Software Listing: Multivariate Regression

The Multivariate Regression Composer, a Matlab toolbox. It generates a regression model of the optimal structure. Uses the source data set, the initial models and the primitive functions.
MVR Composer License - GNU General Public License (GPL).

  • Platform: WinOther

UltimaCalc is a scientific and mathematical calculator designed to occupy minimum screen area, making it immediately available for use. UltimaCalc can stay on top of other windows. Type a calculation as plain text, evaluate it, maybe edit it and re-calculate. Has a comprehensive context-sensitive help system. Calculates to 38 digit precision. The display can be limited to just 8, 12 or 16 digits, and digits grouped for readability. Two 'scientific' view modes show numbers always in exponent format. The 'engineering' mode uses suffixes such as k (kilo) and M (mega). View results in hexadecimal and as ratios.

  • Publisher: UltimaCalc
  • Date: 14-06-2006
  • Size: 3112 KB
  • Platform: Win2000, Windows Server, WinOther

UltimaCalc Professional is a highly functional graphing math toolbox with a compact and intuitive design offering the ultimate balance of power and convenience. Its algebra module lets you perform manipulations and simplifications on basic and complex algebraic expressions. UltimaCalc lets you do calculus: differentiate an expression, or find its integral and ask how this was found. You can factorise polynomials, multiply and divide one polynomial by another, find the GCD of two polynomials. Expand and contract trig expressions. Calculate Taylor series, define your own functions, and calculate exact results (try evaluating the factorial of 1000).

  • Publisher: UltimaCalc
  • Date: 29-08-2008
  • Size: 3223 KB
  • Platform: Win2000, Windows Server, Windows Vista, WinOther

Implement data analysis and multivariate statistical analysis. 1. Probability analysis. 2. Compute descriptive statistics of selected data - compute probability density function values, cumulative density function values, quantile values, means and variances. 3. Frequency analysis. 4. Compare means- one sample t test, independent-samples t test and paired-samples t test. 5. Compare variances. 6. Variance analysis - one-way ANOVA and two-way ANOVA. 7. Univariate linear regression and multivariate linear regression. 8. Linear curve fitting and nonlinear curve fitting. 9. Excel-like data editor is easy to use.

  • Publisher: GraphNow
  • Date: 01-12-2008
  • Size: 2216 KB
  • Platform: Win2000, Windows Vista, WinOther

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 variable, ydata is a matrix). - patternsearch: this solver is useful to obtain a good start point, before using nlinfit or lsqonolin; this way, the global minimum is determined easier. Data is introduced in the GUI as vector or matrix from the workspace. The model to be fitted must be written in an M-file in vectorized form: ypred = model(x,xdata) ypred is a column vector (univariate problem) or matrix (multivariate problem) with the model response (observations in rows).

  • Platform: Matlab, Scripts

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 you provide. This process is also called curve fitting. Fit thousands of data into your equations in seconds: Curvefitter gives scientists, researchers and engineers the power to find the ideal model for even the most complex data, including equations that might never have been considered. You can build equation set which can include a wide array of linear and nonlinear models for any application.

  • Platform: Win2000, Win7 x32, WinOther, WinVista

The Unscrambler® is the complete multivariate analysis and experimental design software, equipped with powerful methods including Principal Component Analysis (PCA), Multivariate Curve Resolution (MCR), Partial Least Squares Regression (PLS-R), 3-Way PLS Regression, K-Means Clustering and SIMCA Classification.

Extensively used across a wide range of research and industrial applications including advanced Chemometrics, Spectroscopy and cutting-edge Sensometrics, this market-leading software yields demand-driven formulations, process optimization, cost- savings and increased ROI in product development, process control, quality control and R&D.

  • Publisher: CAMO
  • Date: 03-06-2011
  • Size: 31755 KB
  • Platform: Win2000, Windows Server, WinOther

Graphical user interface driven first-order multivariate calibration using up-to-date methods, including PCR, PLS, net analyte methods and ortoghonal signal correction. Provides a variety of pre-processing tools, cross-validation plots, prediction plots, elliptical joint region plots, net analyte signal regression plots, and additional information on statistical analysis of results. Includes a user manual and example data..

  • Platform: Matlab, Scripts

RF-ACE is an efficient implementation of a robust machine learning algorithm for uncovering multivariate associations, building predictors, and predicting novel data, either with classification or regression tree ensembles, from large and diverse data sets.

RF-ACE natively handles numerical and categorical data with missing values, and in feature selection potentially large quantities of noninformative features are handled gracefully utilizing artificial contrast features, bootstrapping, and p-value estimation.

The application implements both Gradient Boosting Tree (GBT) and Random Forest (RF) algorithms.

  • Platform: WinOther

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 provide. This process is also called curve fitting. Fit thousands of data into your equations in seconds: CurveFitter gives scientists, researchers and engineers the power to find the ideal model for even the most complex data, including equations that might never have been considered. You can build equation set which can include a wide array of linear and nonlinear models for any application.

  • Platform: Win2000, Win7 x32, Win7 x64, Win98, WinOther, WinVista, WinVista x64, WinXP, Other

ndCurveMaster was designed to find optimum equations to describe empirical data using a regression method. ndCurveMaster is the first and only program to find the ideal equation to allows the auto fitting of an unlimited number of input variables, for example: y= a0 + a1*x1^(-11) + a2*x3 + a3*x5^3 + a4*[ln(x8)]^3 + a5*[exp(x1*x4)]^(-2) + a6*x1*x8^2 + a7*ln(x2*x6) + a8*x2*x3*x4. ndCurveMaster uses heuristic techniques for curve fitting. The software is designed with the purpose of generating high quality results and output while saving your time in the process. ndCurveMaster compares very favourably to the competition and does so at a lower price.

  • Platform: Mac OS X

The Multiple Regression Analysis and Forecasting model provides a solid basis for identifying value drivers and forecasting business plan 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 identified, forecasting can be accomplished based on a range of available methodologies..

  • Platform: WinOther

LAB Fit is a software for Windows developed for treatment and analysis of experimental data. At LABFit program you are able to: 1) Treat similar data (grouped and ungrouped dataset, one or two samples); 2) Treat non-similar data; 3) Determine propagated error (error propagation up to eight independent variables); 4) Plot 2D and 3D graph (normal, parametric, imported dataset, contour of maps); 5) Execute math calculations (system of linear equations, roots of function, non-linear equation, ordinary differential equation - ODE up to fifth order, system of differential equations - up to five first order ODE, calculator, etc); 6) Extract data (x;y) from a 2D graph (digitizing); 7) Curve Fit (nonlinear regression - least squares method, Levenberg-Marquardt algorithm - with almost 500 functions at the library, with 1 and 2 independent...

  • Platform: Unix, Win2000, WinOther
  • DRS
  • License: Demo
  • Price: 108
  • Rating

People will obtain many relating data of two or more than two dimension during experiments and production. These data will help them to solve problems of reality on contrary, which need data processing to make them become mathematicalematical model reflecting the data variation regulation. The application of the Least Square Method can only make linear regression, but to the nonlinear problems it must construct relating mathematicalematical relationship expression, namely mechanism model through procedure supposing to do linearization processing of mechanism model and then do regression modeling computation.

  • Platform: Win2000, Windows Server, WinOther

Calculates regression different models and tests includes Pearson's Correlation Coefficient, Ordinary Least Square, Coefficient of Determination, Statistical Test of Significance. Also the software provides narrative explanation of data analysis. All about Afghanistan - Welcome. Afghanistan history, culture and people, Islam, Afghanistan Economic, Economy of Afghanistan, Afghani Music, Afghan students of Economics.

  • Platform: Win2000, Win7 x32, Win7 x64, Windows Server, WinOther, WinVista, WinVista x64
  • License: Freeware
  • Price: 0.00
  • Rating

Despite the fact that many phenomenon in physical or social sciences involve interaction between causal factors, it seems that very few researchers using multiple regression or structural equation modeling techniques do investigate for the presence of those interactions. If fact, in the context of multiple regression, a statistically significant interaction is often perceived as a curse by researchers, as something that jeopardize their effort to identify simple causal factors. This perception is somewhat reinforced by the fact that many statistical textbooks refer to a statistically significant interaction solely as an indication that an important assumption of multiple regression has been violated (namely the additivity assumption) without further instruction on how to deal with such an interaction.

  • Platform: WinOther

TMVA is a ROOT-integrated toolkit for multivariate classification and regression analysis. TMVA performs the training, testing and performance evaluation of a large variety of multivariate methods..

  • Platform: Linux, Unix

To walk through the code and for a thorough description, refer to A. Meucci (2009) , "Review of Statistical Arbitrage, Cointegration, and Multivariate Ornstein-Uhlenbeck", Latest version of article and code available at

  • Platform: Matlab, Scripts

We use the power of symbolic toolbox in order to find the optimal point in an arbitrary multivariate function Change the following code based on your objective function and run the program Function F in Symbolic Format a='(x1^2+x2-11)^2+(x1+x2^2-7)^2'; The code will iterate and converge to x and y of the optimal point.

  • Platform: Matlab, Scripts

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

  • Publisher: Rasmus Bro
  • Date: 09-03-2013
  • Size: 10 KB
  • Platform: Matlab, Scripts

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