Regres Plus is an advanced mathematical modeling software that is extremely user-friendly, offering state-of-the-art features to its users.
Regress+ is a powerful software tool designed for mathematical modeling that models simple, univariate equations and stochastic models with no more than five parameters. It is easy to use and offers exceptional features that cannot be matched by any other program. Here are some of the key features of Regress Plus:
General
- The ability to model simple, univariate equations and stochastic models
- Robust goodness-of-fit testing to optimize the model
- Creates confidence intervals for parameters using the BCa technique
- Optional freezing of initial parameter estimates
- Provides choice of optimization criterion
Deterministic Modeling
- 22 Built-in families of models which allow users between 1 to 10 parameters
- Special Simulated Annealing mode helps to find an initial parameter estimate
- Optimization criteria includes Least-squares, Minimum average deviation, and weights (for the dependent variable, y)
- Generates a listing of fitted data and residuals
Stochastic Modeling
- Includes 56 Built-in distributions (30 Continuous, 17 Continuous binary mixtures, 5 Discrete, 4 Discrete binary mixtures)
- Optimization criteria include Maximum-likelihood (all), Minimum Kolmogorov-Smirnov statistic (continuous variates), and Minimum Chi-square (discrete variates)
- Optional discrete input may be grouped
- Creates samples of random variates (textfiles)
In addition to the above features, Regress Plus provides intelligent dialogs that allow it to run unattended and/or in the background. It also allows unlimited comments by way of textfile input and produces both text and graphical output. A single keystroke allows the user to make a plot which can be saved as a PICT. Extensive documentation in PDF format is also available, including a tutorial (50 pp.), users' guide (36 pp.), technical details and references (8 pp.), and a compendium of common probability distributions (120 pp.). Four pages are dedicated to error messages and there are numerous sample datafiles available to help the user get started.
Regress+ is a software tool that is unmatched in its functionality and ease of use, making mathematical modeling a breeze for both deterministic and stochastic models.
General
- The ability to model simple, univariate equations and stochastic models
- Robust goodness-of-fit testing to optimize the model
- Creates confidence intervals for parameters using the BCa technique
- Optional freezing of initial parameter estimates
- Provides choice of optimization criterion
Deterministic Modeling
- 22 Built-in families of models which allow users between 1 to 10 parameters
- Special Simulated Annealing mode helps to find an initial parameter estimate
- Optimization criteria includes Least-squares, Minimum average deviation, and weights (for the dependent variable, y)
- Generates a listing of fitted data and residuals
Stochastic Modeling
- Includes 56 Built-in distributions (30 Continuous, 17 Continuous binary mixtures, 5 Discrete, 4 Discrete binary mixtures)
- Optimization criteria include Maximum-likelihood (all), Minimum Kolmogorov-Smirnov statistic (continuous variates), and Minimum Chi-square (discrete variates)
- Optional discrete input may be grouped
- Creates samples of random variates (textfiles)
In addition to the above features, Regress Plus provides intelligent dialogs that allow it to run unattended and/or in the background. It also allows unlimited comments by way of textfile input and produces both text and graphical output. A single keystroke allows the user to make a plot which can be saved as a PICT. Extensive documentation in PDF format is also available, including a tutorial (50 pp.), users' guide (36 pp.), technical details and references (8 pp.), and a compendium of common probability distributions (120 pp.). Four pages are dedicated to error messages and there are numerous sample datafiles available to help the user get started.
Regress+ is a software tool that is unmatched in its functionality and ease of use, making mathematical modeling a breeze for both deterministic and stochastic models.
What's New
Version 2.5.3: N/A