... is a powerful statistical analysis program that performs linear and nonlinear regression analysis (i.e. curve fitting). DataFitting determines the values ... a set of data values. DataFitting can handle linear, exponential, polynomial and general nonlinear functions. DataFitting performs true nonlinear regression analysis, it does not transform the function into a linear form. As a result, it can handle functions ...

... digitizing tool. FindGraph offers 12 generic fits, including linear regression, logistic functions, fourier approximation, rationals, neural networks, B-splines and parametric curves least squares approximations, plus a library of over 300 industry-specific 2D formulas. FindGraph ...

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 ... set which can include a wide array of linear and nonlinear models for any application. Its state-of-the-art ...

... is a powerful statistical analysis program that performs linear and nonlinear regression analysis (i.e. curve fitting). DataFitting determines the values ... a set of data values. DataFitting can handle linear, polynomial, exponential, and general nonlinear functions. DataFitting performs true nonlinear regression analysis, it does not transform the function into a linear form. As a result, it can handle functions ...

... using BLAS and LAPACK libraries when available. Numerous linear algebra and mathematical operations are defined for the ... SMO based Support Vector Machines for classification and regression Reduced-rank methods for large-scale classification and regression Relevance vector machines for classification and regression General purpose multiclass classification tools A Multiclass SVM ... structural support vector machines. An online kernel RLS regression algorithm An online SVM classification algorithm An online ...

... package. PSPP can perform descriptive statistics, T-tests, linear regression and non-parametric tests. Its backend is designed to perform its analyses as fast as possible, regardless of the size of the input data. You ...

... numeric and symbolic calculations (integration, differentiation, smoothing, etc), linear and nonlinear NLSF (Levenberg-Marquardt) regression analysis, configurable user interface and more. You can visualize, edit and analyze data produced by any instruments with RS-232 interface or another numerical data ...

... Median smoothing. - Exponential smoothing: single, double. - Regressions: Polynomial (Constant, Linear, Quadratic, Cubic, 4th, 5th), Exponential, Modified Exponential, Power, Gompertz, Logistic. - Regressions residuals. - Autocorrelations: ACF, PACF. - Box-Jenkins : ...

... Analysis (PCA) · Multivariate Curve Resolution (MCR) · Regression (MLR, PCR, PLS-R, 3-way PLS-R) · Prediction from ... Gap-Segment and Savitzky Golay · Baseline offset and Linear Baseline correction · Standard Normal Variate (SNV) · ... Correlation Loadings, Stability Plot, Bi-plot, Leverages, Variances, RMSE, Regression coefficients, Predicted vs. Measured, Residuals, Response Surface?) · ...

... Also includes Components and routines covering Probability Distributions, Linear Regression, Hypothesis Analysis, Equation Solving and more. The subset includes a good collection of Edits, SpinEdits, ComboBoxes, Memos, CheckBoxes, RadioGroups, CheckGroups as well as a ...

... problems. Synonyms are data fitting, nonlinear regression, parameter identification, curve and surface fitting. The numerical ... 2,000 time values 3,000 experimental data 200 linear or nonlinear constraints - limited by size of ... on parameters to be estimated tabulated data, splines, linear and piecewise constant interpolation indexed variables and functions ...

... built-in formulas including specialized numerical functions: matrix decompositions; linear equation sets with improving iterations; least squares (weighted, constrained), regression with orthogonal polynomials; time series analysis; minimization; linear, integer and quadratic programming. * Array formulas and ...

DataScene is a scientific graphing, graph animation, data analysis, curve fitting, and data monitoring program. It allows the user to easily plot 2D & 3D graphs (Area, Bar, Pie, Line, Surface, Ploar, and more), to manipulate, print, and export high quality graphs, to analyze data with various mathematical methods (fitting curves, ...

... Oscillator... Ability to draw Trend Lines, Fibonacci retracement, linear regression and Gann Angles as well as Fibo lines and extensions. Semi-log or linear scale OHLC, Japanese candlesticks, Heikin-Ashi or simple curve ...

... including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics, partial ... Poisson, Student's t, triangular, and Weibull distributions. Multiple linear regression. Basic hypothesis tests, such as z test, t-test, ...

... support enabled. - super conductive memory manager allows linear scaling with number of CPU cores. - LAPACK ... - Descriptive statistics - Hypothesis testing - Weighted/unweigted linear and multiple linear regression. - Weighted/unweighted non-linear regression - Time series analysis (ARMA, ARIMA, ARAR, MA, ...

This software offers a solution for users who need to look at basic statistics for a set of numbers quickly. This software calculates: mean, median, mode, variance, sum, standard deviation, average deviation, coefficient of deviation, total, square total, and variance. By processing numbers with a simple interface, this software will save ...

... parametric curves. · Fit data to curves using linear, exponential, logarithmic, power, quadratic, or cubic regression. · Utilize over twenty functions for descriptive and inferential statistics. ...

... Matrix (Pearson and Spearman’s Rank Correlation) • Multiple Linear Regression • Binary and Ordinal Logistic Regression • Chi-Square Test (Stacked Column data and Two-Way ...

... data can be modelled using a toolbox of linear regression models, nonlinear regression models, interpolation, or splines. Over 30 models are built-in, but custom regression models may also be defined by the user. ... easily. FEATURES: · Over 35 built-in regression models to choose from, along with over 15 ...

... Data can be modelled using a toolbox of linear regression models, nonlinear regression models, smoothing methods, or various kinds of splines. Over 60 models are built-in, but custom regression models may also be defined by the user. ... zooming, panning, autoscaling, and view stack capability. Multivariate: linear and nonlinear regressions can be computed for datasets ...

... Data can be modelled using a toolbox of linear regression models, nonlinear regression models, smoothing methods, or various kinds of splines. Over 60 models are built-in, but custom regression models may also be defined by the user. ... zooming, panning, autoscaling, and view stack capability. Multivariate: linear and nonlinear regressions can be computed for datasets ...

... Data can be modelled using a toolbox of linear regression models, nonlinear regression models, smoothing methods, or various kinds of splines. Over 60 models are built-in, but custom regression models may also be defined by the user. ... zooming, panning, autoscaling, and view stack capability. Multivariate: linear and nonlinear regressions can be computed for datasets ...

... displayed the "line of best fit" (which uses linear regression analysis) to supporting chart types. Automatically calculate and have displayed the "moving average" to supporting chart types. Data values can be integer, floating point ...

... Cubic Method is a new method for data regression analyse , it expanded Least Square Method, According ... can be used to work out single factor linear data regression, multi factors linear data regression, single factor non-linear data regression, and multifactors non-linear data regression. ...