: can deal with multivariate problems (more than one dependent fitting...


Platforms: Matlab

M-files for unimodality (or monotonically) constrained least squares regression.


Platforms: Matlab

INPUTS: x - vector row with 'x' values y - vector row with 'y' values r - expected 'x'-coordinate of break point if r is empty it is calculated during the optimisation p - if p is equal to 1 the fit is plotted OUTPUT: th - estimated paremeters of the regression lines y_1 = th(1) + th(2) * x y_2 =...


Platforms: Matlab

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


Platforms: Matlab

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...


Platforms: Windows, Windows 7, Other

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

Performs linear regression using the Least Squares method. Determines the regression coefficients, the generalized correlation coefficient and the standard error of estimate. Does multivariate regression. Displays 2D and 3D plots.


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

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

Quantile Regression USAGE: [p,stats]=quantreg(x,y,tau[,order,nboot]); INPUTS: x,y: data that is fitted. (x and y should be columns) Note: that if x is a matrix with several columns then multiple linear regression is used and the "order" argument is not used. tau: quantile used in regression....


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